From d9c37d92b2ace413ea0ff7834eedbc2750cb37a2 Mon Sep 17 00:00:00 2001 From: Gaurav Sheni Date: Tue, 4 Jul 2023 13:59:45 -0400 Subject: [PATCH] Continue replacement of TableMeta with ColumnSchema and Logical Types (#85) * WIP * finished test pp * wip * fix sample * fix sample * cleanup examples * changelog * speed up int tests --- .github/workflows/tests.yaml | 9 +- Examples/chicago_example.ipynb | 1191 - Examples/covid_example.ipynb | 322 - Examples/youtube_example.ipynb | 21857 ---------------- Makefile | 3 +- README.md | 31 + ... Bike Example - Detailed Walkthrough.ipynb | 440 - ...Covid Example - Detailed Walkthrough.ipynb | 122 +- docs/Quickstart - Covid Example.ipynb | 498 - docs/Yelp - End to End.ipynb | 372 - docs/changelog.md | 3 +- tests/ops/test_aggregation_ops.py | 6 +- tests/ops/test_filter_ops.py | 2 +- tests/ops/test_op_base.py | 6 +- tests/test_load_functions.py | 9 +- tests/test_prediction_problem.py | 410 +- tests/test_table_meta.py | 31 + trane/__init__.py | 2 + trane/column_schema.py | 75 + trane/core/prediction_problem.py | 5 +- trane/core/prediction_problem_generator.py | 15 +- trane/core/utils.py | 28 + trane/datasets/load_functions.py | 5 +- trane/logical_types.py | 49 + trane/ops/aggregation_ops.py | 53 +- trane/ops/filter_ops.py | 14 +- 26 files changed, 690 insertions(+), 24868 deletions(-) delete mode 100644 Examples/chicago_example.ipynb delete mode 100644 Examples/covid_example.ipynb delete mode 100644 Examples/youtube_example.ipynb delete mode 100644 docs/Chicago Bike Example - Detailed Walkthrough.ipynb delete mode 100644 docs/Quickstart - Covid Example.ipynb delete mode 100644 docs/Yelp - End to End.ipynb create mode 100644 tests/test_table_meta.py create mode 100644 trane/column_schema.py create mode 100644 trane/core/utils.py create mode 100644 trane/logical_types.py diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index 44640b3d..1b66b8fb 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -10,16 +10,16 @@ on: - main workflow_dispatch: jobs: - unit_tests: - name: ${{ matrix.python_version }} unit tests ${{ matrix.type_of_tests }} + tests: + name: ${{ matrix.python_version }} ${{ matrix.type_of_tests }} tests runs-on: ubuntu-latest strategy: matrix: python-version: ["3.8", "3.11"] - type_of_tests: ["unit tests", "integration tests"] + type_of_tests: ["unit", "integration"] exclude: - python-version: "3.8" - type_of_tests: "integration tests" + type_of_tests: "integration" steps: - uses: actions/checkout@v3 - name: Set up python ${{ matrix.python-version }} @@ -40,6 +40,7 @@ jobs: if: (steps.cache.outputs.cache-hit == 'true') && ( github.event.pull_request.title != 'Automated Latest Dependency Updates') run: python -m pip install --no-dependencies . - name: Run unit tests + if: ${{ matrix.type_of_tests != 'integration tests' }} run: make unit-tests - name: Run integration tests if: ${{ matrix.type_of_tests == 'integration tests' }} diff --git a/Examples/chicago_example.ipynb b/Examples/chicago_example.ipynb deleted file mode 100644 index a368af84..00000000 --- a/Examples/chicago_example.ipynb +++ /dev/null @@ -1,1191 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "7efd117b", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "import warnings\n", - "\n", - "# warnings.filterwarnings(\"ignore\")\n", - "warnings.filterwarnings(\"ignore\", category=DeprecationWarning)\n", - "\n", - "import copy\n", - "import json\n", - "import pandas as pd\n", - "import os\n", - "import sys\n", - "import featuretools as ft\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib\n", - "\n", - "%matplotlib inline\n", - "\n", - "sys.path.append(\"../../\")\n", - "from Trane import trane as trane\n", - "from datetime import datetime, timedelta" - ] - }, - { - "cell_type": "markdown", - "id": "8d67ebc9", - "metadata": {}, - "source": [ - "### Upload of the dataset and metadata" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "f1b249d7", - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_csv(\"./chicago-bike/data/bike-sampled.csv\", sep=\",\")\n", - "df[\"date\"] = df[\"date\"].apply(lambda x: datetime.strptime(x, \"%Y-%m-%d\"))\n", - "df = df.sort_values(by=[\"date\"])\n", - "df = df.fillna(0)\n", - "meta = trane.TableMeta(json.loads(open(\"./chicago-bike/data/meta.json\").read()))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "2eef38b2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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datehourusertypegendertripdurationtemperaturefrom_station_iddpcapacity_startto_station_iddpcapacity_end
1038052017-01-020SubscriberMale10.90000030.013015.011919.0
1026172017-01-0215SubscriberMale5.76666737.933219.015319.0
1026182017-01-0215SubscriberFemale18.55000037.9523.017627.0
1026192017-01-0215SubscriberMale7.16666737.931319.034015.0
1026202017-01-0215SubscriberMale2.88333337.98419.013327.0
.................................
33042017-01-3110SubscriberFemale6.96666737.924719.024719.0
33052017-01-3110SubscriberMale6.48333337.942515.042619.0
33062017-01-3110SubscriberFemale8.25000037.917519.04515.0
32992017-01-3110SubscriberMale16.26666737.920215.031723.0
02017-01-3123SubscriberMale3.31666735.123019.013115.0
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103806 rows × 10 columns

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" - ], - "text/plain": [ - " date hour usertype gender tripduration temperature \\\n", - "103805 2017-01-02 0 Subscriber Male 10.900000 30.0 \n", - "102617 2017-01-02 15 Subscriber Male 5.766667 37.9 \n", - "102618 2017-01-02 15 Subscriber Female 18.550000 37.9 \n", - "102619 2017-01-02 15 Subscriber Male 7.166667 37.9 \n", - "102620 2017-01-02 15 Subscriber Male 2.883333 37.9 \n", - "... ... ... ... ... ... ... \n", - "3304 2017-01-31 10 Subscriber Female 6.966667 37.9 \n", - "3305 2017-01-31 10 Subscriber Male 6.483333 37.9 \n", - "3306 2017-01-31 10 Subscriber Female 8.250000 37.9 \n", - "3299 2017-01-31 10 Subscriber Male 16.266667 37.9 \n", - "0 2017-01-31 23 Subscriber Male 3.316667 35.1 \n", - "\n", - " from_station_id dpcapacity_start to_station_id dpcapacity_end \n", - "103805 130 15.0 119 19.0 \n", - "102617 332 19.0 153 19.0 \n", - "102618 5 23.0 176 27.0 \n", - "102619 313 19.0 340 15.0 \n", - "102620 84 19.0 133 27.0 \n", - "... ... ... ... ... \n", - "3304 247 19.0 247 19.0 \n", - "3305 425 15.0 426 19.0 \n", - "3306 175 19.0 45 15.0 \n", - "3299 202 15.0 317 23.0 \n", - "0 230 19.0 131 15.0 \n", - "\n", - "[103806 rows x 10 columns]" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df" - ] - }, - { - "cell_type": "markdown", - "id": "1bbdae66", - "metadata": {}, - "source": [ - "### Defining entity column, time column and cutoff strategy" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "4916b1ac", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "b3b557696b4e42d09a750ae46984a0ed", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/1702 [00:00 predict the number of records in next 1h days\n", - "For each predict the number of records with greater than 13.05 in next 1h days\n", - "For each predict the number of records with greater than 8.033333333333333 in next 1h days\n", - "For each predict the number of records with greater than 5.116666666666666 in next 1h days\n", - "For each predict the number of records with greater than 37.9 in next 1h days\n", - "For each predict the number of records with greater than 34.0 in next 1h days\n", - "For each predict the number of records with greater than 26.1 in next 1h days\n", - "For each predict the number of records with greater than 27.0 in next 1h days\n", - "For each predict the number of records with greater than 19.0 in next 1h days\n", - "For each predict the number of records with greater than 15.0 in next 1h days\n", - "For each predict the number of records with greater than 27.0 in next 1h days\n", - "For each predict the number of records with greater than 19.0 in next 1h days\n", - "For each predict the number of records with greater than 15.0 in next 1h days\n", - "For each predict the number of records with equal to 17 in next 1h days\n", - "For each predict the number of records with equal to 8 in next 1h days\n", - "For each predict the number of records with equal to 16 in next 1h days\n", - "For each predict the number of records with equal to Male in next 1h days\n", - "For each predict the number of records with equal to Female in next 1h days\n", - "For each predict the number of records with not equal to 17 in next 1h days\n", - "For each predict the number of records with not equal to 8 in next 1h days\n", - "For each predict the number of records with not equal to 16 in next 1h days\n", - "For each predict the number of records with not equal to Male in next 1h days\n", - "For each predict the number of records with not equal to Female in next 1h days\n", - "For each predict the number of records with less than 5.15 in next 1h days\n", - "For each predict the number of records with less than 8.1 in next 1h days\n", - "For each predict the number of records with less than 12.75 in next 1h days\n", - "For each predict the number of records with less than 27.0 in next 1h days\n", - "For each predict the number of records with less than 35.1 in next 1h days\n", - "For each predict the number of records with less than 39.0 in next 1h days\n", - "For each predict the number of records with less than 16.0 in next 1h days\n", - "For each predict the number of records with less than 20.0 in next 1h days\n", - "For each predict the number of records with less than 28.0 in next 1h days\n", - "For each predict the number of records with less than 16.0 in next 1h days\n", - "For each predict the number of records with less than 20.0 in next 1h days\n", - "For each predict the number of records with less than 28.0 in next 1h days\n", - "For each predict the total in all related records in next 1h days\n", - "For each predict the total in all related records in next 1h days\n", - "For each predict the total in all related records in next 1h days\n", - "For each predict the total in all related records in next 1h days\n", - "For each predict the total in all related records with greater than 12.116666666666667 in next 1h days\n", - "For each predict the total in all related records with greater than 8.25 in next 1h days\n", - "For each predict the total in all related records with greater than 5.1 in next 1h days\n", - "For each predict the total in all related records with greater than 12.383333333333333 in next 1h days\n", - "For each predict the total in all related records with greater than 7.833333333333332 in next 1h days\n", - "For each predict the total in all related records with greater than 5.183333333333334 in next 1h days\n", - "For each predict the total in all related records with greater than 12.166666666666664 in next 1h days\n", - "For each predict the total in all related records with greater than 8.116666666666667 in next 1h days\n", - "For each predict the total in all related records with greater than 5.15 in next 1h days\n", - "For each predict the total in all related records with greater than 12.833333333333336 in next 1h days\n", - "For each predict the total in all related records with greater than 7.95 in next 1h days\n", - "For each predict the total in all related records with greater than 5.216666666666667 in next 1h days\n", - "For each predict the total in all related records with greater than 37.9 in next 1h days\n", - "For each predict the total in all related records with greater than 35.1 in next 1h days\n", - "For each predict the total in all related records with greater than 26.6 in next 1h days\n", - "For each predict the total in all related records with greater than 37.9 in next 1h days\n", - "For each predict the total in all related records with greater than 34.0 in next 1h days\n", - "For each predict the total in all related records with greater than 26.6 in next 1h days\n", - "For each predict the total in all related records with greater than 37.9 in next 1h days\n", - "For each predict the total in all related records with greater than 34.0 in next 1h days\n", - "For each predict the total in all related records with greater than 26.6 in next 1h days\n", - "For each predict the total in all related records with greater than 37.9 in next 1h days\n", - "For each predict the total in all related records with greater than 34.0 in next 1h days\n", - "For each predict the total in all related records with greater than 26.6 in next 1h days\n", - "For each predict the total in all related records with greater than 23.0 in next 1h days\n", - "For each predict the total in all related records with greater than 19.0 in next 1h days\n", - "For each predict the total in all related records with greater than 15.0 in next 1h days\n", - "For each predict the total in all related records with greater than 27.0 in next 1h days\n", - "For each predict the total in all related records with greater than 19.0 in next 1h days\n", - "For each predict the total in all related records with greater than 15.0 in next 1h days\n", - "For each predict the total in all related records with greater than 27.0 in next 1h days\n", - "For each predict the total in all related records with greater than 19.0 in next 1h days\n", - "For each predict the total in all related records with greater than 15.0 in next 1h days\n", - "For each predict the total in all related records with greater than 27.0 in next 1h days\n", - "For each predict the total in all related records with greater than 19.0 in next 1h days\n", - "For each predict the total in all related records with greater than 15.0 in next 1h days\n", - "For each predict the total in all related records with greater than 27.0 in next 1h days\n", - "For each predict the total in all related records with greater than 19.0 in next 1h days\n", - "For each predict the total in all related records with greater than 15.0 in next 1h days\n", - "For each predict the total in all related records with greater than 27.0 in next 1h days\n", - "For each predict the total in all related records with greater than 19.0 in next 1h days\n", - "For each predict the total in all related records with greater than 15.0 in next 1h days\n", - "For each predict the total in all related records with greater than 27.0 in next 1h days\n", - "For each predict the total in all related records with greater than 19.0 in next 1h days\n", - "For each predict the total in all related records with greater than 15.0 in next 1h days\n", - "For each predict the total in all related records with greater than 27.0 in next 1h days\n", - "For each predict the total in all related records with greater than 19.0 in next 1h days\n", - "For each predict the total in all related records with greater than 15.0 in next 1h days\n", - "For each predict the total in all related records with equal to 17 in next 1h days\n", - "For each predict the total in all related records with equal to 8 in next 1h days\n", - "For each predict the total in all related records with equal to 16 in next 1h days\n", - "For each predict the total in all related records with equal to 17 in next 1h days\n", - "For each predict the total in all related records with equal to 8 in next 1h days\n", - "For each predict the total in all related records with equal to 16 in next 1h days\n", - "For each predict the total in all related records with equal to 17 in next 1h days\n", - "For each predict the total in all related records with equal to 8 in next 1h days\n", - "For each predict the total in all related records with equal to 16 in next 1h days\n", - "For each predict the total in all related records with equal to 17 in next 1h days\n", - "For each predict the total in all related records with equal to 8 in next 1h days\n", - "For each predict the total in all related records with equal to 16 in next 1h days\n", - "For each predict the total in all related records with equal to Male in next 1h days\n", - "For each predict the total in all related records with equal to Female in next 1h days\n", - "For each predict the total in all related records with equal to Male in next 1h days\n", - "For each predict the total in all related records with equal to Female in next 1h days\n", - "For each predict the total in all related records with equal to Male in next 1h days\n", - "For each predict the total in all related records with equal to Female in next 1h days\n", - "For each predict the total in all related records with equal to Male in next 1h days\n", - "For each predict the total in all related records with equal to Female in next 1h days\n", - "For each predict the total in all related records with not equal to 17 in next 1h days\n", - "For each predict the total in all related records with not equal to 8 in next 1h days\n", - "For each predict the total in all related records with not equal to 16 in next 1h days\n", - "For each predict the total in all related records with not equal to 17 in next 1h days\n", - "For each predict the total in all related records with not equal to 8 in next 1h days\n", - "For each predict the total in all related records with not equal to 16 in next 1h days\n", - "For each predict the total in all related records with not equal to 17 in next 1h days\n", - "For each predict the total in all related records with not equal to 8 in next 1h days\n", - "For each predict the total in all related records with not equal to 16 in next 1h days\n", - "For each predict the total in all related records with not equal to 17 in next 1h days\n", - "For each predict the total in all related records with not equal to 8 in next 1h days\n", - "For each predict the total in all related records with not equal to 16 in next 1h days\n", - "For each predict the total in all related records with not equal to Male in next 1h days\n", - "For each predict the total in all related records with not equal to Female in next 1h days\n", - "For each predict the total in all related records with not equal to Male in next 1h days\n", - "For each predict the total in all related records with not equal to Female in next 1h days\n", - "For each predict the total in all related records with not equal to Male in next 1h days\n", - "For each predict the total in all related records with not equal to Female in next 1h days\n", - "For each predict the total in all related records with not equal to Male in next 1h days\n", - "For each predict the total in all related records with not equal to Female in next 1h days\n", - "For each predict the total in all related records with less than 5.216666666666667 in next 1h days\n", - "For each predict the total in all related records with less than 7.966666666666668 in next 1h days\n", - "For each predict the total in all related records with less than 12.566666666666665 in next 1h days\n", - "For each predict the total in all related records with less than 5.083333333333333 in next 1h days\n", - "For each predict the total in all related records with less than 7.85 in next 1h days\n", - "For each predict the total in all related records with less than 12.666666666666664 in next 1h days\n", - "For each predict the total in all related records with less than 5.2 in next 1h days\n", - "For each predict the total in all related records with less than 8.083333333333334 in next 1h days\n", - "For each predict the total in all related records with less than 12.516666666666667 in next 1h days\n", - "For each predict the total in all related records with less than 5.25 in next 1h days\n", - "For each predict the total in all related records with less than 7.85 in next 1h days\n", - "For each predict the total in all related records with less than 12.716666666666669 in next 1h days\n", - "For each predict the total in all related records with less than 26.6 in next 1h days\n", - "For each predict the total in all related records with less than 35.6 in next 1h days\n", - "For each predict the total in all related records with less than 37.9 in next 1h days\n", - "For each predict the total in all related records with less than 26.6 in next 1h days\n", - "For each predict the total in all related records with less than 35.1 in next 1h days\n", - "For each predict the total in all related records with less than 39.0 in next 1h days\n", - "For each predict the total in all related records with less than 27.0 in next 1h days\n", - "For each predict the total in all related records with less than 35.1 in next 1h days\n", - "For each predict the total in all related records with less than 39.0 in next 1h days\n", - "For each predict the total in all related records with less than 27.0 in next 1h days\n", - "For each predict the total in all related records with less than 35.1 in next 1h days\n", - "For each predict the total in all related records with less than 39.0 in next 1h days\n", - "For each predict the total in all related records with less than 16.0 in next 1h days\n", - "For each predict the total in all related records with less than 20.0 in next 1h days\n", - "For each predict the total in all related records with less than 28.0 in next 1h days\n", - "For each predict the total in all related records with less than 16.0 in next 1h days\n", - "For each predict the total in all related records with less than 20.0 in next 1h days\n", - "For each predict the total in all related records with less than 28.0 in next 1h days\n", - "For each predict the total in all related records with less than 16.0 in next 1h days\n", - "For each predict the total in all related records with less than 20.0 in next 1h days\n", - "For each predict the total in all related records with less than 28.0 in next 1h days\n", - "For each predict the total in all related records with less than 16.0 in next 1h days\n", - "For each predict the total in all related records with less than 20.0 in next 1h days\n", - "For each predict the total in all related records with less than 28.0 in next 1h days\n", - "For each predict the total in all related records with less than 16.0 in next 1h days\n", - "For each predict the total in all related records with less than 20.0 in next 1h days\n", - "For each predict the total in all related records with less than 28.0 in next 1h days\n", - "For each predict the total in all related records with less than 16.0 in next 1h days\n", - "For each predict the total in all related records with less than 20.0 in next 1h days\n", - "For each predict the total in all related records with less than 28.0 in next 1h days\n", - "For each predict the total in all related records with less than 16.0 in next 1h days\n", - "For each predict the total in all related records with less than 20.0 in next 1h days\n", - "For each predict the total in all related records with less than 28.0 in next 1h days\n", - "For each predict the total in all related records with less than 16.0 in next 1h days\n", - "For each predict the total in all related records with less than 20.0 in next 1h days\n", - "For each predict the total in all related records with less than 28.0 in next 1h days\n", - "For each predict the average in all related records in next 1h days\n", - "For each predict the average in all related records in next 1h days\n", - "For each predict the average in all related records in next 1h days\n", - "For each predict the average in all related records in next 1h days\n", - "For each predict the average in all related records with greater than 12.433333333333335 in next 1h days\n", - "For each predict the average in all related records with greater than 7.783333333333332 in next 1h days\n", - "For each predict the average in all related records with greater than 5.15 in next 1h days\n", - "For each predict the average in all related records with greater than 12.316666666666665 in next 1h days\n", - "For each predict the average in all related records with greater than 7.7666666666666675 in next 1h days\n", - "For each predict the average in all related records with greater than 5.0 in next 1h days\n", - "For each predict the average in all related records with greater than 12.5 in next 1h days\n", - "For each predict the average in all related records with greater than 7.916666666666668 in next 1h days\n", - "For each predict the average in all related records with greater than 5.15 in next 1h days\n", - "For each predict the average in all related records with greater than 12.916666666666664 in next 1h days\n", - "For each predict the average in all related records with greater than 7.833333333333332 in next 1h days\n", - "For each predict the average in all related records with greater than 5.166666666666667 in next 1h days\n", - "For each predict the average in all related records with greater than 37.9 in next 1h days\n", - "For each predict the average in all related records with greater than 34.0 in next 1h days\n", - "For each predict the average in all related records with greater than 26.6 in next 1h days\n", - "For each predict the average in all related records with greater than 37.9 in next 1h days\n", - "For each predict the average in all related records with greater than 34.0 in next 1h days\n", - "For each predict the average in all related records with greater than 26.6 in next 1h days\n", - "For each predict the average in all related records with greater than 37.9 in next 1h days\n", - "For each predict the average in all related records with greater than 35.1 in next 1h days\n", - "For each predict the average in all related records with greater than 26.6 in next 1h days\n", - "For each predict the average in all related records with greater than 37.9 in next 1h days\n", - "For each predict the average in all related records with greater than 34.0 in next 1h days\n", - "For each predict the average in all related records with greater than 26.1 in next 1h days\n", - "For each predict the average in all related records with greater than 27.0 in next 1h days\n", - "For each predict the average in all related records with greater than 19.0 in next 1h days\n", - "For each predict the average in all related records with greater than 15.0 in next 1h days\n", - "For each predict the average in all related records with greater than 27.0 in next 1h days\n", - "For each predict the average in all related records with greater than 19.0 in next 1h days\n", - "For each predict the average in all related records with greater than 15.0 in next 1h days\n", - "For each predict the average in all related records with greater than 27.0 in next 1h days\n", - "For each predict the average in all related records with greater than 19.0 in next 1h days\n", - "For each predict the average in all related records with greater than 15.0 in next 1h days\n", - "For each predict the average in all related records with greater than 27.0 in next 1h days\n", - "For each predict the average in all related records with greater than 19.0 in next 1h days\n", - "For each predict the average in all related records with greater than 15.0 in next 1h days\n", - "For each predict the average in all related records with greater than 27.0 in next 1h days\n", - "For each predict the average in all related records with greater than 19.0 in next 1h days\n", - "For each predict the average in all related records with greater than 15.0 in next 1h days\n", - "For each predict the average in all related records with greater than 27.0 in next 1h days\n", - "For each predict the average in all related records with greater than 19.0 in next 1h days\n", - "For each predict the average in all related records with greater than 15.0 in next 1h days\n", - "For each predict the average in all related records with greater than 27.0 in next 1h days\n", - "For each predict the average in all related records with greater than 19.0 in next 1h days\n", - "For each predict the average in all related records with greater than 15.0 in next 1h days\n", - "For each predict the average in all related records with greater than 27.0 in next 1h days\n", - "For each predict the average in all related records with greater than 19.0 in next 1h days\n", - "For each predict the average in all related records with greater than 15.0 in next 1h days\n", - "For each predict the average in all related records with equal to 17 in next 1h days\n", - "For each predict the average in all related records with equal to 8 in next 1h days\n", - "For each predict the average in all related records with equal to 16 in next 1h days\n", - "For each predict the average in all related records with equal to 17 in next 1h days\n", - "For each predict the average in all related records with equal to 8 in next 1h days\n", - "For each predict the average in all related records with equal to 16 in next 1h days\n", - "For each predict the average in all related records with equal to 17 in next 1h days\n", - "For each predict the average in all related records with equal to 8 in next 1h days\n", - "For each predict the average in all related records with equal to 16 in next 1h days\n", - "For each predict the average in all related records with equal to 17 in next 1h days\n", - "For each predict the average in all related records with equal to 8 in next 1h days\n", - "For each predict the average in all related records with equal to 16 in next 1h days\n", - "For each predict the average in all related records with equal to Male in next 1h days\n", - "For each predict the average in all related records with equal to Female in next 1h days\n", - "For each predict the average in all related records with equal to Male in next 1h days\n", - "For each predict the average in all related records with equal to Female in next 1h days\n", - "For each predict the average in all related records with equal to Male in next 1h days\n", - "For each predict the average in all related records with equal to Female in next 1h days\n", - "For each predict the average in all related records with equal to Male in next 1h days\n", - "For each predict the average in all related records with equal to Female in next 1h days\n", - "For each predict the average in all related records with not equal to 17 in next 1h days\n", - "For each predict the average in all related records with not equal to 8 in next 1h days\n", - "For each predict the average in all related records with not equal to 16 in next 1h days\n", - "For each predict the average in all related records with not equal to 17 in next 1h days\n", - "For each predict the average in all related records with not equal to 8 in next 1h days\n", - "For each predict the average in all related records with not equal to 16 in next 1h days\n", - "For each predict the average in all related records with not equal to 17 in next 1h days\n", - "For each predict the average in all related records with not equal to 8 in next 1h days\n", - "For each predict the average in all related records with not equal to 16 in next 1h days\n", - "For each predict the average in all related records with not equal to 17 in next 1h days\n", - "For each predict the average in all related records with not equal to 8 in next 1h days\n", - "For each predict the average in all related records with not equal to 16 in next 1h days\n", - "For each predict the average in all related records with not equal to Male in next 1h days\n", - "For each predict the average in all related records with not equal to Female in next 1h days\n", - "For each predict the average in all related records with not equal to Male in next 1h days\n", - "For each predict the average in all related records with not equal to Female in next 1h days\n", - "For each predict the average in all related records with not equal to Male in next 1h days\n", - "For each predict the average in all related records with not equal to Female in next 1h days\n", - "For each predict the average in all related records with not equal to Male in next 1h days\n", - "For each predict the average in all related records with not equal to Female in next 1h days\n", - "For each predict the average in all related records with less than 5.2 in next 1h days\n", - "For each predict the average in all related records with less than 7.8 in next 1h days\n", - "For each predict the average in all related records with less than 12.566666666666665 in next 1h days\n", - "For each predict the average in all related records with less than 5.266666666666667 in next 1h days\n", - "For each predict the average in all related records with less than 7.95 in next 1h days\n", - "For each predict the average in all related records with less than 12.033333333333331 in next 1h days\n", - "For each predict the average in all related records with less than 5.05 in next 1h days\n", - "For each predict the average in all related records with less than 8.316666666666666 in next 1h days\n", - "For each predict the average in all related records with less than 12.566666666666665 in next 1h days\n", - "For each predict the average in all related records with less than 5.066666666666666 in next 1h days\n", - "For each predict the average in all related records with less than 8.033333333333333 in next 1h days\n", - "For each predict the average in all related records with less than 12.383333333333333 in next 1h days\n", - "For each predict the average in all related records with less than 27.0 in next 1h days\n", - "For each predict the average in all related records with less than 35.1 in next 1h days\n", - "For each predict the average in all related records with less than 39.0 in next 1h days\n", - "For each predict the average in all related records with less than 26.6 in next 1h days\n", - "For each predict the average in all related records with less than 35.1 in next 1h days\n", - "For each predict the average in all related records with less than 39.0 in next 1h days\n", - "For each predict the average in all related records with less than 27.0 in next 1h days\n", - "For each predict the average in all related records with less than 35.1 in next 1h days\n", - "For each predict the average in all related records with less than 39.0 in next 1h days\n", - "For each predict the average in all related records with less than 27.0 in next 1h days\n", - "For each predict the average in all related records with less than 35.1 in next 1h days\n", - "For each predict the average in all related records with less than 39.0 in next 1h days\n", - "For each predict the average in all related records with less than 16.0 in next 1h days\n", - "For each predict the average in all related records with less than 20.0 in next 1h days\n", - "For each predict the average in all related records with less than 28.0 in next 1h days\n", - "For each predict the average in all related records with less than 16.0 in next 1h days\n", - "For each predict the average in all related records with less than 20.0 in next 1h days\n", - "For each predict the average in all related records with less than 28.0 in next 1h days\n", - "For each predict the average in all related records with less than 16.0 in next 1h days\n", - "For each predict the average in all related records with less than 20.0 in next 1h days\n", - "For each predict the average in all related records with less than 28.0 in next 1h days\n", - "For each predict the average in all related records with less than 16.0 in next 1h days\n", - "For each predict the average in all related records with less than 20.0 in next 1h days\n", - "For each predict the average in all related records with less than 28.0 in next 1h days\n", - "For each predict the average in all related records with less than 16.0 in next 1h days\n", - "For each predict the average in all related records with less than 20.0 in next 1h days\n", - "For each predict the average in all related records with less than 28.0 in next 1h days\n", - "For each predict the average in all related records with less than 16.0 in next 1h days\n", - "For each predict the average in all related records with less than 20.0 in next 1h days\n", - "For each predict the average in all related records with less than 28.0 in next 1h days\n", - "For each predict the average in all related records with less than 16.0 in next 1h days\n", - "For each predict the average in all related records with less than 20.0 in next 1h days\n", - "For each predict the average in all related records with less than 28.0 in next 1h days\n", - "For each predict the average in all related records with less than 16.0 in next 1h days\n", - "For each predict the average in all related records with less than 20.0 in next 1h days\n", - "For each predict the average in all related records with less than 28.0 in next 1h days\n", - "For each predict the maximum in all related records in next 1h days\n", - "For each predict the maximum in all related records in next 1h days\n", - "For each predict the maximum in all related records in next 1h days\n", - "For each predict the maximum in all related records in next 1h days\n", - "For each predict the maximum in all related records with greater than 12.733333333333333 in next 1h days\n", - "For each predict the maximum in all related records with greater than 8.116666666666667 in next 1h days\n", - "For each predict the maximum in all related records with greater than 5.2 in next 1h days\n", - "For each predict the maximum in all related records with greater than 12.416666666666664 in next 1h days\n", - "For each predict the maximum in all related records with greater than 7.95 in next 1h days\n", - "For each predict the maximum in all related records with greater than 5.116666666666666 in next 1h days\n", - "For each predict the maximum in all related records with greater than 12.566666666666665 in next 1h days\n", - "For each predict the maximum in all related records with greater than 8.183333333333334 in next 1h days\n", - "For each predict the maximum in all related records with greater than 5.016666666666667 in next 1h days\n", - "For each predict the maximum in all related records with greater than 12.833333333333336 in next 1h days\n", - "For each predict the maximum in all related records with greater than 8.1 in next 1h days\n", - "For each predict the maximum in all related records with greater than 5.266666666666667 in next 1h days\n", - "For each predict the maximum in all related records with greater than 37.9 in next 1h days\n", - "For each predict the maximum in all related records with greater than 34.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 26.1 in next 1h days\n", - "For each predict the maximum in all related records with greater than 37.9 in next 1h days\n", - "For each predict the maximum in all related records with greater than 34.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 26.6 in next 1h days\n", - "For each predict the maximum in all related records with greater than 37.9 in next 1h days\n", - "For each predict the maximum in all related records with greater than 34.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 26.6 in next 1h days\n", - "For each predict the maximum in all related records with greater than 37.9 in next 1h days\n", - "For each predict the maximum in all related records with greater than 34.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 26.1 in next 1h days\n", - "For each predict the maximum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the maximum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the maximum in all related records with equal to 17 in next 1h days\n", - "For each predict the maximum in all related records with equal to 8 in next 1h days\n", - "For each predict the maximum in all related records with equal to 16 in next 1h days\n", - "For each predict the maximum in all related records with equal to 17 in next 1h days\n", - "For each predict the maximum in all related records with equal to 8 in next 1h days\n", - "For each predict the maximum in all related records with equal to 16 in next 1h days\n", - "For each predict the maximum in all related records with equal to 17 in next 1h days\n", - "For each predict the maximum in all related records with equal to 8 in next 1h days\n", - "For each predict the maximum in all related records with equal to 16 in next 1h days\n", - "For each predict the maximum in all related records with equal to 17 in next 1h days\n", - "For each predict the maximum in all related records with equal to 8 in next 1h days\n", - "For each predict the maximum in all related records with equal to 16 in next 1h days\n", - "For each predict the maximum in all related records with equal to Male in next 1h days\n", - "For each predict the maximum in all related records with equal to Female in next 1h days\n", - "For each predict the maximum in all related records with equal to Male in next 1h days\n", - "For each predict the maximum in all related records with equal to Female in next 1h days\n", - "For each predict the maximum in all related records with equal to Male in next 1h days\n", - "For each predict the maximum in all related records with equal to Female in next 1h days\n", - "For each predict the maximum in all related records with equal to Male in next 1h days\n", - "For each predict the maximum in all related records with equal to Female in next 1h days\n", - "For each predict the maximum in all related records with not equal to 17 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 8 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 16 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 17 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 8 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 16 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 17 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 8 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 16 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 17 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 8 in next 1h days\n", - "For each predict the maximum in all related records with not equal to 16 in next 1h days\n", - "For each predict the maximum in all related records with not equal to Male in next 1h days\n", - "For each predict the maximum in all related records with not equal to Female in next 1h days\n", - "For each predict the maximum in all related records with not equal to Male in next 1h days\n", - "For each predict the maximum in all related records with not equal to Female in next 1h days\n", - "For each predict the maximum in all related records with not equal to Male in next 1h days\n", - "For each predict the maximum in all related records with not equal to Female in next 1h days\n", - "For each predict the maximum in all related records with not equal to Male in next 1h days\n", - "For each predict the maximum in all related records with not equal to Female in next 1h days\n", - "For each predict the maximum in all related records with less than 5.2 in next 1h days\n", - "For each predict the maximum in all related records with less than 7.733333333333332 in next 1h days\n", - "For each predict the maximum in all related records with less than 12.45 in next 1h days\n", - "For each predict the maximum in all related records with less than 5.033333333333333 in next 1h days\n", - "For each predict the maximum in all related records with less than 8.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 12.15 in next 1h days\n", - "For each predict the maximum in all related records with less than 5.033333333333333 in next 1h days\n", - "For each predict the maximum in all related records with less than 7.9 in next 1h days\n", - "For each predict the maximum in all related records with less than 12.416666666666664 in next 1h days\n", - "For each predict the maximum in all related records with less than 5.133333333333334 in next 1h days\n", - "For each predict the maximum in all related records with less than 7.9 in next 1h days\n", - "For each predict the maximum in all related records with less than 12.466666666666669 in next 1h days\n", - "For each predict the maximum in all related records with less than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 35.1 in next 1h days\n", - "For each predict the maximum in all related records with less than 39.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 26.6 in next 1h days\n", - "For each predict the maximum in all related records with less than 35.1 in next 1h days\n", - "For each predict the maximum in all related records with less than 39.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 27.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 35.1 in next 1h days\n", - "For each predict the maximum in all related records with less than 39.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 26.6 in next 1h days\n", - "For each predict the maximum in all related records with less than 35.1 in next 1h days\n", - "For each predict the maximum in all related records with less than 39.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 16.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 20.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 28.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 16.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 20.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 28.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 16.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 20.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 28.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 16.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 20.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 28.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 16.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 20.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 28.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 16.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 20.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 28.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 16.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 20.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 28.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 16.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 20.0 in next 1h days\n", - "For each predict the maximum in all related records with less than 28.0 in next 1h days\n", - "For each predict the minimum in all related records in next 1h days\n", - "For each predict the minimum in all related records in next 1h days\n", - "For each predict the minimum in all related records in next 1h days\n", - "For each predict the minimum in all related records in next 1h days\n", - "For each predict the minimum in all related records with greater than 12.8 in next 1h days\n", - "For each predict the minimum in all related records with greater than 8.016666666666667 in next 1h days\n", - "For each predict the minimum in all related records with greater than 5.25 in next 1h days\n", - "For each predict the minimum in all related records with greater than 12.15 in next 1h days\n", - "For each predict the minimum in all related records with greater than 8.183333333333334 in next 1h days\n", - "For each predict the minimum in all related records with greater than 5.1 in next 1h days\n", - "For each predict the minimum in all related records with greater than 12.816666666666665 in next 1h days\n", - "For each predict the minimum in all related records with greater than 7.95 in next 1h days\n", - "For each predict the minimum in all related records with greater than 5.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 12.983333333333333 in next 1h days\n", - "For each predict the minimum in all related records with greater than 8.033333333333333 in next 1h days\n", - "For each predict the minimum in all related records with greater than 5.133333333333334 in next 1h days\n", - "For each predict the minimum in all related records with greater than 37.9 in next 1h days\n", - "For each predict the minimum in all related records with greater than 34.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 26.6 in next 1h days\n", - "For each predict the minimum in all related records with greater than 37.9 in next 1h days\n", - "For each predict the minimum in all related records with greater than 34.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 26.1 in next 1h days\n", - "For each predict the minimum in all related records with greater than 37.9 in next 1h days\n", - "For each predict the minimum in all related records with greater than 34.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 25.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 37.9 in next 1h days\n", - "For each predict the minimum in all related records with greater than 34.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 26.1 in next 1h days\n", - "For each predict the minimum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 19.0 in next 1h days\n", - "For each predict the minimum in all related records with greater than 15.0 in next 1h days\n", - "For each predict the minimum in all related records with equal to 17 in next 1h days\n", - "For each predict the minimum in all related records with equal to 8 in next 1h days\n", - "For each predict the minimum in all related records with equal to 16 in next 1h days\n", - "For each predict the minimum in all related records with equal to 17 in next 1h days\n", - "For each predict the minimum in all related records with equal to 8 in next 1h days\n", - "For each predict the minimum in all related records with equal to 16 in next 1h days\n", - "For each predict the minimum in all related records with equal to 17 in next 1h days\n", - "For each predict the minimum in all related records with equal to 8 in next 1h days\n", - "For each predict the minimum in all related records with equal to 16 in next 1h days\n", - "For each predict the minimum in all related records with equal to 17 in next 1h days\n", - "For each predict the minimum in all related records with equal to 8 in next 1h days\n", - "For each predict the minimum in all related records with equal to 16 in next 1h days\n", - "For each predict the minimum in all related records with equal to Male in next 1h days\n", - "For each predict the minimum in all related records with equal to Female in next 1h days\n", - "For each predict the minimum in all related records with equal to Male in next 1h days\n", - "For each predict the minimum in all related records with equal to Female in next 1h days\n", - "For each predict the minimum in all related records with equal to Male in next 1h days\n", - "For each predict the minimum in all related records with equal to Female in next 1h days\n", - "For each predict the minimum in all related records with equal to Male in next 1h days\n", - "For each predict the minimum in all related records with equal to Female in next 1h days\n", - "For each predict the minimum in all related records with not equal to 17 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 8 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 16 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 17 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 8 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 16 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 17 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 8 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 16 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 17 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 8 in next 1h days\n", - "For each predict the minimum in all related records with not equal to 16 in next 1h days\n", - "For each predict the minimum in all related records with not equal to Male in next 1h days\n", - "For each predict the minimum in all related records with not equal to Female in next 1h days\n", - "For each predict the minimum in all related records with not equal to Male in next 1h days\n", - "For each predict the minimum in all related records with not equal to Female in next 1h days\n", - "For each predict the minimum in all related records with not equal to Male in next 1h days\n", - "For each predict the minimum in all related records with not equal to Female in next 1h days\n", - "For each predict the minimum in all related records with not equal to Male in next 1h days\n", - "For each predict the minimum in all related records with not equal to Female in next 1h days\n", - "For each predict the minimum in all related records with less than 5.1 in next 1h days\n", - "For each predict the minimum in all related records with less than 7.95 in next 1h days\n", - "For each predict the minimum in all related records with less than 12.7 in next 1h days\n", - "For each predict the minimum in all related records with less than 5.1 in next 1h days\n", - "For each predict the minimum in all related records with less than 7.9 in next 1h days\n", - "For each predict the minimum in all related records with less than 12.316666666666665 in next 1h days\n", - "For each predict the minimum in all related records with less than 5.2 in next 1h days\n", - "For each predict the minimum in all related records with less than 8.083333333333334 in next 1h days\n", - "For each predict the minimum in all related records with less than 12.45 in next 1h days\n", - "For each predict the minimum in all related records with less than 5.066666666666666 in next 1h days\n", - "For each predict the minimum in all related records with less than 8.016666666666667 in next 1h days\n", - "For each predict the minimum in all related records with less than 12.85 in next 1h days\n", - "For each predict the minimum in all related records with less than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 35.1 in next 1h days\n", - "For each predict the minimum in all related records with less than 39.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 26.6 in next 1h days\n", - "For each predict the minimum in all related records with less than 35.1 in next 1h days\n", - "For each predict the minimum in all related records with less than 39.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 27.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 35.1 in next 1h days\n", - "For each predict the minimum in all related records with less than 39.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 26.6 in next 1h days\n", - "For each predict the minimum in all related records with less than 35.1 in next 1h days\n", - "For each predict the minimum in all related records with less than 39.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 16.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 20.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 28.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 16.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 20.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 28.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 16.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 20.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 28.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 16.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 20.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 28.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 16.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 20.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 28.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 16.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 20.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 28.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 16.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 20.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 28.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 16.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 20.0 in next 1h days\n", - "For each predict the minimum in all related records with less than 28.0 in next 1h days\n", - "For each predict the majority in all related records in next 1h days\n", - "For each predict the majority in all related records in next 1h days\n", - "For each predict the majority in all related records in next 1h days\n", - "For each predict the majority in all related records in next 1h days\n", - "For each predict the majority in all related records with greater than 12.816666666666665 in next 1h days\n", - "For each predict the majority in all related records with greater than 8.3 in next 1h days\n", - "For each predict the majority in all related records with greater than 5.15 in next 1h days\n", - "For each predict the majority in all related records with greater than 12.166666666666664 in next 1h days\n", - "For each predict the majority in all related records with greater than 7.916666666666668 in next 1h days\n", - "For each predict the majority in all related records with greater than 5.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 12.35 in next 1h days\n", - "For each predict the majority in all related records with greater than 7.933333333333334 in next 1h days\n", - "For each predict the majority in all related records with greater than 5.066666666666666 in next 1h days\n", - "For each predict the majority in all related records with greater than 12.633333333333333 in next 1h days\n", - "For each predict the majority in all related records with greater than 7.9 in next 1h days\n", - "For each predict the majority in all related records with greater than 5.1 in next 1h days\n", - "For each predict the majority in all related records with greater than 37.9 in next 1h days\n", - "For each predict the majority in all related records with greater than 34.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 26.6 in next 1h days\n", - "For each predict the majority in all related records with greater than 37.9 in next 1h days\n", - "For each predict the majority in all related records with greater than 34.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 26.6 in next 1h days\n", - "For each predict the majority in all related records with greater than 37.9 in next 1h days\n", - "For each predict the majority in all related records with greater than 35.1 in next 1h days\n", - "For each predict the majority in all related records with greater than 26.6 in next 1h days\n", - "For each predict the majority in all related records with greater than 37.9 in next 1h days\n", - "For each predict the majority in all related records with greater than 34.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 26.1 in next 1h days\n", - "For each predict the majority in all related records with greater than 27.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 19.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 15.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 27.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 19.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 15.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 27.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 19.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 15.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 27.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 19.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 15.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 27.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 19.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 15.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 27.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 19.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 15.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 27.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 19.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 15.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 27.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 19.0 in next 1h days\n", - "For each predict the majority in all related records with greater than 15.0 in next 1h days\n", - "For each predict the majority in all related records with equal to 17 in next 1h days\n", - "For each predict the majority in all related records with equal to 8 in next 1h days\n", - "For each predict the majority in all related records with equal to 16 in next 1h days\n", - "For each predict the majority in all related records with equal to 17 in next 1h days\n", - "For each predict the majority in all related records with equal to 8 in next 1h days\n", - "For each predict the majority in all related records with equal to 16 in next 1h days\n", - "For each predict the majority in all related records with equal to 17 in next 1h days\n", - "For each predict the majority in all related records with equal to 8 in next 1h days\n", - "For each predict the majority in all related records with equal to 16 in next 1h days\n", - "For each predict the majority in all related records with equal to 17 in next 1h days\n", - "For each predict the majority in all related records with equal to 8 in next 1h days\n", - "For each predict the majority in all related records with equal to 16 in next 1h days\n", - "For each predict the majority in all related records with equal to Male in next 1h days\n", - "For each predict the majority in all related records with equal to Female in next 1h days\n", - "For each predict the majority in all related records with equal to Male in next 1h days\n", - "For each predict the majority in all related records with equal to Female in next 1h days\n", - "For each predict the majority in all related records with equal to Male in next 1h days\n", - "For each predict the majority in all related records with equal to Female in next 1h days\n", - "For each predict the majority in all related records with equal to Male in next 1h days\n", - "For each predict the majority in all related records with equal to Female in next 1h days\n", - "For each predict the majority in all related records with not equal to 17 in next 1h days\n", - "For each predict the majority in all related records with not equal to 8 in next 1h days\n", - "For each predict the majority in all related records with not equal to 16 in next 1h days\n", - "For each predict the majority in all related records with not equal to 17 in next 1h days\n", - "For each predict the majority in all related records with not equal to 8 in next 1h days\n", - "For each predict the majority in all related records with not equal to 16 in next 1h days\n", - "For each predict the majority in all related records with not equal to 17 in next 1h days\n", - "For each predict the majority in all related records with not equal to 8 in next 1h days\n", - "For each predict the majority in all related records with not equal to 16 in next 1h days\n", - "For each predict the majority in all related records with not equal to 17 in next 1h days\n", - "For each predict the majority in all related records with not equal to 8 in next 1h days\n", - "For each predict the majority in all related records with not equal to 16 in next 1h days\n", - "For each predict the majority in all related records with not equal to Male in next 1h days\n", - "For each predict the majority in all related records with not equal to Female in next 1h days\n", - "For each predict the majority in all related records with not equal to Male in next 1h days\n", - "For each predict the majority in all related records with not equal to Female in next 1h days\n", - "For each predict the majority in all related records with not equal to Male in next 1h days\n", - "For each predict the majority in all related records with not equal to Female in next 1h days\n", - "For each predict the majority in all related records with not equal to Male in next 1h days\n", - "For each predict the majority in all related records with not equal to Female in next 1h days\n", - "For each predict the majority in all related records with less than 5.05 in next 1h days\n", - "For each predict the majority in all related records with less than 7.916666666666668 in next 1h days\n", - "For each predict the majority in all related records with less than 12.466666666666669 in next 1h days\n", - "For each predict the majority in all related records with less than 5.116666666666666 in next 1h days\n", - "For each predict the majority in all related records with less than 8.333333333333334 in next 1h days\n", - "For each predict the majority in all related records with less than 12.216666666666669 in next 1h days\n", - "For each predict the majority in all related records with less than 5.133333333333334 in next 1h days\n", - "For each predict the majority in all related records with less than 8.15 in next 1h days\n", - "For each predict the majority in all related records with less than 12.266666666666667 in next 1h days\n", - "For each predict the majority in all related records with less than 5.15 in next 1h days\n", - "For each predict the majority in all related records with less than 8.233333333333333 in next 1h days\n", - "For each predict the majority in all related records with less than 12.083333333333336 in next 1h days\n", - "For each predict the majority in all related records with less than 27.0 in next 1h days\n", - "For each predict the majority in all related records with less than 35.1 in next 1h days\n", - "For each predict the majority in all related records with less than 39.0 in next 1h days\n", - "For each predict the majority in all related records with less than 26.6 in next 1h days\n", - "For each predict the majority in all related records with less than 35.1 in next 1h days\n", - "For each predict the majority in all related records with less than 39.0 in next 1h days\n", - "For each predict the majority in all related records with less than 27.0 in next 1h days\n", - "For each predict the majority in all related records with less than 35.1 in next 1h days\n", - "For each predict the majority in all related records with less than 39.0 in next 1h days\n", - "For each predict the majority in all related records with less than 26.6 in next 1h days\n", - "For each predict the majority in all related records with less than 35.1 in next 1h days\n", - "For each predict the majority in all related records with less than 39.0 in next 1h days\n", - "For each predict the majority in all related records with less than 16.0 in next 1h days\n", - "For each predict the majority in all related records with less than 20.0 in next 1h days\n", - "For each predict the majority in all related records with less than 28.0 in next 1h days\n", - "For each predict the majority in all related records with less than 16.0 in next 1h days\n", - "For each predict the majority in all related records with less than 20.0 in next 1h days\n", - "For each predict the majority in all related records with less than 28.0 in next 1h days\n", - "For each predict the majority in all related records with less than 16.0 in next 1h days\n", - "For each predict the majority in all related records with less than 20.0 in next 1h days\n", - "For each predict the majority in all related records with less than 28.0 in next 1h days\n", - "For each predict the majority in all related records with less than 16.0 in next 1h days\n", - "For each predict the majority in all related records with less than 20.0 in next 1h days\n", - "For each predict the majority in all related records with less than 28.0 in next 1h days\n", - "For each predict the majority in all related records with less than 16.0 in next 1h days\n", - "For each predict the majority in all related records with less than 20.0 in next 1h days\n", - "For each predict the majority in all related records with less than 28.0 in next 1h days\n", - "For each predict the majority in all related records with less than 16.0 in next 1h days\n", - "For each predict the majority in all related records with less than 20.0 in next 1h days\n", - "For each predict the majority in all related records with less than 28.0 in next 1h days\n", - "For each predict the majority in all related records with less than 16.0 in next 1h days\n", - "For each predict the majority in all related records with less than 20.0 in next 1h days\n", - "For each predict the majority in all related records with less than 28.0 in next 1h days\n", - "For each predict the majority in all related records with less than 16.0 in next 1h days\n", - "For each predict the majority in all related records with less than 20.0 in next 1h days\n", - "For each predict the majority in all related records with less than 28.0 in next 1h days\n" - ] - } - ], - "source": [ - "for p in problems:\n", - " print(str(p))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8a2ba67b", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "for p in problems:\n", - " try:\n", - " x = p.execute(df, -1)\n", - " problem_label_dict[str(p)] = x\n", - " except:\n", - " pass" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3258af1f", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.2" - }, - "vscode": { - "interpreter": { - "hash": "8207ecde8cf2fda520169a8f8360958470b9168fa3b5c7074fdec936472ea246" - } - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Examples/covid_example.ipynb b/Examples/covid_example.ipynb deleted file mode 100644 index 095ec8bd..00000000 --- a/Examples/covid_example.ipynb +++ /dev/null @@ -1,322 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 2, - "id": "7efd117b", - "metadata": {}, - "outputs": [], - "source": [ - "import warnings\n", - "\n", - "# warnings.filterwarnings(\"ignore\")\n", - "warnings.filterwarnings(\"ignore\", category=DeprecationWarning)\n", - "\n", - "import copy\n", - "import json\n", - "import pandas as pd\n", - "import os\n", - "import sys\n", - "import featuretools as ft\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib\n", - "\n", - "%matplotlib inline\n", - "\n", - "sys.path.append(\"../../\")\n", - "from Trane import trane as trane\n", - "from datetime import datetime, timedelta\n", - "from sentence_transformers import SentenceTransformer\n", - "from atm import ATM" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "579ae6be", - "metadata": {}, - "outputs": [], - "source": [ - "case_folder = \"covid_pts\"\n", - "os.makedirs(case_folder, exist_ok=True)\n", - "os.chdir(case_folder)" - ] - }, - { - "cell_type": "markdown", - "id": "8d67ebc9", - "metadata": {}, - "source": [ - "### Upload of the dataset and metadata" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "f1b249d7", - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_csv(\"./covid19.csv\")\n", - "df[\"Date\"] = df[\"Date\"].apply(lambda x: datetime.strptime(x, \"%m/%d/%y\"))\n", - "df = df.sort_values(by=[\"Date\"])\n", - "df = df.fillna(0)\n", - "meta_covid = trane.TableMeta(json.loads(open(\"./meta_covid.json\").read()))" - ] - }, - { - "cell_type": "markdown", - "id": "1bbdae66", - "metadata": {}, - "source": [ - "### Defining entity column, time column and cutoff strategy" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "4916b1ac", - "metadata": {}, - "outputs": [], - "source": [ - "entity = \"Country/Region\"\n", - "time = \"Date\"\n", - "cutoff = \"2d\"\n", - "cutoff_base = str(datetime.strptime(\"2020-01-22\", \"%Y-%m-%d\"))\n", - "cutoff_end = str(datetime.strptime(\"2020-03-29\", \"%Y-%m-%d\"))\n", - "cutoff_strategy = trane.CutoffStrategy(entity, cutoff, cutoff_base, cutoff_end, cutoff)" - ] - }, - { - "cell_type": "markdown", - "id": "cce81137", - "metadata": {}, - "source": [ - "### Generating prediction problems" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "fe494410", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Success/Attempt = 516/1044\n" - ] - } - ], - "source": [ - "problem_generator = trane.PredictionProblemGenerator(\n", - " table_meta=meta_covid,\n", - " entity_col=entity,\n", - " time_col=time,\n", - " cutoff_strategy=cutoff_strategy,\n", - ")\n", - "\n", - "problems = problem_generator.generate(df, generate_thresholds=True)" - ] - }, - { - "cell_type": "markdown", - "id": "f0bc9b88", - "metadata": {}, - "source": [ - "### Labeling the prediction tasks" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8a2ba67b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Elapsed: 00:02 | Remaining: 00:00 | Progress: 100%|███████████████████████| Country/Region: 177/177 \n", - "Elapsed: 00:05 | Remaining: 00:00 | Progress: 100%|███████████████████████| Country/Region: 177/177 \n", - 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"language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Examples/youtube_example.ipynb b/Examples/youtube_example.ipynb deleted file mode 100644 index f11fc544..00000000 --- a/Examples/youtube_example.ipynb +++ /dev/null @@ -1,21857 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "7efd117b", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/pido/miniconda3/envs/alfriend/lib/python3.7/site-packages/woodwork/__init__.py:23: FutureWarning: Woodwork may not support Python 3.7 in next non-bugfix release.\n", - " \"Woodwork may not support Python 3.7 in next non-bugfix release.\", FutureWarning\n", - "/home/pido/miniconda3/envs/alfriend/lib/python3.7/site-packages/featuretools/__init__.py:67: FutureWarning: Featuretools may not support Python 3.7 in next non-bugfix release.\n", - " FutureWarning,\n" - ] - } - ], - "source": [ - "import warnings\n", - "\n", - "# warnings.filterwarnings(\"ignore\")\n", - "warnings.filterwarnings(\"ignore\", category=DeprecationWarning)\n", - "\n", - "import copy\n", - "import json\n", - "import pandas as pd\n", - "import os\n", - "import sys\n", - "import featuretools as ft\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib\n", - "\n", - "%matplotlib inline\n", - "\n", - "sys.path.append(\"../../\")\n", - "from Trane import trane as trane\n", - "from datetime import datetime, timedelta" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "579ae6be", - "metadata": {}, - "outputs": [], - "source": [ - "# case_folder = 'youtube_pts'\n", - "# os.makedirs(case_folder, exist_ok=True)\n", - "# os.chdir(case_folder)" - ] - }, - { - "cell_type": "markdown", - "id": "8d67ebc9", - "metadata": {}, - "source": [ - "### Upload of the dataset and metadata" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "f1b249d7", - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_csv(\"./youtube/USvideos.csv\", sep=\",\")\n", - "df[\"trending_date\"] = df[\"trending_date\"].apply(\n", - " lambda x: datetime.strptime(x, \"%y.%d.%m\")\n", - ")\n", - "df = df.sort_values(by=[\"trending_date\"])\n", - "df = df.fillna(0)\n", - "meta = trane.TableMeta(json.loads(open(\"./youtube/meta.json\").read()))" - ] - }, - { - "cell_type": "markdown", - "id": "1bbdae66", - "metadata": {}, - "source": [ - "### Defining entity column, time column and cutoff strategy" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "4916b1ac", - "metadata": {}, - "outputs": [], - "source": [ - "entity = \"category_id\"\n", - "time = \"trending_date\"\n", - "cutoff = \"4d\"\n", - "cutoff_base = pd.Timestamp(datetime.strptime(\"2017-11-14\", \"%Y-%m-%d\"))\n", - "cutoff_end = pd.Timestamp(datetime.strptime(\"2018-06-14\", \"%Y-%m-%d\"))\n", - "cutoff_strategy = trane.CutoffStrategy(entity, cutoff, cutoff_base, cutoff_end)" - ] - }, - { - "cell_type": "markdown", - "id": "cce81137", - "metadata": {}, - "source": [ - "### Generating prediction problems" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "fe494410", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Success/Attempt = 101/163\n" - ] - } - ], - "source": [ - "problem_generator = trane.PredictionProblemGenerator(\n", - " table_meta=meta, entity_col=entity, time_col=time, cutoff_strategy=cutoff_strategy\n", - ")\n", - "\n", - "problems = problem_generator.generate(df, generate_thresholds=True, n_problems=100)" - ] - }, - { - "cell_type": "markdown", - "id": "f0bc9b88", - "metadata": {}, - "source": [ - "### Labeling the prediction tasks" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "8a2ba67b", - "metadata": {}, - 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" 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 1722568 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 657458 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 247227 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 58567 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 17136 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 4816 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 2038 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 600 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 201 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 6115 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 1762 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with greater than 541 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 240827 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 650153 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 1870014 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 5250 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 18987 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 54484 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 210 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 675 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 1781 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 594 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 1837 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the number of records with less than 5915 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the total in all related records in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the total in all related records in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the total in all related records in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the total in all related records in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [772 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 1968528 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [561 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 714472 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [709 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 248207 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [744 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 1824815 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [575 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 688540 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [712 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 250175 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [744 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 1738805 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [583 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 684388 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [712 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 231236 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [747 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 1904736 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [568 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 749794 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [705 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 237666 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [745 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 55257 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [529 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 19981 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [681 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 5467 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [741 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 58512 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [523 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 17835 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [695 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 5187 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [741 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 58630 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [523 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 17500 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [698 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 5471 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [741 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 58275 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [523 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 18449 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [692 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 4429 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [745 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 1902 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [576 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 602 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 29 2018-02-14 38 658130.0 \n", - " 2018-02-18 42 658130.0 \n", - " 43 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 29 2018-02-14 497847.0 1988746.0 \n", - " 2018-02-18 497847.0 1988746.0 \n", - " 43 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 29 2018-02-14 24286474.0 124152.578947 \n", - " 2018-02-18 24286474.0 114238.309524 \n", - " 43 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 29 2018-02-14 85342.736842 376316.473684 \n", - " 2018-02-18 78747.833333 349682.357143 \n", - " 43 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 29 2018-02-14 4.187227e+06 0.0 ... \n", - " 2018-02-18 3.931850e+06 0.0 ... \n", - " 43 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-02-14 True \n", - " 2018-02-18 True \n", - " 43 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-02-14 False \n", - " 2018-02-18 False \n", - " 43 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 29 2018-02-14 False \n", - " 2018-02-18 False \n", - " 43 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-02-14 False \n", - " 2018-02-18 False \n", - " 43 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-02-14 False \n", - " 2018-02-18 False \n", - " 43 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-02-14 False \n", - " 2018-02-18 False \n", - " 43 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-02-14 False \n", - " 2018-02-18 False \n", - " 43 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-02-14 True \n", - " 2018-02-18 True \n", - " 43 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 29 2018-02-14 False \n", - " 2018-02-18 False \n", - " 43 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-02-14 False \n", - " 2018-02-18 False \n", - " 43 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [698 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 197 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [744 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 1880 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [577 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 632 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-02 32 658130.0 \n", - " 2018-02-06 35 658130.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-02 497847.0 1988746.0 \n", - " 2018-02-06 497847.0 1988746.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-02 24286474.0 147303.625000 \n", - " 2018-02-06 24286474.0 134791.685714 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-02 101267.906250 446520.500000 \n", - " 2018-02-06 92654.942857 408562.514286 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-02 4.944884e+06 0.0 ... \n", - " 2018-02-06 4.545154e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-02 True \n", - " 2018-02-06 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 True \n", - " 2018-02-06 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " [690 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 209 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [743 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 1963 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [571 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 643 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-02 32 658130.0 \n", - " 2018-02-06 35 658130.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-02 497847.0 1988746.0 \n", - " 2018-02-06 497847.0 1988746.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-02 24286474.0 147303.625000 \n", - " 2018-02-06 24286474.0 134791.685714 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-02 101267.906250 446520.500000 \n", - " 2018-02-06 92654.942857 408562.514286 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-02 4.944884e+06 0.0 ... \n", - " 2018-02-06 4.545154e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-02 True \n", - " 2018-02-06 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 True \n", - " 2018-02-06 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " [690 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 200 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [744 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 2000 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [569 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 626 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-02 32 658130.0 \n", - " 2018-02-06 35 658130.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-02 497847.0 1988746.0 \n", - " 2018-02-06 497847.0 1988746.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-02 24286474.0 147303.625000 \n", - " 2018-02-06 24286474.0 134791.685714 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-02 101267.906250 446520.500000 \n", - " 2018-02-06 92654.942857 408562.514286 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-02 4.944884e+06 0.0 ... \n", - " 2018-02-06 4.545154e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-02 True \n", - " 2018-02-06 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 True \n", - " 2018-02-06 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-02 False \n", - " 2018-02-06 False \n", - " 2018-02-14 False \n", - " \n", - " [691 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 195 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [744 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 5791 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [603 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 1940 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-01-01 10 1984.0 \n", - " 2018-04-15 18 1998.0 \n", - " 2018-04-19 22 2117.0 \n", - " 2018-04-23 26 2148.0 \n", - " 2018-04-27 30 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-01-01 244.0 4739.0 \n", - " 2018-04-15 371.0 26310.0 \n", - " 2018-04-19 441.0 30186.0 \n", - " 2018-04-23 462.0 32145.0 \n", - " 2018-04-27 470.0 32815.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-01-01 178191.0 1817.300000 \n", - " 2018-04-15 891246.0 1401.777778 \n", - " 2018-04-19 1182221.0 1522.909091 \n", - " 2018-04-23 1335365.0 1618.230769 \n", - " 2018-04-27 1400041.0 1691.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-01-01 224.800000 4410.800000 \n", - " 2018-04-15 202.166667 5790.666667 \n", - " 2018-04-19 243.409091 10090.181818 \n", - " 2018-04-23 276.538462 13426.461538 \n", - " 2018-04-27 301.800000 15962.500000 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-04-15 1.993121e+05 220.0 ... \n", - " 2018-04-19 3.685994e+05 220.0 ... \n", - " 2018-04-23 5.120393e+05 220.0 ... \n", - " 2018-04-27 6.262338e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 True \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 True \n", - " 2018-04-15 False \n", - " 2018-04-19 True \n", - " 2018-04-23 True \n", - " 2018-04-27 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 True \n", - " 2018-04-23 True \n", - " 2018-04-27 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-01-01 True \n", - " 2018-04-15 True \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " [714 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 588 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [753 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 5811 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [603 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 1919 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-01-01 10 1984.0 \n", - " 2018-04-15 18 1998.0 \n", - " 2018-04-19 22 2117.0 \n", - " 2018-04-23 26 2148.0 \n", - " 2018-04-27 30 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-01-01 244.0 4739.0 \n", - " 2018-04-15 371.0 26310.0 \n", - " 2018-04-19 441.0 30186.0 \n", - " 2018-04-23 462.0 32145.0 \n", - " 2018-04-27 470.0 32815.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-01-01 178191.0 1817.300000 \n", - " 2018-04-15 891246.0 1401.777778 \n", - " 2018-04-19 1182221.0 1522.909091 \n", - " 2018-04-23 1335365.0 1618.230769 \n", - " 2018-04-27 1400041.0 1691.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-01-01 224.800000 4410.800000 \n", - " 2018-04-15 202.166667 5790.666667 \n", - " 2018-04-19 243.409091 10090.181818 \n", - " 2018-04-23 276.538462 13426.461538 \n", - " 2018-04-27 301.800000 15962.500000 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-04-15 1.993121e+05 220.0 ... \n", - " 2018-04-19 3.685994e+05 220.0 ... \n", - " 2018-04-23 5.120393e+05 220.0 ... \n", - " 2018-04-27 6.262338e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 True \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 True \n", - " 2018-04-15 False \n", - " 2018-04-19 True \n", - " 2018-04-23 True \n", - " 2018-04-27 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 True \n", - " 2018-04-23 True \n", - " 2018-04-27 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-01-01 True \n", - " 2018-04-15 True \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " [716 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 567 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [756 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 5284 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [624 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 1877 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-01-01 10 1984.0 \n", - " 2018-04-15 18 1998.0 \n", - " 2018-04-19 22 2117.0 \n", - " 2018-04-23 26 2148.0 \n", - " 2018-04-27 30 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-01-01 244.0 4739.0 \n", - " 2018-04-15 371.0 26310.0 \n", - " 2018-04-19 441.0 30186.0 \n", - " 2018-04-23 462.0 32145.0 \n", - " 2018-04-27 470.0 32815.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-01-01 178191.0 1817.300000 \n", - " 2018-04-15 891246.0 1401.777778 \n", - " 2018-04-19 1182221.0 1522.909091 \n", - " 2018-04-23 1335365.0 1618.230769 \n", - " 2018-04-27 1400041.0 1691.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-01-01 224.800000 4410.800000 \n", - " 2018-04-15 202.166667 5790.666667 \n", - " 2018-04-19 243.409091 10090.181818 \n", - " 2018-04-23 276.538462 13426.461538 \n", - " 2018-04-27 301.800000 15962.500000 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-04-15 1.993121e+05 220.0 ... \n", - " 2018-04-19 3.685994e+05 220.0 ... \n", - " 2018-04-23 5.120393e+05 220.0 ... \n", - " 2018-04-27 6.262338e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 True \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 True \n", - " 2018-04-15 False \n", - " 2018-04-19 True \n", - " 2018-04-23 True \n", - " 2018-04-27 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 True \n", - " 2018-04-23 True \n", - " 2018-04-27 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-01-01 True \n", - " 2018-04-15 True \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-01-01 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " [718 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 547 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [756 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 5645 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 28 2018-06-10 2375 180913.0 \n", - " 2018-06-14 2401 180913.0 \n", - " 29 2018-01-25 24 363133.0 \n", - " 2018-01-29 28 625002.0 \n", - " 2018-02-14 38 658130.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 28 2018-06-10 47469.0 564804.0 \n", - " 2018-06-14 47469.0 564804.0 \n", - " 29 2018-01-25 147643.0 1167488.0 \n", - " 2018-01-29 461659.0 1919981.0 \n", - " 2018-02-14 497847.0 1988746.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 28 2018-06-10 42799458.0 4970.277895 \n", - " 2018-06-14 42799458.0 4993.721783 \n", - " 29 2018-01-25 8041970.0 15211.333333 \n", - " 2018-01-29 22387656.0 98947.250000 \n", - " 2018-02-14 24286474.0 124152.578947 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 28 2018-06-10 1842.308632 34095.681263 \n", - " 2018-06-14 1894.378176 34374.276551 \n", - " 29 2018-01-25 6171.458333 49251.791667 \n", - " 2018-01-29 63495.250000 299188.750000 \n", - " 2018-02-14 85342.736842 376316.473684 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 28 2018-06-10 1.438713e+06 0.0 ... \n", - " 2018-06-14 1.452627e+06 0.0 ... \n", - " 29 2018-01-25 3.510557e+05 0.0 ... \n", - " 2018-01-29 3.100653e+06 0.0 ... \n", - " 2018-02-14 4.187227e+06 0.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 True \n", - " 2018-06-14 True \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-02-14 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 28 2018-06-10 False \n", - " 2018-06-14 False \n", - " 29 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-02-14 False \n", - " \n", - " [608 rows x 71 columns],\n", - " 'For each predict the total in all related records with greater than 1807 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-04-11 16 1998.0 \n", - " 2018-04-15 18 1998.0 \n", - " 2018-04-19 22 2117.0 \n", - " 2018-04-23 26 2148.0 \n", - " 2018-04-27 30 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-04-11 247.0 4763.0 \n", - " 2018-04-15 371.0 26310.0 \n", - " 2018-04-19 441.0 30186.0 \n", - " 2018-04-23 462.0 32145.0 \n", - " 2018-04-27 470.0 32815.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-04-11 179723.0 1340.375000 \n", - " 2018-04-15 891246.0 1401.777778 \n", - " 2018-04-19 1182221.0 1522.909091 \n", - " 2018-04-23 1335365.0 1618.230769 \n", - " 2018-04-27 1400041.0 1691.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-04-11 184.875000 3363.437500 \n", - " 2018-04-15 202.166667 5790.666667 \n", - " 2018-04-19 243.409091 10090.181818 \n", - " 2018-04-23 276.538462 13426.461538 \n", - " 2018-04-27 301.800000 15962.500000 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-04-11 1.274492e+05 220.0 ... \n", - " 2018-04-15 1.993121e+05 220.0 ... \n", - " 2018-04-19 3.685994e+05 220.0 ... \n", - " 2018-04-23 5.120393e+05 220.0 ... \n", - " 2018-04-27 6.262338e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-04-11 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-04-11 False \n", - " 2018-04-15 True \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-04-11 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-04-11 True \n", - " 2018-04-15 False \n", - " 2018-04-19 True \n", - " 2018-04-23 True \n", - " 2018-04-27 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-04-11 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-04-11 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-04-11 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-04-11 False \n", - " 2018-04-15 False \n", - " 2018-04-19 True \n", - " 2018-04-23 True \n", - " 2018-04-27 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-04-11 True \n", - " 2018-04-15 True \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-04-11 False \n", - " 2018-04-15 False \n", - " 2018-04-19 False \n", - " 2018-04-23 False \n", - " 2018-04-27 False \n", - " \n", - " [720 rows x 72 columns],\n", - " 'For each predict the total in all related records with greater than 639 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [750 rows x 72 columns],\n", - " 'For each predict the total in all related records with less than 242627 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [606 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 712778 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " 2018-04-11 16 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " 2018-04-11 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " 2018-04-11 179723.0 1340.375000 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " 2018-04-11 184.875000 3363.437500 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " 2018-04-11 1.274492e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-04-11 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-04-11 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " [716 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 1780225 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [769 rows x 72 columns],\n", - " 'For each predict the total in all related records with less than 234280 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [604 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 651645 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [713 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 1797044 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [769 rows x 72 columns],\n", - " 'For each predict the total in all related records with less than 235830 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [604 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 679906 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " 2018-04-11 16 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " 2018-04-11 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " 2018-04-11 179723.0 1340.375000 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " 2018-04-11 184.875000 3363.437500 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " 2018-04-11 1.274492e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-04-11 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-04-11 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " [715 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 1770318 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [769 rows x 72 columns],\n", - " 'For each predict the total in all related records with less than 236912 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [604 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 678676 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " 2018-04-11 16 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " 2018-04-11 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " 2018-04-11 179723.0 1340.375000 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " 2018-04-11 184.875000 3363.437500 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " 2018-04-11 1.274492e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-04-11 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " 2018-04-11 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " 2018-04-11 False \n", - " \n", - " [715 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 1790942 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [769 rows x 72 columns],\n", - " 'For each predict the total in all related records with less than 5845 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [604 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 17911 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [722 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 56564 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [770 rows x 72 columns],\n", - " 'For each predict the total in all related records with less than 5246 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [593 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 18376 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [724 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 54319 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [770 rows x 72 columns],\n", - " 'For each predict the total in all related records with less than 6347 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [616 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 17222 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [721 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 53082 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [770 rows x 72 columns],\n", - " 'For each predict the total in all related records with less than 5545 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [599 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 17460 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2017-12-24 2 1645.0 \n", - " 2017-12-28 6 1870.0 \n", - " 2018-01-01 10 1984.0 \n", - " 2018-01-25 11 1998.0 \n", - " 2018-01-29 15 1998.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2017-12-24 202.0 4080.0 \n", - " 2017-12-28 233.0 4564.0 \n", - " 2018-01-01 244.0 4739.0 \n", - " 2018-01-25 247.0 4763.0 \n", - " 2018-01-29 247.0 4763.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2017-12-24 134433.0 1535.500000 \n", - " 2017-12-28 166529.0 1722.166667 \n", - " 2018-01-01 178191.0 1817.300000 \n", - " 2018-01-25 179723.0 1833.727273 \n", - " 2018-01-29 179723.0 1412.133333 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2017-12-24 191.000000 3813.500000 \n", - " 2017-12-28 214.333333 4222.500000 \n", - " 2018-01-01 224.800000 4410.800000 \n", - " 2018-01-25 226.818182 4442.818182 \n", - " 2018-01-29 189.666667 3512.333333 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2017-12-24 1.222725e+05 1426.0 ... \n", - " 2017-12-28 1.453738e+05 1426.0 ... \n", - " 2018-01-01 1.571723e+05 1426.0 ... \n", - " 2018-01-25 1.592224e+05 1426.0 ... \n", - " 2018-01-29 1.311054e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2017-12-24 True \n", - " 2017-12-28 True \n", - " 2018-01-01 True \n", - " 2018-01-25 True \n", - " 2018-01-29 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2017-12-24 False \n", - " 2017-12-28 False \n", - " 2018-01-01 False \n", - " 2018-01-25 False \n", - " 2018-01-29 False \n", - " \n", - " [721 rows x 71 columns],\n", - " 'For each predict the total in all related records with less than 57817 in next 4d days': COUNT(youtube) MAX(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 8 7915.0 \n", - " 2017-11-18 49 11910.0 \n", - " 2017-11-22 85 45240.0 \n", - " 2017-11-26 134 47119.0 \n", - " 2017-11-30 174 48348.0 \n", - " ... ... ... \n", - " 43 2018-05-21 41 2181.0 \n", - " 2018-05-25 45 2181.0 \n", - " 2018-05-29 49 2181.0 \n", - " 2018-06-02 53 2181.0 \n", - " 2018-06-06 57 2181.0 \n", - " \n", - " MAX(youtube.dislikes) MAX(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 3492.0 58967.0 \n", - " 2017-11-18 5437.0 254158.0 \n", - " 2017-11-22 7892.0 369518.0 \n", - " 2017-11-26 12821.0 431134.0 \n", - " 2017-11-30 15434.0 444698.0 \n", - " ... ... ... \n", - " 43 2018-05-21 578.0 33261.0 \n", - " 2018-05-25 589.0 33261.0 \n", - " 2018-05-29 605.0 33261.0 \n", - " 2018-06-02 608.0 33261.0 \n", - " 2018-06-06 616.0 33261.0 \n", - " \n", - " MAX(youtube.views) MEAN(youtube.comment_count) \\\n", - " category_id time \n", - " 1 2017-11-14 2736733.0 1561.500000 \n", - " 2017-11-18 8291139.0 2463.551020 \n", - " 2017-11-22 17613871.0 4703.188235 \n", - " 2017-11-26 29964922.0 5265.746269 \n", - " 2017-11-30 36152111.0 5115.695402 \n", - " ... ... ... \n", - " 43 2018-05-21 1445949.0 1685.292683 \n", - " 2018-05-25 1445949.0 1677.955556 \n", - " 2018-05-29 1445949.0 1672.877551 \n", - " 2018-06-02 1445949.0 1670.245283 \n", - " 2018-06-06 1445949.0 1668.719298 \n", - " \n", - " MEAN(youtube.dislikes) MEAN(youtube.likes) \\\n", - " category_id time \n", - " 1 2017-11-14 749.250000 11596.250000 \n", - " 2017-11-18 801.551020 26569.795918 \n", - " 2017-11-22 1340.741176 48967.988235 \n", - " 2017-11-26 1606.656716 50841.059701 \n", - " 2017-11-30 1654.005747 47653.350575 \n", - " ... ... ... \n", - " 43 2018-05-21 363.170732 17801.902439 \n", - " 2018-05-25 382.733333 18119.955556 \n", - " 2018-05-29 400.510204 18433.244898 \n", - " 2018-06-02 416.075472 18727.264151 \n", - " 2018-06-06 429.964912 18993.666667 \n", - " \n", - " MEAN(youtube.views) MIN(youtube.comment_count) ... \\\n", - " category_id time ... \n", - " 1 2017-11-14 7.519099e+05 17.0 ... \n", - " 2017-11-18 1.109045e+06 3.0 ... \n", - " 2017-11-22 2.132388e+06 0.0 ... \n", - " 2017-11-26 2.532531e+06 0.0 ... \n", - " 2017-11-30 2.525553e+06 0.0 ... \n", - " ... ... ... ... \n", - " 43 2018-05-21 7.583313e+05 220.0 ... \n", - " 2018-05-25 7.964295e+05 220.0 ... \n", - " 2018-05-29 8.344194e+05 220.0 ... \n", - " 2018-06-02 8.704219e+05 220.0 ... \n", - " 2018-06-06 9.035273e+05 220.0 ... \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 4 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 5 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 0 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 3 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 True \n", - " 2017-11-22 False \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 2 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) = 6 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.WEEKDAY(trending_date)) is unknown \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2018 \\\n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 True \n", - " 2018-05-25 True \n", - " 2018-05-29 True \n", - " 2018-06-02 True \n", - " 2018-06-06 True \n", - " \n", - " MODE(youtube.YEAR(trending_date)) = 2017 \\\n", - " category_id time \n", - " 1 2017-11-14 True \n", - " 2017-11-18 True \n", - " 2017-11-22 True \n", - " 2017-11-26 True \n", - " 2017-11-30 True \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " MODE(youtube.YEAR(trending_date)) is unknown \n", - " category_id time \n", - " 1 2017-11-14 False \n", - " 2017-11-18 False \n", - " 2017-11-22 False \n", - " 2017-11-26 False \n", - " 2017-11-30 False \n", - " ... ... \n", - " 43 2018-05-21 False \n", - " 2018-05-25 False \n", - " 2018-05-29 False \n", - " 2018-06-02 False \n", - " 2018-06-06 False \n", - " \n", - " [770 rows x 72 columns]}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "problem_features_dict" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.1" - }, - "vscode": { - "interpreter": { - "hash": "8207ecde8cf2fda520169a8f8360958470b9168fa3b5c7074fdec936472ea246" - } - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Makefile b/Makefile index 89507dd1..2ef46df2 100755 --- a/Makefile +++ b/Makefile @@ -5,6 +5,7 @@ clean: find . -name __pycache__ -delete find . -name '*~' -delete find . -name '.coverage.*' -delete + coverage erase .PHONY: lint lint: @@ -34,7 +35,7 @@ COVERAGE = --cov=trane/ --cov-report term-missing --cov-config=./pyproject.toml .PHONY: tests tests: - $(PYTEST) tests/ --sample 100 $(COVERAGE) + $(PYTEST) tests/ .PHONY: unit-tests unit-tests: diff --git a/README.md b/README.md index 5d77e109..59547123 100755 --- a/README.md +++ b/README.md @@ -33,6 +33,37 @@ To install Trane, run the following command: python -m pip install trane ``` +# Example + +Below is an example of using Trane: + +```python +import trane + +data = trane.datasets.load_covid() +table_meta = trane.datasets.load_covid_metadata() + +entity_col = "Country/Region" +window_size = "2d" +minimum_data = "2020-01-22" +maximum_data = "2020-03-29" +cutoff_strategy = trane.CutoffStrategy( + entity_col=entity_col, + window_size=window_size, + minimum_data=minimum_data, + maximum_data=maximum_data, +) +time_col = "Date" +problem_generator = trane.PredictionProblemGenerator( + entity_col=entity_col, + time_col=time_col, + cutoff_strategy=cutoff_strategy, + table_meta=table_meta, +) +problems = problem_generator.generate(data, generate_thresholds=True) +``` + + ## Citing Trane If you use Trane, please consider citing the following paper: diff --git a/docs/Chicago Bike Example - Detailed Walkthrough.ipynb b/docs/Chicago Bike Example - Detailed Walkthrough.ipynb deleted file mode 100644 index b626e0c1..00000000 --- a/docs/Chicago Bike Example - Detailed Walkthrough.ipynb +++ /dev/null @@ -1,440 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "id": "1abae5f1", - "metadata": {}, - "outputs": [], - "source": [ - "# Automatically generate prediction problems for the Chicago bike sharing dataset with Trane" - ] - }, - { - "cell_type": "markdown", - "id": "4597963b", - "metadata": {}, - "source": [ - "In this tutorial, we will show how we can use Trane to generate predictions problems for a bike sharing program, [from Kaggle](https://www.kaggle.com/datasets/yingwurenjian/chicago-divvy-bicycle-sharing-data).\n", - "\n", - "## Load Data\n", - "First, let's load our data, and examine the first few rows." - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "f9f60f09", - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "\n", - "data = pd.read_csv(\"data_raw.csv\")" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "18d32a5f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Subscriber 10017631\n", - "Customer 3756894\n", - "Dependent 190\n", - "Name: usertype, dtype: int64" - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "counts = data[\"usertype\"].value_counts()\n", - "counts" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "15f9bf49", - "metadata": {}, - "outputs": [], - "source": [ - "remove_rows = data[data[\"usertype\"] == \"Dependent\"]\n", - "data = data.drop(index=remove_rows.index)" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "864fd495", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Subscriber 10017631\n", - "Customer 3756894\n", - "Name: usertype, dtype: int64" - ] - }, - "execution_count": 40, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "counts = data[\"usertype\"].value_counts()\n", - "counts" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "16395769", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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trip_idusertypegenderstarttimestoptimetripdurationfrom_station_idfrom_station_namelatitude_startlongitude_start...windchilldewpointhumiditypressurevisibilitywind_speedprecipitationeventsrainconditions
1377471016734070SubscriberMale2017-10-01 00:01:002017-10-01 00:15:00837289Wells St & Concord Ln41.912133-87.634656...-999.041.064.030.3110.08.1-9999.0partlycloudy0Partly Cloudy
1377471116734069CustomerNaN2017-10-01 00:00:002017-10-01 00:07:0036645Michigan Ave & Congress Pkwy41.876243-87.624426...-999.041.064.030.3110.08.1-9999.0partlycloudy0Partly Cloudy
1377471216734068CustomerNaN2017-10-01 00:00:002017-10-01 00:05:00264520Greenview Ave & Jarvis Ave42.015962-87.668570...-999.041.064.030.3110.08.1-9999.0partlycloudy0Partly Cloudy
1377471316734067SubscriberFemale2017-10-01 00:00:002017-10-01 00:06:00361288Larrabee St & Armitage Ave41.918084-87.643749...-999.041.064.030.3110.08.1-9999.0partlycloudy0Partly Cloudy
1377471416734066SubscriberFemale2017-10-01 00:00:002017-10-01 00:12:00741135Halsted St & 21st St41.853780-87.646650...-999.041.064.030.3110.08.1-9999.0partlycloudy0Partly Cloudy
\n", - "

5 rows × 27 columns

\n", - "
" - ], - "text/plain": [ - " trip_id usertype gender starttime \\\n", - "13774710 16734070 Subscriber Male 2017-10-01 00:01:00 \n", - "13774711 16734069 Customer NaN 2017-10-01 00:00:00 \n", - "13774712 16734068 Customer NaN 2017-10-01 00:00:00 \n", - "13774713 16734067 Subscriber Female 2017-10-01 00:00:00 \n", - "13774714 16734066 Subscriber Female 2017-10-01 00:00:00 \n", - "\n", - " stoptime tripduration from_station_id \\\n", - "13774710 2017-10-01 00:15:00 837 289 \n", - "13774711 2017-10-01 00:07:00 366 45 \n", - "13774712 2017-10-01 00:05:00 264 520 \n", - "13774713 2017-10-01 00:06:00 361 288 \n", - "13774714 2017-10-01 00:12:00 741 135 \n", - "\n", - " from_station_name latitude_start longitude_start ... \\\n", - "13774710 Wells St & Concord Ln 41.912133 -87.634656 ... \n", - "13774711 Michigan Ave & Congress Pkwy 41.876243 -87.624426 ... \n", - "13774712 Greenview Ave & Jarvis Ave 42.015962 -87.668570 ... \n", - "13774713 Larrabee St & Armitage Ave 41.918084 -87.643749 ... \n", - "13774714 Halsted St & 21st St 41.853780 -87.646650 ... \n", - "\n", - " windchill dewpoint humidity pressure visibility wind_speed \\\n", - "13774710 -999.0 41.0 64.0 30.31 10.0 8.1 \n", - "13774711 -999.0 41.0 64.0 30.31 10.0 8.1 \n", - "13774712 -999.0 41.0 64.0 30.31 10.0 8.1 \n", - "13774713 -999.0 41.0 64.0 30.31 10.0 8.1 \n", - "13774714 -999.0 41.0 64.0 30.31 10.0 8.1 \n", - "\n", - " precipitation events rain conditions \n", - "13774710 -9999.0 partlycloudy 0 Partly Cloudy \n", - "13774711 -9999.0 partlycloudy 0 Partly Cloudy \n", - "13774712 -9999.0 partlycloudy 0 Partly Cloudy \n", - "13774713 -9999.0 partlycloudy 0 Partly Cloudy \n", - "13774714 -9999.0 partlycloudy 0 Partly Cloudy \n", - "\n", - "[5 rows x 27 columns]" - ] - }, - "execution_count": 43, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.tail(5)" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "d9acbee1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of Rows: 13774525\n" - ] - } - ], - "source": [ - "print(f\"Number of Rows: {data.shape[0]}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "575dbf32", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['trip_id', 'usertype', 'gender', 'starttime', 'stoptime',\n", - " 'tripduration', 'from_station_id', 'from_station_name',\n", - " 'latitude_start', 'longitude_start', 'dpcapacity_start',\n", - " 'to_station_id', 'to_station_name', 'latitude_end', 'longitude_end',\n", - " 'dpcapacity_end', 'temperature', 'windchill', 'dewpoint', 'humidity',\n", - " 'pressure', 'visibility', 'wind_speed', 'precipitation', 'events',\n", - " 'rain', 'conditions'],\n", - " dtype='object')" - ] - }, - "execution_count": 44, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.columns" - ] - }, - { - "cell_type": "markdown", - "id": "cd590828", - "metadata": {}, - "source": [ - "As we can see, this is a dataset from a bike sharing program. We have information on where the riders go, when they ride, how far they go, how long their trips are, etc. \n", - "\n", - "We are required to determine the following parameters to generate the Cutoff Strategy:\n", - "\n", - "**entity_col**: the column name to use for grouping the data.\n", - "- For this walkthrough, we are interested interested in prediction problems `user type`, which could be a Customer or Subscriber.\n", - "\n", - "**window_size**: the amount of data to use per label\n", - "- We will set this at `2d`, to account for the delay in reporting Covid information. \n", - "\n", - "**minimum_size**: the time at which the labeling should begin\n", - " - We want to use all avaliable information for labeling: set the `minimum_size` to the timestamp of the oldest data point \n", - "\n", - "**maximum_size**: the time at which the labeling will end\n", - " - We want to create labels for all data points: set the `maximum_size` to be the timestamp of the most recent data point. " - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "af03f594", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "metadata = trane.datasets.load_bike_metadata()\n", - "metadata" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b2e9a63f", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.2" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/Covid Example - Detailed Walkthrough.ipynb b/docs/Covid Example - Detailed Walkthrough.ipynb index 249ef838..986c8ddf 100644 --- a/docs/Covid Example - Detailed Walkthrough.ipynb +++ b/docs/Covid Example - Detailed Walkthrough.ipynb @@ -215,35 +215,35 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "51b06c76", "metadata": {}, "outputs": [], "source": [ - "from trane.utils import TableMeta\n", + "from trane.column_schema import ColumnSchema\n", + "from trane.logical_types import Categorical, Double, Datetime, Integer\n", "\n", - "metadata = {\n", - " \"tables\": [\n", - " {\n", - " \"fields\": [\n", - " {\"name\": \"Province/State\", \"type\": \"text\"},\n", - " {\"name\": \"Country/Region\", \"type\": \"text\"},\n", - " {\"name\": \"Lat\", \"type\": \"number\", \"subtype\": \"float\"},\n", - " {\"name\": \"Long\", \"type\": \"number\", \"subtype\": \"float\"},\n", - " {\"name\": \"Date\", \"type\": \"datetime\"},\n", - " {\"name\": \"Confirmed\", \"type\": \"number\", \"subtype\": \"integer\"},\n", - " {\"name\": \"Deaths\", \"type\": \"number\", \"subtype\": \"integer\"},\n", - " {\"name\": \"Recovered\", \"type\": \"number\", \"subtype\": \"integer\"},\n", - " ],\n", - " },\n", - " ],\n", - "}\n", - "table_meta = TableMeta(metadata)" + "table_meta = {\n", + " \"Province/State\": ColumnSchema(\n", + " logical_type=Categorical,\n", + " semantic_tags={\"category\"},\n", + " ),\n", + " \"Country/Region\": ColumnSchema(\n", + " logical_type=Categorical,\n", + " semantic_tags={\"category\", \"index\"},\n", + " ),\n", + " \"Lat\": ColumnSchema(logical_type=Double, semantic_tags={\"numeric\"}),\n", + " \"Long\": ColumnSchema(logical_type=Double, semantic_tags={\"numeric\"}),\n", + " \"Date\": ColumnSchema(logical_type=Datetime),\n", + " \"Confirmed\": ColumnSchema(logical_type=Integer, semantic_tags={\"numeric\"}),\n", + " \"Deaths\": ColumnSchema(logical_type=Integer, semantic_tags={\"numeric\"}),\n", + " \"Recovered\": ColumnSchema(logical_type=Integer, semantic_tags={\"numeric\"}),\n", + "}" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "0fcfb8db", "metadata": { "scrolled": true @@ -252,7 +252,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "dc77230ef5674666a1ed1ec178fda0f2", + "model_id": "0abaaf55a71d424aa2570c8d79d7cd4d", "version_major": 2, "version_minor": 0 }, @@ -262,13 +262,6 @@ }, "metadata": {}, "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Success/Attempt = 525/1044\n" - ] } ], "source": [ @@ -285,73 +278,44 @@ }, { "cell_type": "code", - "execution_count": 7, - "id": "e94cdbb3", - "metadata": {}, - "outputs": [], - "source": [ - "prediction_problem_to_label_times = {}\n", - "for idx, problem in enumerate(problems):\n", - " problem_sentence = str(problem)\n", - " prediction_problem_to_label_times[problem_sentence] = problem.execute(\n", - " data, -1, verbose=False\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "06ebb2d7", + "execution_count": null, + "id": "7a2f348b", "metadata": {}, "outputs": [ { "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "eeab61409825474fb08ef9c1735b44fc", + "version_major": 2, + "version_minor": 0 + }, "text/plain": [ - "525" + " 0%| | 0/544 [00:00 predict the number of records with greater than 41.6086 in next 2d days\n", - "----\n", - "For each predict the total in all related records with greater than -19.0208 in next 2d days\n", - "----\n", - "For each predict the average in all related records with greater than 0 in next 2d days\n", - "----\n", - "For each predict the maximum in all related records with greater than 90.3563 in next 2d days\n", - "----\n", - "For each predict the minimum in all related records in next 2d days\n", - "----\n", - "\n", - "Total Number of Prediction Problems = 525\n" - ] - } - ], + "outputs": [], "source": [ - "picked_indexes = [1, 50, 200, 300, 400]\n", - "for idx, problem in enumerate(problems[i] for i in picked_indexes):\n", - " problem_sentence = str(problem)\n", - " print(f\"{problem_sentence}\")\n", - " print(\"----\")\n", - "\n", - "print(f\"\\nTotal Number of Prediction Problems = {len(problems)}\")" + "len(problems)" ] }, { @@ -480,7 +444,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.3" }, "vscode": { "interpreter": { diff --git a/docs/Quickstart - Covid Example.ipynb b/docs/Quickstart - Covid Example.ipynb deleted file mode 100644 index 9e993982..00000000 --- a/docs/Quickstart - Covid Example.ipynb +++ /dev/null @@ -1,498 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "3320a286", - "metadata": {}, - "source": [ - "# Trane Quickstart Guide - Covid Example" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "bf64e16f", - "metadata": {}, - "outputs": [], - "source": [ - "import trane\n", - "import pandas as pd\n", - "import json\n", - "from datetime import datetime\n", - "from urllib.request import urlopen\n", - "\n", - "\n", - "data_url = \"https://raw.githubusercontent.com/HDI-Project/Trane/main/Examples/covid/\"\n", - "df = pd.read_csv(f\"{data_url}covid19.csv\")\n", - "df[\"Date\"] = df[\"Date\"].apply(lambda x: datetime.strptime(x, \"%m/%d/%y\"))\n", - "df = df.sort_values(by=[\"Date\"])\n", - "df = df.fillna(0)\n", - "\n", - "meta_covid_response = urlopen(f\"{data_url}meta_covid.json\")\n", - "meta_covid = trane.TableMeta(json.loads(meta_covid_response.read()))" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "b6713657", - "metadata": {}, - "outputs": [], - "source": [ - "entity_col = \"Country/Region\"\n", - "time_col = \"Date\"\n", - "window_size = \"2d\"\n", - "cutoff_base = \"2020-01-22\"\n", - "cutoff_end = \"2020-03-29\"\n", - "cutoff_strategy = trane.CutoffStrategy(\n", - " entity_col,\n", - " window_size=window_size,\n", - " minimum_data=cutoff_base,\n", - " maximum_data=cutoff_end,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "0fcfb8db", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "d7f4b7afd98546ce8ab0bef3220ccd60", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/1044 [00:00 predict the number of records with greater than 41.1533 in next 2d days\n", - "----\n", - "For each predict the total in all related records with greater than -23.0418 in next 2d days\n", - "----\n", - "For each predict the average in all related records with greater than 0 in next 2d days\n", - "----\n", - "For each predict the maximum in all related records with greater than -19.0208 in next 2d days\n", - "----\n", - "For each predict the minimum in all related records with greater than 41.3775 in next 2d days\n", - "----\n", - "\n", - "Total Number of Prediction Problems = 515\n" - ] - } - ], - "source": [ - "picked_indexes = [1, 50, 200, 300, 400]\n", - "for idx, problem in enumerate(problems[i] for i in picked_indexes):\n", - " problem_sentence = str(problem)\n", - " print(f\"{problem_sentence}\")\n", - " print(\"----\")\n", - "\n", - "print(f\"\\nTotal Number of Prediction Problems = {len(problems)}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "cb05cfbd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "For each predict the number of records in next 2d days \n", - "\n", - " Country/Region time _execute_operations_on_df\n", - "0 Afghanistan 2020-01-22 2\n", - "1 Afghanistan 2020-01-24 2\n", - "2 Afghanistan 2020-01-26 2\n", - "3 Afghanistan 2020-01-28 2\n", - "4 Afghanistan 2020-01-30 2\n" - ] - } - ], - "source": [ - "problem = problems[0]\n", - "problem_sentence = str(problem)\n", - "label_times = problem.execute(df, -1, verbose=False)\n", - "print(problem_sentence, \"\\n\")\n", - "print(label_times.head(5))" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "daf95f57", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Built 41 features\n", - "Elapsed: 00:03 | Progress: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████\n" - ] - } - ], - "source": [ - "ft_wrapper = trane.FeaturetoolsWrapper(\n", - " df=df, entity_col=entity_col, time_col=time_col, name=\"covid\"\n", - ")\n", - "feature_matrix, features = ft_wrapper.compute_features(label_times, window_size)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "abdd8c93", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "\n", - "\n", - "\n", - "\n" - ] - } - ], - "source": [ - "for feature in features[:5]:\n", - " print(feature)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "9bb08074", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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Country/RegiontimeCOUNT(covid)MAX(covid.Confirmed)MAX(covid.Deaths)MAX(covid.Lat)MAX(covid.Long)MAX(covid.Recovered)MEAN(covid.Confirmed)MEAN(covid.Deaths)...SUM(covid.Recovered)MODE(covid.DAY(Date))MODE(covid.MONTH(Date))MODE(covid.WEEKDAY(Date))MODE(covid.YEAR(Date))NUM_UNIQUE(covid.DAY(Date))NUM_UNIQUE(covid.MONTH(Date))NUM_UNIQUE(covid.WEEKDAY(Date))NUM_UNIQUE(covid.YEAR(Date))_execute_operations_on_df
0Afghanistan2020-01-2210.00.033.065.00.00.00.0...0.02212202011112
1Afghanistan2020-01-2430.00.033.065.00.00.00.0...0.02212202031312
2Afghanistan2020-01-2650.00.033.065.00.00.00.0...0.02212202051512
3Afghanistan2020-01-2870.00.033.065.00.00.00.0...0.02210202071712
4Afghanistan2020-01-3090.00.033.065.00.00.00.0...0.02212202091712
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" - ], - "text/plain": [ - " Country/Region time COUNT(covid) MAX(covid.Confirmed) \\\n", - "0 Afghanistan 2020-01-22 1 0.0 \n", - "1 Afghanistan 2020-01-24 3 0.0 \n", - "2 Afghanistan 2020-01-26 5 0.0 \n", - "3 Afghanistan 2020-01-28 7 0.0 \n", - "4 Afghanistan 2020-01-30 9 0.0 \n", - "\n", - " MAX(covid.Deaths) MAX(covid.Lat) MAX(covid.Long) MAX(covid.Recovered) \\\n", - "0 0.0 33.0 65.0 0.0 \n", - "1 0.0 33.0 65.0 0.0 \n", - "2 0.0 33.0 65.0 0.0 \n", - "3 0.0 33.0 65.0 0.0 \n", - "4 0.0 33.0 65.0 0.0 \n", - "\n", - " MEAN(covid.Confirmed) MEAN(covid.Deaths) ... SUM(covid.Recovered) \\\n", - "0 0.0 0.0 ... 0.0 \n", - "1 0.0 0.0 ... 0.0 \n", - "2 0.0 0.0 ... 0.0 \n", - "3 0.0 0.0 ... 0.0 \n", - "4 0.0 0.0 ... 0.0 \n", - "\n", - " MODE(covid.DAY(Date)) MODE(covid.MONTH(Date)) MODE(covid.WEEKDAY(Date)) \\\n", - "0 22 1 2 \n", - "1 22 1 2 \n", - "2 22 1 2 \n", - "3 22 1 0 \n", - "4 22 1 2 \n", - "\n", - " MODE(covid.YEAR(Date)) NUM_UNIQUE(covid.DAY(Date)) \\\n", - "0 2020 1 \n", - "1 2020 3 \n", - "2 2020 5 \n", - "3 2020 7 \n", - "4 2020 9 \n", - "\n", - " NUM_UNIQUE(covid.MONTH(Date)) NUM_UNIQUE(covid.WEEKDAY(Date)) \\\n", - "0 1 1 \n", - "1 1 3 \n", - "2 1 5 \n", - "3 1 7 \n", - "4 1 7 \n", - "\n", - " NUM_UNIQUE(covid.YEAR(Date)) _execute_operations_on_df \n", - "0 1 2 \n", - "1 1 2 \n", - "2 1 2 \n", - "3 1 2 \n", - "4 1 2 \n", - "\n", - "[5 rows x 44 columns]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "feature_matrix.reset_index().head(5)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "8db3e8bd", - "metadata": {}, - "outputs": [], - "source": [ - "feature_matrix_encoded, features_encoded = ft_wrapper.encode_features(\n", - " feature_matrix, features\n", - ")\n", - "\n", - "y = feature_matrix_encoded[\"_execute_operations_on_df\"]\n", - "feature_matrix_encoded = feature_matrix_encoded.drop(\n", - " columns=[\"_execute_operations_on_df\"]\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.2" - }, - "vscode": { - "interpreter": { - "hash": "8207ecde8cf2fda520169a8f8360958470b9168fa3b5c7074fdec936472ea246" - } - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/Yelp - End to End.ipynb b/docs/Yelp - End to End.ipynb deleted file mode 100644 index 13dc8ed9..00000000 --- a/docs/Yelp - End to End.ipynb +++ /dev/null @@ -1,372 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "dc7985c7", - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import trane\n", - "from trane.utils import infer_types" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "62e42721", - "metadata": {}, - "outputs": [], - "source": [ - "pd.set_option(\"display.max_columns\", 500)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "affcfe33", - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_parquet(\"./yelp.parquet\")\n", - "df = infer_types(df)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "baac241b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of Rows: 50000\n" - ] - } - ], - "source": [ - "print(f\"Number of Rows: {df.shape[0]}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "3cc953d7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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review_iduser_idbusiness_idstarsuseful_reviewfunny_reviewcool_reviewtextdatenamereview_countyelping_sinceuseful_userfunny_usercool_userelitefriendsfansaverage_starscompliment_hotcompliment_morecompliment_profilecompliment_cutecompliment_listcompliment_notecompliment_plaincompliment_coolcompliment_funnycompliment_writercompliment_photosname_businessaddresscitystatepostal_codelatitudelongitudestars_businessreview_count_businessis_open
0KU_O5udG6zpxOg-VcAEodgmh_-eMZ6K5RLWhZyISBhwAXQfwVwDr-v0ZS3_CbbE5Xw3000If you decide to eat here, just be aware it is...2018-07-07 22:09:11Melanie332016-01-13 17:20:443238DS9QBM_NWJz1E279Zrao-A, XdXgIs4i5JFvtJf0rJlWsA...04.0600000001100Turning Point of North Wales1460 Bethlehem PikeNorth WalesPA1945440.210196-75.2236393.01691
1VJxlBnJmCDIy8DFG0kjSowIaee7y6zdSB3B-kRCo4z1wXQfwVwDr-v0ZS3_CbbE5Xw2000This is the second time we tried turning point...2017-05-13 17:06:55John92015-12-07 14:46:53311None02.8900000000000Turning Point of North Wales1460 Bethlehem PikeNorth WalesPA1945440.210196-75.2236393.01691
2S6pQZQocMB1WHMjTRbt77AejFxLGqQcWNLdNByJlIhnQXQfwVwDr-v0ZS3_CbbE5Xw4201The place is cute and the staff was very frien...2017-08-08 00:58:18Stella1562010-07-19 00:49:061323473SOyhBc3XZVXGiV_2D59BjQ, QroLivYxf3ij7Llio6L24g...83.7310000110014Turning Point of North Wales1460 Bethlehem PikeNorth WalesPA1945440.210196-75.2236393.01691
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XdXgIs4i5JFvtJf0rJlWsA... 0 \n", - "1 1 None 0 \n", - "2 73 SOyhBc3XZVXGiV_2D59BjQ, QroLivYxf3ij7Llio6L24g... 8 \n", - "\n", - " average_stars compliment_hot compliment_more compliment_profile \\\n", - "0 4.06 0 0 0 \n", - "1 2.89 0 0 0 \n", - "2 3.73 1 0 0 \n", - "\n", - " compliment_cute compliment_list compliment_note compliment_plain \\\n", - "0 0 0 0 0 \n", - "1 0 0 0 0 \n", - "2 0 0 1 1 \n", - "\n", - " compliment_cool compliment_funny compliment_writer compliment_photos \\\n", - "0 1 1 0 0 \n", - "1 0 0 0 0 \n", - "2 0 0 1 4 \n", - "\n", - " name_business address city state \\\n", - "0 Turning Point of North Wales 1460 Bethlehem Pike North Wales PA \n", - "1 Turning Point of North Wales 1460 Bethlehem Pike North Wales PA \n", - "2 Turning Point of North Wales 1460 Bethlehem Pike North Wales PA \n", - "\n", - " postal_code latitude longitude stars_business review_count_business \\\n", - "0 19454 40.210196 -75.223639 3.0 169 \n", - "1 19454 40.210196 -75.223639 3.0 169 \n", - "2 19454 40.210196 -75.223639 3.0 169 \n", - "\n", - " is_open \n", - "0 1 \n", - "1 1 \n", - "2 1 " - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.head(3)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "f41c04f6", - "metadata": {}, - "outputs": [], - "source": [ - "entity_col = \"user_id\"\n", - "window_size = \"2d\"\n", - "minimum_data = \"2020-01-22\"\n", - "maximum_data = \"2020-03-29\"\n", - "cutoff_strategy = trane.CutoffStrategy(\n", - " entity_col=entity_col,\n", - " window_size=window_size,\n", - " minimum_data=minimum_data,\n", - " maximum_data=maximum_data,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9116e0d8", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.2" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/changelog.md b/docs/changelog.md index 52bbcd39..a193bdfa 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -12,7 +12,7 @@ What’s new in 0.3.0 (February, 24, 2023) * Fixes * Update to use new compose argument [#56][#56] * Remove py from requirements [#56][#56] - * Remove TableMeta class and replace with ColumnSchema [#83][#83] + * Remove TableMeta class and replace with ColumnSchema [#83][#83] [#85][#85] [#56]: [#57]: @@ -20,6 +20,7 @@ What’s new in 0.3.0 (February, 24, 2023) [#60]: [#77]: [#83]: + [#85]: What’s new in 0.2.0 (January 5, 2023) ===================================== diff --git a/tests/ops/test_aggregation_ops.py b/tests/ops/test_aggregation_ops.py index 35d58497..5dcfa746 100755 --- a/tests/ops/test_aggregation_ops.py +++ b/tests/ops/test_aggregation_ops.py @@ -1,11 +1,11 @@ import numpy as np import pandas as pd import pytest -from woodwork.column_schema import ColumnSchema -from woodwork.logical_types import ( + +from trane.column_schema import ColumnSchema +from trane.logical_types import ( Categorical, ) - from trane.ops.aggregation_ops import ( AvgAggregationOp, CountAggregationOp, diff --git a/tests/ops/test_filter_ops.py b/tests/ops/test_filter_ops.py index 21723ee6..698bf01f 100755 --- a/tests/ops/test_filter_ops.py +++ b/tests/ops/test_filter_ops.py @@ -1,7 +1,7 @@ import pandas as pd import pytest -from woodwork.column_schema import ColumnSchema +from trane.column_schema import ColumnSchema from trane.ops.filter_ops import ( AllFilterOp, EqFilterOp, diff --git a/tests/ops/test_op_base.py b/tests/ops/test_op_base.py index f9f97170..fa63534c 100755 --- a/tests/ops/test_op_base.py +++ b/tests/ops/test_op_base.py @@ -1,13 +1,13 @@ import pandas as pd import pytest -from woodwork.column_schema import ColumnSchema -from woodwork.logical_types import ( + +from trane.column_schema import ColumnSchema +from trane.logical_types import ( Boolean, Categorical, Datetime, Double, ) - from trane.ops.op_base import OpBase diff --git a/tests/test_load_functions.py b/tests/test_load_functions.py index 43bef315..ebacd338 100644 --- a/tests/test_load_functions.py +++ b/tests/test_load_functions.py @@ -1,8 +1,4 @@ -from woodwork.column_schema import ColumnSchema -from woodwork.logical_types import ( - Datetime, -) - +from trane.column_schema import ColumnSchema from trane.datasets.load_functions import ( load_bike, load_bike_metadata, @@ -11,6 +7,9 @@ load_youtube, load_youtube_metadata, ) +from trane.logical_types import ( + Datetime, +) def test_load_covid(): diff --git a/tests/test_prediction_problem.py b/tests/test_prediction_problem.py index 90fdda0f..b045ba7b 100644 --- a/tests/test_prediction_problem.py +++ b/tests/test_prediction_problem.py @@ -1,29 +1,26 @@ from datetime import datetime +import composeml as cp import pandas as pd -from woodwork.column_schema import ColumnSchema -from woodwork.logical_types import ( - Categorical, - Datetime, - Double, -) +import pytest import trane -def make_fake_dataset(): +@pytest.fixture() +def make_fake_df(): data = { - "id": [1, 2, 2, 3, 3], + "id": [1, 2, 2, 3, 3, 3], "date": [ datetime(2023, 1, 1), - datetime(2023, 1, 2), - datetime(2023, 1, 2), datetime(2023, 1, 3), datetime(2023, 1, 4), + datetime(2023, 1, 3), + datetime(2023, 1, 4), + datetime(2023, 1, 5), ], - "state": ["CA", "CA", "CA", "NY", "NY"], - "country": ["US", "US", "US", "UK", "UK"], - "amount": [10, 20, 30, 40, 50], + "state": ["MA", "NY", "NY", "NJ", "NJ", "CT"], + "amount": [10, 20, 30, 40, 50, 60], } df = pd.DataFrame(data) df["date"] = pd.to_datetime(df["date"]) @@ -31,38 +28,393 @@ def make_fake_dataset(): return df +@pytest.fixture() def make_fake_meta(): meta = { - "id": ColumnSchema(logical_type=Categorical, semantic_tags={"index"}), - "date": ColumnSchema(logical_type=Datetime), - "amount": ColumnSchema(logical_type=Double, semantic_tags={"numeric"}), + "id": ("Categorical", {"index", "category"}), + "date": ("Datetime", {}), + "state": ("Categorical", {"category"}), + "amount": ("Double", {"numeric"}), } + + # "id": ColumnSchema( + # logical_type=Categorical, + # semantic_tags={"index", "category"}, + # ), + # "date": ColumnSchema(logical_type=Datetime), + # "country": ColumnSchema(logical_type=Categorical, semantic_tags={"category"}), + # "amount": ColumnSchema(logical_type=Double, semantic_tags={"numeric"}), + # } return meta -def test_prediction_problem(): - df = make_fake_dataset() +def num_observations(data_slice, **kwargs): + return len(data_slice) + + +def column_gt_len(data_slice, column, value, **kwargs): + return len(data_slice[data_slice[column] > value]) + + +def column_lt_len(data_slice, column, value, **kwargs): + return len(data_slice[data_slice[column] < value]) + + +def column_gt_op(data_slice, column, value, operation="sum", **kwargs): + calculated = data_slice[data_slice[column] > value] + if calculated.empty: + return pd.NA + else: + if operation is None: + return calculated[column].iloc[0] + return getattr(calculated[column], operation)() + + +def column_lt_op(data_slice, column, value, operation="sum", **kwargs): + calculated = data_slice[data_slice[column] < value] + if calculated.empty: + return pd.NA + else: + if operation is None: + return calculated[column].iloc[0] + return getattr(calculated[column], operation)() + + +def sum_column(data_slice, column, **kwargs): + return data_slice[column].sum() + + +def avg_column(data_slice, column, **kwargs): + return data_slice[column].mean() + + +def max_column(data_slice, column, **kwargs): + return data_slice[column].max() + + +def min_column(data_slice, column, **kwargs): + return data_slice[column].min() + + +def test_prediction_problem(make_fake_df, make_fake_meta): + df = make_fake_df + meta = make_fake_meta + for column in df.columns: + assert column in meta entity_col = "id" time_col = "date" - cutoff = "2d" - cutoff_base = "2023-01-01" - cutoff_end = "2023-01-04" + window_size = "2d" + minimum_data = "2023-01-01" + maximum_data = "2023-01-05" cutoff_strategy = trane.CutoffStrategy( entity_col=entity_col, - window_size=cutoff, - minimum_data=cutoff_base, - maximum_data=cutoff_end, + window_size=window_size, + minimum_data=minimum_data, + maximum_data=maximum_data, ) - cutoff = cutoff_strategy.window_size - - meta = make_fake_meta() problem_generator = trane.PredictionProblemGenerator( table_meta=meta, entity_col=entity_col, cutoff_strategy=cutoff_strategy, time_col=time_col, ) + problems = problem_generator.generate(df, generate_thresholds=True) + problems_verified = 0 + # bad integration testing + # not ideal but okay to test for now for p in problems: - # print(p.operations) - print(p) + label_times = p.execute(df, -1) + label_times.rename(columns={"_execute_operations_on_df": "label"}, inplace=True) + threshold = p.operations[0].hyper_parameter_settings.get("threshold", None) + + if str(p) == "For each predict the number of records in next 2d days": + assert label_times["label"].tolist() == [1, 2, 2, 1] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=num_observations, + operation=None, + ) + problems_verified += 1 + elif "For each predict the number of records with " in str(p): + is_greater_than = False + if "greater than" in str(p): + is_greater_than = True + + if is_greater_than and threshold == 40: + assert label_times["label"].tolist() == [0, 0, 1, 1] + elif is_greater_than and threshold == 30: + assert label_times["label"].tolist() == [0, 0, 2, 1] + elif is_greater_than and threshold == 10: + assert label_times["label"].tolist() == [0, 2, 2, 1] + + if not is_greater_than and threshold == 30: + assert label_times["label"].tolist() == [1, 1, 0, 0] + elif not is_greater_than and threshold == 40: + assert label_times["label"].tolist() == [1, 2, 0, 0] + elif not is_greater_than and threshold == 50: + assert label_times["label"].tolist() == [1, 2, 1, 0] + label_function = column_gt_len if is_greater_than else column_lt_len + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=label_function, + operation=None, + ) + problems_verified += 1 + elif ( + "For each predict the total in all related records in next 2d days" + in str(p) + ): + assert label_times["label"].tolist() == [10, 50, 90, 60] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=sum_column, + operation=None, + ) + problems_verified += 1 + elif ( + "For each predict the total in all related records with greater than" + in str(p) + ): + if threshold == 40: + assert label_times["label"].tolist() == [50, 60] + elif threshold == 30: + assert label_times["label"].tolist() == [90, 60] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=column_gt_op, + operation="sum", + ) + problems_verified += 1 + elif ( + "For each predict the total in all related records with less than" + in str(p) + ): + if threshold == 10: + assert label_times["label"].tolist() == [10, 20] + elif threshold == 20: + assert label_times["label"].tolist() == [10, 20] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=column_lt_op, + operation="sum", + ) + problems_verified += 1 + elif ( + "For each predict the average in all related records in next 2d days" + in str(p) + ): + assert label_times["label"].tolist() == [10.0, 25.0, 45.0, 60.0] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=avg_column, + operation=None, + ) + problems_verified += 1 + elif ( + "For each predict the average in all related records with greater than" + in str(p) + ): + if threshold == 40: + assert label_times["label"].tolist() == [50.0, 60.0] + elif threshold == 30: + assert label_times["label"].tolist() == [45.0, 60.0] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=column_gt_op, + operation="mean", + ) + problems_verified += 1 + elif ( + "For each predict the average in all related records with less than" + in str(p) + ): + if threshold == 30: + assert label_times["label"].tolist() == [10.0, 20.0] + elif threshold == 40: + assert label_times["label"].tolist() == [10.0, 25.0] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=column_lt_op, + operation="mean", + ) + problems_verified += 1 + elif ( + "For each predict the maximum in all related records in next 2d days" + in str(p) + ): + assert label_times["label"].tolist() == [10.0, 30.0, 50.0, 60.0] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=max_column, + operation="max", + ) + problems_verified += 1 + elif ( + "For each predict the maximum in all related records with greater than" + in str(p) + ): + if threshold in [30, 40]: + assert label_times["label"].tolist() == [50, 60] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=column_gt_op, + operation="max", + ) + problems_verified += 1 + elif ( + "For each predict the maximum in all related records with less than" + in str(p) + ): + if threshold in [10, 20]: + assert label_times["label"].tolist() == [10, 20] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=column_lt_op, + operation="max", + ) + problems_verified += 1 + elif ( + "For each predict the minimum in all related records in next 2d days" + in str(p) + ): + assert label_times["label"].tolist() == [10, 20, 40, 60] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=min_column, + operation="min", + ) + problems_verified += 1 + elif ( + "For each predict the minimum in all related records with greater than" + in str(p) + ): + if threshold == 40: + assert label_times["label"].tolist() == [50, 60] + elif threshold == 30: + assert label_times["label"].tolist() == [40, 60] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=column_gt_op, + operation="min", + ) + problems_verified += 1 + elif ( + "For each predict the minimum in all related records with less than" + in str(p) + ): + if threshold in [30, 40]: + assert label_times["label"].tolist() == [10, 20] + verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function=column_lt_op, + operation="min", + ) + problems_verified += 1 + assert problems_verified >= 35 + + +def verify_label_times( + cutoff_strategy, + df, + p, + label_times, + function, + operation, + column="amount", +): + threshold = p.operations[0].hyper_parameter_settings.get("threshold", None) + + window_size = cutoff_strategy.window_size + minimum_data = cutoff_strategy.minimum_data + maximum_data = cutoff_strategy.maximum_data + + expected_label_times = generate_label_times( + function, + df, + minimum_data, + maximum_data, + window_size, + value=threshold, + column=column, + operation=operation, + ) + pd.testing.assert_frame_equal( + expected_label_times, + label_times, + check_frame_type=False, + ) + + +def generate_label_times( + labeling_function, + df, + minimum_data, + maximum_data, + window_size, + column=None, + value=None, + operation="sum", + label_column_name="label", +): + lm = cp.LabelMaker( + target_dataframe_index="id", + labeling_function=labeling_function, + time_index="date", + window_size=window_size, + ) + lt = lm.search( + df=df, + column=column, + value=value, + operation=operation, + num_examples_per_instance=-1, + minimum_data=minimum_data, + maximum_data=maximum_data, + verbose=False, + ) + # rename the third column to label + lt.rename(columns={lt.columns[2]: label_column_name}, inplace=True) + return lt diff --git a/tests/test_table_meta.py b/tests/test_table_meta.py new file mode 100644 index 00000000..fec0cb51 --- /dev/null +++ b/tests/test_table_meta.py @@ -0,0 +1,31 @@ +from trane.column_schema import ColumnSchema +from trane.core.prediction_problem import _parse_table_meta +from trane.logical_types import ( + Categorical, + Datetime, + Double, +) + + +def test_parse_table_meta(): + meta = { + "id": ("Categorical", {"index", "category"}), + "date": "Datetime", + "cost": ("Double", {"numeric"}), + "amount": (None, {"numeric"}), + } + parsed_meta = _parse_table_meta(meta) + assert parsed_meta["id"] == ColumnSchema( + logical_type=Categorical, + semantic_tags={"index", "category"}, + ) + assert parsed_meta["date"] == ColumnSchema(logical_type=Datetime, semantic_tags={}) + assert parsed_meta["cost"] == ColumnSchema( + logical_type=Double, + semantic_tags={"numeric"}, + ) + assert parsed_meta["amount"] == ColumnSchema( + logical_type=None, + semantic_tags={"numeric"}, + ) + assert len(parsed_meta) == 4 diff --git a/trane/__init__.py b/trane/__init__.py index 73bf8092..b755bf22 100755 --- a/trane/__init__.py +++ b/trane/__init__.py @@ -7,6 +7,8 @@ load_youtube_metadata, load_yelp, ) +from trane.column_schema import ColumnSchema +from trane.logical_types import * from trane.utils import * # noqa from trane.version import __version__ diff --git a/trane/column_schema.py b/trane/column_schema.py new file mode 100644 index 00000000..08fc661d --- /dev/null +++ b/trane/column_schema.py @@ -0,0 +1,75 @@ +from inspect import isclass + +from trane.logical_types import Boolean, Datetime, Ordinal + + +class ColumnSchema(object): + def __init__( + self, + logical_type=None, + semantic_tags=None, + ): + """Create ColumnSchema + Args: + logical_type (LogicalType, optional): The column's LogicalType. + semantic_tags (str, list, set, optional): The semantic tag(s) specified for the column. + """ + if isclass(logical_type): + self.logical_type = logical_type() + semantic_tags = self._parse_column_tags(semantic_tags) + self.logical_type = logical_type + self.semantic_tags = semantic_tags + + def __eq__(self, other, deep=True): + if self.logical_type != other.logical_type: + return False + if self.semantic_tags != other.semantic_tags: + return False + return True + + def __repr__(self): + msg = " predict the total in all related records with greater than" in str(self) and "in next" in str(self): - # breakpoint() if temp_meta is None: return False diff --git a/trane/core/prediction_problem_generator.py b/trane/core/prediction_problem_generator.py index ffb84486..bb4609ea 100755 --- a/trane/core/prediction_problem_generator.py +++ b/trane/core/prediction_problem_generator.py @@ -4,14 +4,15 @@ import random from tqdm.notebook import tqdm -from woodwork.column_schema import ColumnSchema -from woodwork.logical_types import ( + +from trane.column_schema import ColumnSchema +from trane.core.prediction_problem import PredictionProblem +from trane.core.utils import _parse_table_meta +from trane.logical_types import ( Categorical, Datetime, Integer, ) - -from trane.core.prediction_problem import PredictionProblem from trane.ops import aggregation_ops as agg_ops from trane.ops import filter_ops @@ -37,7 +38,7 @@ def __init__(self, table_meta, entity_col, time_col, cutoff_strategy=None): ------- None """ - self.table_meta = table_meta + self.table_meta = _parse_table_meta(table_meta) self.entity_col = entity_col self.time_col = time_col self.cutoff_strategy = cutoff_strategy @@ -181,11 +182,11 @@ def ensure_valid_inputs(self): assert isinstance(col_type, ColumnSchema) entity_col_type = self.table_meta[self.entity_col] - assert entity_col_type.logical_type in [Integer(), Categorical()] + assert entity_col_type.logical_type in [Integer, Categorical] assert "index" in entity_col_type.semantic_tags time_col_type = self.table_meta[self.time_col] - assert time_col_type.logical_type == Datetime() + assert time_col_type.logical_type == Datetime def _threshold_recommend(self, filter_op, df, keep_rates=[0.25, 0.5, 0.75]): yielded_thresholds = [] diff --git a/trane/core/utils.py b/trane/core/utils.py new file mode 100644 index 00000000..3cb49d63 --- /dev/null +++ b/trane/core/utils.py @@ -0,0 +1,28 @@ +from trane.column_schema import ColumnSchema +from trane.logical_types import ALL_LOGICAL_TYPES + + +def _parse_table_meta(table_meta): + str_to_logical_type = {ltype.__name__.lower(): ltype for ltype in ALL_LOGICAL_TYPES} + parsed_schema = {} + for col, schema in table_meta.items(): + if isinstance(schema, str): + parsed_schema[col] = ColumnSchema( + logical_type=str_to_logical_type[schema.lower()], + ) + elif isinstance(schema, tuple): + logical_type = None + semantic_tags = None + if schema[0]: + logical_type = str_to_logical_type[schema[0].lower()] + if schema[1]: + semantic_tags = schema[1] + parsed_schema[col] = ColumnSchema( + logical_type=logical_type, + semantic_tags=semantic_tags, + ) + elif isinstance(schema, ColumnSchema): + parsed_schema[col] = schema + else: + raise TypeError(f"Invalid schema type for column '{col}'") + return parsed_schema diff --git a/trane/datasets/load_functions.py b/trane/datasets/load_functions.py index 826e78bc..8d1f6aa2 100644 --- a/trane/datasets/load_functions.py +++ b/trane/datasets/load_functions.py @@ -1,8 +1,9 @@ import os import pandas as pd -from woodwork.column_schema import ColumnSchema -from woodwork.logical_types import ( + +from trane.column_schema import ColumnSchema +from trane.logical_types import ( Categorical, Datetime, Double, diff --git a/trane/logical_types.py b/trane/logical_types.py new file mode 100644 index 00000000..93b56672 --- /dev/null +++ b/trane/logical_types.py @@ -0,0 +1,49 @@ +class LogicalTypeMetaClass(type): + def __repr__(cls): + return cls.__name__ + + +class LogicalType(object, metaclass=LogicalTypeMetaClass): + def __eq__(self, other, deep=False): + return isinstance(other, self.__class__) + + def __str__(self): + return str(self.__class__) + + +class Boolean(LogicalType): + pass + + +class Categorical(LogicalType): + pass + + +class Datetime(LogicalType): + pass + + +class Double(LogicalType): + pass + + +class Integer(LogicalType): + pass + + +class Ordinal(LogicalType): + pass + + +class PostalCode(LogicalType): + pass + + +ALL_LOGICAL_TYPES = [ + Boolean, + Categorical, + Datetime, + Double, + Integer, + Ordinal, +] diff --git a/trane/ops/aggregation_ops.py b/trane/ops/aggregation_ops.py index 77eb596b..08593552 100755 --- a/trane/ops/aggregation_ops.py +++ b/trane/ops/aggregation_ops.py @@ -1,6 +1,5 @@ -from woodwork.column_schema import ColumnSchema -from woodwork.logical_types import Categorical, Double, Integer, Ordinal, PostalCode - +from trane.column_schema import ColumnSchema +from trane.logical_types import Double, Integer from trane.ops.op_base import OpBase AGGREGATION_OPS = [ @@ -81,11 +80,8 @@ def __init__(self, column_name): self.hyper_parameter_settings = {} def op_type_check(self, table_meta): - if "numeric" not in table_meta[self.column_name].semantic_tags: - return None - if not isinstance(table_meta[self.column_name].logical_type, (Integer, Double)): - return None - return table_meta + if table_meta[self.column_name].is_numeric: + return table_meta def execute(self, dataframe): if len(dataframe) == 0: @@ -109,11 +105,8 @@ def __init__(self, column_name): self.hyper_parameter_settings = {} def op_type_check(self, table_meta): - if "numeric" not in table_meta[self.column_name].semantic_tags: - return None - if not isinstance(table_meta[self.column_name].logical_type, (Integer, Double)): - return None - return table_meta + if table_meta[self.column_name].is_numeric: + return table_meta def execute(self, dataframe): if len(dataframe) == 0: @@ -137,11 +130,8 @@ def __init__(self, column_name): self.hyper_parameter_settings = {} def op_type_check(self, table_meta): - if "numeric" not in table_meta[self.column_name].semantic_tags: - return None - if not isinstance(table_meta[self.column_name].logical_type, (Integer, Double)): - return None - return table_meta + if table_meta[self.column_name].is_numeric: + return table_meta def execute(self, dataframe): if len(dataframe) == 0: @@ -165,11 +155,8 @@ def __init__(self, column_name): self.hyper_parameter_settings = {} def op_type_check(self, table_meta): - if "numeric" not in table_meta[self.column_name].semantic_tags: - return None - if not isinstance(table_meta[self.column_name].logical_type, (Integer, Double)): - return None - return table_meta + if table_meta[self.column_name].is_numeric: + return table_meta def execute(self, dataframe): if len(dataframe) == 0: @@ -192,32 +179,18 @@ class MajorityAggregationOp(AggregationOpBase): def __init__(self, column_name): self.column_name = column_name - self.input_type = ColumnSchema(semantic_tags={"category"}) + # self.input_type = ColumnSchema(semantic_tags={"category"}) # doesn't seem right # self.output_type = ColumnSchema(logical_type=Double, semantic_tags={"numeric"}) self.hyper_parameter_settings = {} def op_type_check(self, table_meta): - semantic_tags = table_meta[self.column_name].semantic_tags - if "index" not in semantic_tags or "category" not in semantic_tags: - return None - if not isinstance( - table_meta[self.column_name].logical_type, - (Integer, Categorical, Ordinal, PostalCode), - ): - return None - - if "numeric" in semantic_tags: - self.output_type = ColumnSchema( - logical_type=table_meta[self.column_name].logical_type, - semantic_tags={"numeric"}, - ) - if "category" in semantic_tags: + if table_meta[self.column_name].is_categorical: self.output_type = ColumnSchema( logical_type=table_meta[self.column_name].logical_type, semantic_tags={"category"}, ) - return table_meta + return table_meta def execute(self, dataframe): if len(dataframe) == 0: diff --git a/trane/ops/filter_ops.py b/trane/ops/filter_ops.py index 9bdc2975..ee786e60 100755 --- a/trane/ops/filter_ops.py +++ b/trane/ops/filter_ops.py @@ -1,12 +1,11 @@ -from woodwork.column_schema import ColumnSchema -from woodwork.logical_types import ( +from trane.column_schema import ColumnSchema +from trane.logical_types import ( Categorical, Double, Integer, Ordinal, PostalCode, ) - from trane.ops.op_base import OpBase FILTER_OPS = [ @@ -28,11 +27,6 @@ class FilterOpBase(OpBase): operations are defined as classes that inherit the FilterOpBase class and instantiate the execute method. - Make Your Own - ------------- - Simply make a new class that follows the requirements below and issue a - pull request. - Requirements ------------ REQUIRED_PARAMETERS: the hyper parameters needed for the operation @@ -75,7 +69,7 @@ class EqFilterOp(FilterOpBase): def __init__(self, column_name): self.column_name = column_name self.input_type = [ - ColumnSchema(semantic_tags={"index"}), + ColumnSchema(semantic_tags={"category"}), ColumnSchema(semantic_tags={"category"}), ] # doesn't seem right @@ -127,7 +121,7 @@ class NeqFilterOp(FilterOpBase): def __init__(self, column_name): self.column_name = column_name self.input_type = [ - ColumnSchema(semantic_tags={"index"}), + ColumnSchema(semantic_tags={"category"}), ColumnSchema(semantic_tags={"category"}), ] # doesn't seem right