wrangle_act.ipynb

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   "source": [
    "<h1>Project: Wrangling and Analyze Data</h1>\n",
    "<a id='intro'></a>\n",
    "<h2>Introduction</h2>\n",
    "\n",
    "This report delves into the analysis of WeRateDogs Twitter datasets to uncover the insights behind how twitter users rate people’s dogs and the humorous comment they tweet about the god. \n",
    "\n",
    "The objective of the study is to understand the behavior of dog owners and their followers on Twitter, especially in terms of what drives their favorite and retweet counts. By using three datasets: twitter_archive_enhanced.csv, image_prediction.tsv, and tweet_json.txt, the report emphasizes the findings obtained after a comprehensive process of data wrangling and cleaning. \n",
    "\n",
    "The findings provide valuable information for those lacking the knowledge of what the audience likes and how to effectively run a social media account for their dogs.\n",
    "\n",
    "<h2>About WeRateDogs</h2>\n",
    "\n",
    "<a href=\"https://twitter.com/dog_rates\">WeRateDogs</a> is a Twitter account that rates people's dogs with a humorous comment about the dog. The account was started in 2015 by college student Matt Nelson, and has received international media attention both for its popularity and for the attention drawn to social media.\n",
    "\n",
    "<h2>Table of Contents</h2>\n",
    "<ul>\n",
    "    <li><a href=\"#intro\">Introduction</a></li>\n",
    "    <li><a href=\"#datagathering\">Data Gathering</a></li>\n",
    "    <li><a href=\"#assessingdata\">Assessing Data</a></li>\n",
    "    <li><a href=\"#cleaningdata\">Cleaning Data</a></li>\n",
    "    <li><a href=\"#storingdata\">Storing Data</a></li>\n",
    "    <li><a href=\"#analyzingandvisualizing\">Analyzing and Visualizing Data</a></li>\n",
    "    <li><a href=\"#conclusion\">Conclusion</a></li>\n",
    "</ul>\n"
   ]
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  {
   "cell_type": "code",
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   "source": [
    "# Import packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import json\n",
    "import os\n",
    "from timeit import default_timer as timer\n",
    "import tweepy\n",
    "from tweepy import OAuthHandler\n",
    "from requests import get\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "%matplotlib inline"
   ]
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  {
   "cell_type": "markdown",
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   "source": [
    "<a id=\"datagathering\"></a>\n",
    "<h2>Data Gathering</h2>\n",
    "\n",
    "In the cell below, gather **all** three pieces of data for this project and load them in the notebook. **Note:** the methods required to gather each data are different.\n",
    "1. Directly download the WeRateDogs Twitter archive data (twitter_archive_enhanced.csv)"
   ]
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   "source": [
    "# Loead \"twitter-archive-enhanced.csv\"\n",
    "df_1 = pd.read_csv(\"twitter-archive-enhanced.csv\")"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Use the Requests library to download the tweet image prediction (image_predictions.tsv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://d17h27t6h515a5.cloudfront.net/topher/2017/August/599fd2ad_image-predictions/image-predictions.tsv\"\n",
    "response = get(url)\n",
    "\n",
    "with open(\"image_predictions.tsv\", mode='wb') as file:\n",
    "    file.write(response.content)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Use the Tweepy library to query additional data via the Twitter API (tweet_json.txt)"
   ]
  },
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   "source": [
    "# Authenticate with Twitter OAuth\n",
    "consumer_key = \"HIDDEN\"\n",
    "consumer_secret = \"HIDDEN\"\n",
    "access_token = \"HIDDEN\"\n",
    "access_secret = \"HIDDEN\"\n",
    "\n",
    "# Authenticate to Twitter API\n",
    "auth = tweepy.OAuthHandler(consumer_key, consumer_secret)\n",
    "auth.set_access_token(access_token, access_secret)\n",
    "\n",
    "# Create API object\n",
    "api = tweepy.API(auth, wait_on_rate_limit = True)\n",
    "\n",
    "# Load the list of tweet IDs from the Twitter archive\n",
    "tweet_ids = df_1.tweet_id.values\n",
    "len(tweet_ids)\n",
    "\n",
    "# Query Twitter API for JASON data for each tweet ID in the Twitter archive \n",
    "count = 0\n",
    "fails_dict = {}\n",
    "start = timer()\n",
    "# Save each tweet returned JASON as a new line in a .text file\n",
    "with open(\"tweet_json.txt\", \"w\") as outfile:\n",
    "    for tweet_id in tweet_ids:\n",
    "        count +=1\n",
    "        print(str(count) + \": \" + str(tweet_id))\n",
    "        try:\n",
    "            tweet = api.get_status(tweet_id, tweet_mode = \"extended\")\n",
    "            print(\"success\")\n",
    "            json.dump(tweet._json, outfile)\n",
    "            outfile.write(\"\\n\")\n",
    "        except tweepy.TweepError as e:\n",
    "            print(\"Fail\")\n",
    "            fails_dict[tweet_id] = e\n",
    "            pass\n",
    "end = timer()\n",
    "print(end - start)\n",
    "print(fails_dict)"
   ]
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   "source": [
    "<a id=\"assessingdata\"></a>\n",
    "<h2>Assessing Data</h2>\n",
    "\n",
    "In this section, detect and document at least **eight (8) quality issues and two (2) tidiness issue**. You must use **both** visual assessment\n",
    "programmatic assessement to assess the data.\n",
    "\n",
    "**Note:** pay attention to the following key points when you access the data.\n",
    "\n",
    "* You only want original ratings (no retweets) that have images. Though there are 5000+ tweets in the dataset, not all are dog ratings and some are retweets.\n",
    "* Assessing and cleaning the entire dataset completely would require a lot of time, and is not necessary to practice and demonstrate your skills in data wrangling. Therefore, the requirements of this project are only to assess and clean at least 8 quality issues and at least 2 tidiness issues in this dataset.\n",
    "* The fact that the rating numerators are greater than the denominators does not need to be cleaned. This [unique rating system](http://knowyourmeme.com/memes/theyre-good-dogs-brent) is a big part of the popularity of WeRateDogs.\n",
    "* You do not need to gather the tweets beyond August 1st, 2017. You can, but note that you won't be able to gather the image predictions for these tweets since you don't have access to the algorithm used.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Load dataframes\n",
    "df_2 = pd.read_csv(\"image_predictions.tsv\", delimiter='\\t')\n",
    "df_3 = pd.read_json(\"tweet_json.txt\", lines = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2356, 17)"
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     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Check the shape of df_1\n",
    "df_1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "(2075, 12)"
      ]
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "# Check the shape of df_2\n",
    "df_2.shape"
   ]
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  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "(2326, 32)"
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     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the shape of df_3\n",
    "df_3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
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   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Archie</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Darla</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>891087950875897856</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 00:08:17 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a majestic great white breaching ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891087950...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>890971913173991426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-28 16:27:12 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Meet Jax. He enjoys ice cream so much he gets ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://gofundme.com/ydvmve-surgery-for-jax,ht...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Jax</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>890729181411237888</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-28 00:22:40 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>When you watch your owner call another dog a g...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890729181...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>890609185150312448</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-27 16:25:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Zoey. She doesn't want to be one of th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890609185...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Zoey</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>890240255349198849</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-26 15:59:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Cassie. She is a college pup. Studying...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890240255...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>Cassie</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>890006608113172480</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-26 00:31:25 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Koda. He is a South Australian decksha...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890006608...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Koda</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>889880896479866881</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 16:11:53 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Bruno. He is a service shark. Only get...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889880896...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Bruno</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>889665388333682689</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 01:55:32 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here's a puppo that seems to be on the fence a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889665388...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>puppo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>889638837579907072</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 00:10:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Ted. He does his best. Sometimes that'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889638837...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Ted</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>889531135344209921</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-24 17:02:04 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Stuart. He's sporting his favorite fan...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889531135...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Stuart</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>puppo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>889278841981685760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-24 00:19:32 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Oliver. You're witnessing one of his m...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889278841...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Oliver</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>888917238123831296</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-23 00:22:39 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Jim. He found a fren. Taught him how t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/888917238...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Jim</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>888804989199671297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-22 16:56:37 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Zeke. He has a new stick. Very proud o...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/888804989...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Zeke</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>888554962724278272</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-22 00:23:06 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Ralphus. He's powering up. Attempting ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/888554962...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Ralphus</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>888202515573088257</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-21 01:02:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: This is Canela. She attempted s...</td>\n",
       "      <td>8.874740e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2017-07-19 00:47:34 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887473957...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Canela</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>888078434458587136</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-20 16:49:33 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Gerald. He was just told he didn't get...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/888078434...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Gerald</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>887705289381826560</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 16:06:48 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Jeffrey. He has a monopoly on the pool...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887705289...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Jeffrey</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>887517139158093824</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 03:39:09 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>I've yet to rate a Venezuelan Hover Wiener. Th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887517139...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>such</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>887473957103951883</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 00:47:34 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Canela. She attempted some fancy porch...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887473957...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Canela</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>887343217045368832</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-18 16:08:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>You may not have known you needed to see this ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887343217...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>887101392804085760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-18 00:07:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This... is a Jubilant Antarctic House Bear. We...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887101392...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>886983233522544640</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-17 16:17:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Maya. She's very shy. Rarely leaves he...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/886983233...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Maya</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>886736880519319552</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-16 23:58:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Mingus. He's a wonderful father to his...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://www.gofundme.com/mingusneedsus,https:/...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Mingus</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>886680336477933568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-16 20:14:00 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Derek. He's late for a dog meeting. 13...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/886680336...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Derek</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>886366144734445568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-15 23:25:31 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Roscoe. Another pupper fallen victim t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/886366144...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Roscoe</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2326</th>\n",
       "      <td>666411507551481857</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 00:24:19 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is quite the dog. Gets really excited whe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666411507...</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>quite</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2327</th>\n",
       "      <td>666407126856765440</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 00:06:54 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a southern Vesuvius bumblegruff. Can d...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666407126...</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2328</th>\n",
       "      <td>666396247373291520</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 23:23:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Oh goodness. A super rare northeast Qdoba kang...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666396247...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2329</th>\n",
       "      <td>666373753744588802</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 21:54:18 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Those are sunglasses and a jean jacket. 11/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666373753...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2330</th>\n",
       "      <td>666362758909284353</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 21:10:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Unique dog here. Very small. Lives in containe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666362758...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2331</th>\n",
       "      <td>666353288456101888</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 20:32:58 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a mixed Asiago from the Galápagos...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666353288...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2332</th>\n",
       "      <td>666345417576210432</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 20:01:42 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Look at this jokester thinking seat belt laws ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666345417...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2333</th>\n",
       "      <td>666337882303524864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 19:31:45 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is an extremely rare horned Parthenon. No...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666337882...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>an</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2334</th>\n",
       "      <td>666293911632134144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 16:37:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a funny dog. Weird toes. Won't come do...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666293911...</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2335</th>\n",
       "      <td>666287406224695296</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 16:11:11 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is an Albanian 3 1/2 legged  Episcopalian...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666287406...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>an</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2336</th>\n",
       "      <td>666273097616637952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 15:14:19 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Can take selfies 11/10 https://t.co/ws2AMaNwPW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666273097...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2337</th>\n",
       "      <td>666268910803644416</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 14:57:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Very concerned about fellow dog trapped in com...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666268910...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2338</th>\n",
       "      <td>666104133288665088</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 04:02:55 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Not familiar with this breed. No tail (weird)....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666104133...</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2339</th>\n",
       "      <td>666102155909144576</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:55:04 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Oh my. Here you are seeing an Adobe Setter giv...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666102155...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2340</th>\n",
       "      <td>666099513787052032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:44:34 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Can stand on stump for what seems like a while...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666099513...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2341</th>\n",
       "      <td>666094000022159362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:22:39 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This appears to be a Mongolian Presbyterian mi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666094000...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2342</th>\n",
       "      <td>666082916733198337</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 02:38:37 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a well-established sunblockerspan...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666082916...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2343</th>\n",
       "      <td>666073100786774016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:59:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Let's hope this flight isn't Malaysian (lol). ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666073100...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2344</th>\n",
       "      <td>666071193221509120</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:52:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a northern speckled Rhododendron....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666071193...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2345</th>\n",
       "      <td>666063827256086533</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:22:45 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is the happiest dog you will ever see. Ve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666063827...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>the</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2346</th>\n",
       "      <td>666058600524156928</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:01:59 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here is the Rand Paul of retrievers folks! He'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666058600...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>the</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2347</th>\n",
       "      <td>666057090499244032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:55:59 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>My oh my. This is a rare blond Canadian terrie...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666057090...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2348</th>\n",
       "      <td>666055525042405380</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:49:46 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here is a Siberian heavily armored polar bear ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666055525...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2349</th>\n",
       "      <td>666051853826850816</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:35:11 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is an odd dog. Hard on the outside but lo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666051853...</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>an</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2350</th>\n",
       "      <td>666050758794694657</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:30:50 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a truly beautiful English Wilson Staff...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666050758...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2351</th>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:24:50 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a 1949 1st generation vulpix. Enj...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666049248...</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2352</th>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:04:52 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a purebred Piers Morgan. Loves to Netf...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666044226...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2353</th>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 23:21:54 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here is a very happy pup. Big fan of well-main...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666033412...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2354</th>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 23:05:30 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a western brown Mitsubishi terrier. Up...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666029285...</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2355</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 22:32:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a Japanese Irish Setter. Lost eye...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666020888...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2356 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0     892420643555336193                    NaN                  NaN   \n",
       "1     892177421306343426                    NaN                  NaN   \n",
       "2     891815181378084864                    NaN                  NaN   \n",
       "3     891689557279858688                    NaN                  NaN   \n",
       "4     891327558926688256                    NaN                  NaN   \n",
       "5     891087950875897856                    NaN                  NaN   \n",
       "6     890971913173991426                    NaN                  NaN   \n",
       "7     890729181411237888                    NaN                  NaN   \n",
       "8     890609185150312448                    NaN                  NaN   \n",
       "9     890240255349198849                    NaN                  NaN   \n",
       "10    890006608113172480                    NaN                  NaN   \n",
       "11    889880896479866881                    NaN                  NaN   \n",
       "12    889665388333682689                    NaN                  NaN   \n",
       "13    889638837579907072                    NaN                  NaN   \n",
       "14    889531135344209921                    NaN                  NaN   \n",
       "15    889278841981685760                    NaN                  NaN   \n",
       "16    888917238123831296                    NaN                  NaN   \n",
       "17    888804989199671297                    NaN                  NaN   \n",
       "18    888554962724278272                    NaN                  NaN   \n",
       "19    888202515573088257                    NaN                  NaN   \n",
       "20    888078434458587136                    NaN                  NaN   \n",
       "21    887705289381826560                    NaN                  NaN   \n",
       "22    887517139158093824                    NaN                  NaN   \n",
       "23    887473957103951883                    NaN                  NaN   \n",
       "24    887343217045368832                    NaN                  NaN   \n",
       "25    887101392804085760                    NaN                  NaN   \n",
       "26    886983233522544640                    NaN                  NaN   \n",
       "27    886736880519319552                    NaN                  NaN   \n",
       "28    886680336477933568                    NaN                  NaN   \n",
       "29    886366144734445568                    NaN                  NaN   \n",
       "...                  ...                    ...                  ...   \n",
       "2326  666411507551481857                    NaN                  NaN   \n",
       "2327  666407126856765440                    NaN                  NaN   \n",
       "2328  666396247373291520                    NaN                  NaN   \n",
       "2329  666373753744588802                    NaN                  NaN   \n",
       "2330  666362758909284353                    NaN                  NaN   \n",
       "2331  666353288456101888                    NaN                  NaN   \n",
       "2332  666345417576210432                    NaN                  NaN   \n",
       "2333  666337882303524864                    NaN                  NaN   \n",
       "2334  666293911632134144                    NaN                  NaN   \n",
       "2335  666287406224695296                    NaN                  NaN   \n",
       "2336  666273097616637952                    NaN                  NaN   \n",
       "2337  666268910803644416                    NaN                  NaN   \n",
       "2338  666104133288665088                    NaN                  NaN   \n",
       "2339  666102155909144576                    NaN                  NaN   \n",
       "2340  666099513787052032                    NaN                  NaN   \n",
       "2341  666094000022159362                    NaN                  NaN   \n",
       "2342  666082916733198337                    NaN                  NaN   \n",
       "2343  666073100786774016                    NaN                  NaN   \n",
       "2344  666071193221509120                    NaN                  NaN   \n",
       "2345  666063827256086533                    NaN                  NaN   \n",
       "2346  666058600524156928                    NaN                  NaN   \n",
       "2347  666057090499244032                    NaN                  NaN   \n",
       "2348  666055525042405380                    NaN                  NaN   \n",
       "2349  666051853826850816                    NaN                  NaN   \n",
       "2350  666050758794694657                    NaN                  NaN   \n",
       "2351  666049248165822465                    NaN                  NaN   \n",
       "2352  666044226329800704                    NaN                  NaN   \n",
       "2353  666033412701032449                    NaN                  NaN   \n",
       "2354  666029285002620928                    NaN                  NaN   \n",
       "2355  666020888022790149                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "0     2017-08-01 16:23:56 +0000   \n",
       "1     2017-08-01 00:17:27 +0000   \n",
       "2     2017-07-31 00:18:03 +0000   \n",
       "3     2017-07-30 15:58:51 +0000   \n",
       "4     2017-07-29 16:00:24 +0000   \n",
       "5     2017-07-29 00:08:17 +0000   \n",
       "6     2017-07-28 16:27:12 +0000   \n",
       "7     2017-07-28 00:22:40 +0000   \n",
       "8     2017-07-27 16:25:51 +0000   \n",
       "9     2017-07-26 15:59:51 +0000   \n",
       "10    2017-07-26 00:31:25 +0000   \n",
       "11    2017-07-25 16:11:53 +0000   \n",
       "12    2017-07-25 01:55:32 +0000   \n",
       "13    2017-07-25 00:10:02 +0000   \n",
       "14    2017-07-24 17:02:04 +0000   \n",
       "15    2017-07-24 00:19:32 +0000   \n",
       "16    2017-07-23 00:22:39 +0000   \n",
       "17    2017-07-22 16:56:37 +0000   \n",
       "18    2017-07-22 00:23:06 +0000   \n",
       "19    2017-07-21 01:02:36 +0000   \n",
       "20    2017-07-20 16:49:33 +0000   \n",
       "21    2017-07-19 16:06:48 +0000   \n",
       "22    2017-07-19 03:39:09 +0000   \n",
       "23    2017-07-19 00:47:34 +0000   \n",
       "24    2017-07-18 16:08:03 +0000   \n",
       "25    2017-07-18 00:07:08 +0000   \n",
       "26    2017-07-17 16:17:36 +0000   \n",
       "27    2017-07-16 23:58:41 +0000   \n",
       "28    2017-07-16 20:14:00 +0000   \n",
       "29    2017-07-15 23:25:31 +0000   \n",
       "...                         ...   \n",
       "2326  2015-11-17 00:24:19 +0000   \n",
       "2327  2015-11-17 00:06:54 +0000   \n",
       "2328  2015-11-16 23:23:41 +0000   \n",
       "2329  2015-11-16 21:54:18 +0000   \n",
       "2330  2015-11-16 21:10:36 +0000   \n",
       "2331  2015-11-16 20:32:58 +0000   \n",
       "2332  2015-11-16 20:01:42 +0000   \n",
       "2333  2015-11-16 19:31:45 +0000   \n",
       "2334  2015-11-16 16:37:02 +0000   \n",
       "2335  2015-11-16 16:11:11 +0000   \n",
       "2336  2015-11-16 15:14:19 +0000   \n",
       "2337  2015-11-16 14:57:41 +0000   \n",
       "2338  2015-11-16 04:02:55 +0000   \n",
       "2339  2015-11-16 03:55:04 +0000   \n",
       "2340  2015-11-16 03:44:34 +0000   \n",
       "2341  2015-11-16 03:22:39 +0000   \n",
       "2342  2015-11-16 02:38:37 +0000   \n",
       "2343  2015-11-16 01:59:36 +0000   \n",
       "2344  2015-11-16 01:52:02 +0000   \n",
       "2345  2015-11-16 01:22:45 +0000   \n",
       "2346  2015-11-16 01:01:59 +0000   \n",
       "2347  2015-11-16 00:55:59 +0000   \n",
       "2348  2015-11-16 00:49:46 +0000   \n",
       "2349  2015-11-16 00:35:11 +0000   \n",
       "2350  2015-11-16 00:30:50 +0000   \n",
       "2351  2015-11-16 00:24:50 +0000   \n",
       "2352  2015-11-16 00:04:52 +0000   \n",
       "2353  2015-11-15 23:21:54 +0000   \n",
       "2354  2015-11-15 23:05:30 +0000   \n",
       "2355  2015-11-15 22:32:08 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "0     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "5     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "6     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "7     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "8     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "9     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "10    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "11    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "12    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "13    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "14    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "15    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "16    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "17    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "18    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "19    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "20    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "21    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "22    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "23    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "24    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "25    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "26    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "27    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "28    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "29    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "...                                                 ...   \n",
       "2326  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2327  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2328  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2329  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2330  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2331  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2332  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2333  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2334  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2335  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2336  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2337  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2338  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2339  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2340  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2341  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2342  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2343  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2344  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2345  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2346  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2347  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2348  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2349  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2350  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2351  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2352  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2353  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2354  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2355  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "0     This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1     This is Tilly. She's just checking pup on you....                  NaN   \n",
       "2     This is Archie. He is a rare Norwegian Pouncin...                  NaN   \n",
       "3     This is Darla. She commenced a snooze mid meal...                  NaN   \n",
       "4     This is Franklin. He would like you to stop ca...                  NaN   \n",
       "5     Here we have a majestic great white breaching ...                  NaN   \n",
       "6     Meet Jax. He enjoys ice cream so much he gets ...                  NaN   \n",
       "7     When you watch your owner call another dog a g...                  NaN   \n",
       "8     This is Zoey. She doesn't want to be one of th...                  NaN   \n",
       "9     This is Cassie. She is a college pup. Studying...                  NaN   \n",
       "10    This is Koda. He is a South Australian decksha...                  NaN   \n",
       "11    This is Bruno. He is a service shark. Only get...                  NaN   \n",
       "12    Here's a puppo that seems to be on the fence a...                  NaN   \n",
       "13    This is Ted. He does his best. Sometimes that'...                  NaN   \n",
       "14    This is Stuart. He's sporting his favorite fan...                  NaN   \n",
       "15    This is Oliver. You're witnessing one of his m...                  NaN   \n",
       "16    This is Jim. He found a fren. Taught him how t...                  NaN   \n",
       "17    This is Zeke. He has a new stick. Very proud o...                  NaN   \n",
       "18    This is Ralphus. He's powering up. Attempting ...                  NaN   \n",
       "19    RT @dog_rates: This is Canela. She attempted s...         8.874740e+17   \n",
       "20    This is Gerald. He was just told he didn't get...                  NaN   \n",
       "21    This is Jeffrey. He has a monopoly on the pool...                  NaN   \n",
       "22    I've yet to rate a Venezuelan Hover Wiener. Th...                  NaN   \n",
       "23    This is Canela. She attempted some fancy porch...                  NaN   \n",
       "24    You may not have known you needed to see this ...                  NaN   \n",
       "25    This... is a Jubilant Antarctic House Bear. We...                  NaN   \n",
       "26    This is Maya. She's very shy. Rarely leaves he...                  NaN   \n",
       "27    This is Mingus. He's a wonderful father to his...                  NaN   \n",
       "28    This is Derek. He's late for a dog meeting. 13...                  NaN   \n",
       "29    This is Roscoe. Another pupper fallen victim t...                  NaN   \n",
       "...                                                 ...                  ...   \n",
       "2326  This is quite the dog. Gets really excited whe...                  NaN   \n",
       "2327  This is a southern Vesuvius bumblegruff. Can d...                  NaN   \n",
       "2328  Oh goodness. A super rare northeast Qdoba kang...                  NaN   \n",
       "2329  Those are sunglasses and a jean jacket. 11/10 ...                  NaN   \n",
       "2330  Unique dog here. Very small. Lives in containe...                  NaN   \n",
       "2331  Here we have a mixed Asiago from the Galápagos...                  NaN   \n",
       "2332  Look at this jokester thinking seat belt laws ...                  NaN   \n",
       "2333  This is an extremely rare horned Parthenon. No...                  NaN   \n",
       "2334  This is a funny dog. Weird toes. Won't come do...                  NaN   \n",
       "2335  This is an Albanian 3 1/2 legged  Episcopalian...                  NaN   \n",
       "2336     Can take selfies 11/10 https://t.co/ws2AMaNwPW                  NaN   \n",
       "2337  Very concerned about fellow dog trapped in com...                  NaN   \n",
       "2338  Not familiar with this breed. No tail (weird)....                  NaN   \n",
       "2339  Oh my. Here you are seeing an Adobe Setter giv...                  NaN   \n",
       "2340  Can stand on stump for what seems like a while...                  NaN   \n",
       "2341  This appears to be a Mongolian Presbyterian mi...                  NaN   \n",
       "2342  Here we have a well-established sunblockerspan...                  NaN   \n",
       "2343  Let's hope this flight isn't Malaysian (lol). ...                  NaN   \n",
       "2344  Here we have a northern speckled Rhododendron....                  NaN   \n",
       "2345  This is the happiest dog you will ever see. Ve...                  NaN   \n",
       "2346  Here is the Rand Paul of retrievers folks! He'...                  NaN   \n",
       "2347  My oh my. This is a rare blond Canadian terrie...                  NaN   \n",
       "2348  Here is a Siberian heavily armored polar bear ...                  NaN   \n",
       "2349  This is an odd dog. Hard on the outside but lo...                  NaN   \n",
       "2350  This is a truly beautiful English Wilson Staff...                  NaN   \n",
       "2351  Here we have a 1949 1st generation vulpix. Enj...                  NaN   \n",
       "2352  This is a purebred Piers Morgan. Loves to Netf...                  NaN   \n",
       "2353  Here is a very happy pup. Big fan of well-main...                  NaN   \n",
       "2354  This is a western brown Mitsubishi terrier. Up...                  NaN   \n",
       "2355  Here we have a Japanese Irish Setter. Lost eye...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                          NaN                        NaN   \n",
       "1                          NaN                        NaN   \n",
       "2                          NaN                        NaN   \n",
       "3                          NaN                        NaN   \n",
       "4                          NaN                        NaN   \n",
       "5                          NaN                        NaN   \n",
       "6                          NaN                        NaN   \n",
       "7                          NaN                        NaN   \n",
       "8                          NaN                        NaN   \n",
       "9                          NaN                        NaN   \n",
       "10                         NaN                        NaN   \n",
       "11                         NaN                        NaN   \n",
       "12                         NaN                        NaN   \n",
       "13                         NaN                        NaN   \n",
       "14                         NaN                        NaN   \n",
       "15                         NaN                        NaN   \n",
       "16                         NaN                        NaN   \n",
       "17                         NaN                        NaN   \n",
       "18                         NaN                        NaN   \n",
       "19                4.196984e+09  2017-07-19 00:47:34 +0000   \n",
       "20                         NaN                        NaN   \n",
       "21                         NaN                        NaN   \n",
       "22                         NaN                        NaN   \n",
       "23                         NaN                        NaN   \n",
       "24                         NaN                        NaN   \n",
       "25                         NaN                        NaN   \n",
       "26                         NaN                        NaN   \n",
       "27                         NaN                        NaN   \n",
       "28                         NaN                        NaN   \n",
       "29                         NaN                        NaN   \n",
       "...                        ...                        ...   \n",
       "2326                       NaN                        NaN   \n",
       "2327                       NaN                        NaN   \n",
       "2328                       NaN                        NaN   \n",
       "2329                       NaN                        NaN   \n",
       "2330                       NaN                        NaN   \n",
       "2331                       NaN                        NaN   \n",
       "2332                       NaN                        NaN   \n",
       "2333                       NaN                        NaN   \n",
       "2334                       NaN                        NaN   \n",
       "2335                       NaN                        NaN   \n",
       "2336                       NaN                        NaN   \n",
       "2337                       NaN                        NaN   \n",
       "2338                       NaN                        NaN   \n",
       "2339                       NaN                        NaN   \n",
       "2340                       NaN                        NaN   \n",
       "2341                       NaN                        NaN   \n",
       "2342                       NaN                        NaN   \n",
       "2343                       NaN                        NaN   \n",
       "2344                       NaN                        NaN   \n",
       "2345                       NaN                        NaN   \n",
       "2346                       NaN                        NaN   \n",
       "2347                       NaN                        NaN   \n",
       "2348                       NaN                        NaN   \n",
       "2349                       NaN                        NaN   \n",
       "2350                       NaN                        NaN   \n",
       "2351                       NaN                        NaN   \n",
       "2352                       NaN                        NaN   \n",
       "2353                       NaN                        NaN   \n",
       "2354                       NaN                        NaN   \n",
       "2355                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "0     https://twitter.com/dog_rates/status/892420643...                13   \n",
       "1     https://twitter.com/dog_rates/status/892177421...                13   \n",
       "2     https://twitter.com/dog_rates/status/891815181...                12   \n",
       "3     https://twitter.com/dog_rates/status/891689557...                13   \n",
       "4     https://twitter.com/dog_rates/status/891327558...                12   \n",
       "5     https://twitter.com/dog_rates/status/891087950...                13   \n",
       "6     https://gofundme.com/ydvmve-surgery-for-jax,ht...                13   \n",
       "7     https://twitter.com/dog_rates/status/890729181...                13   \n",
       "8     https://twitter.com/dog_rates/status/890609185...                13   \n",
       "9     https://twitter.com/dog_rates/status/890240255...                14   \n",
       "10    https://twitter.com/dog_rates/status/890006608...                13   \n",
       "11    https://twitter.com/dog_rates/status/889880896...                13   \n",
       "12    https://twitter.com/dog_rates/status/889665388...                13   \n",
       "13    https://twitter.com/dog_rates/status/889638837...                12   \n",
       "14    https://twitter.com/dog_rates/status/889531135...                13   \n",
       "15    https://twitter.com/dog_rates/status/889278841...                13   \n",
       "16    https://twitter.com/dog_rates/status/888917238...                12   \n",
       "17    https://twitter.com/dog_rates/status/888804989...                13   \n",
       "18    https://twitter.com/dog_rates/status/888554962...                13   \n",
       "19    https://twitter.com/dog_rates/status/887473957...                13   \n",
       "20    https://twitter.com/dog_rates/status/888078434...                12   \n",
       "21    https://twitter.com/dog_rates/status/887705289...                13   \n",
       "22    https://twitter.com/dog_rates/status/887517139...                14   \n",
       "23    https://twitter.com/dog_rates/status/887473957...                13   \n",
       "24    https://twitter.com/dog_rates/status/887343217...                13   \n",
       "25    https://twitter.com/dog_rates/status/887101392...                12   \n",
       "26    https://twitter.com/dog_rates/status/886983233...                13   \n",
       "27    https://www.gofundme.com/mingusneedsus,https:/...                13   \n",
       "28    https://twitter.com/dog_rates/status/886680336...                13   \n",
       "29    https://twitter.com/dog_rates/status/886366144...                12   \n",
       "...                                                 ...               ...   \n",
       "2326  https://twitter.com/dog_rates/status/666411507...                 2   \n",
       "2327  https://twitter.com/dog_rates/status/666407126...                 7   \n",
       "2328  https://twitter.com/dog_rates/status/666396247...                 9   \n",
       "2329  https://twitter.com/dog_rates/status/666373753...                11   \n",
       "2330  https://twitter.com/dog_rates/status/666362758...                 6   \n",
       "2331  https://twitter.com/dog_rates/status/666353288...                 8   \n",
       "2332  https://twitter.com/dog_rates/status/666345417...                10   \n",
       "2333  https://twitter.com/dog_rates/status/666337882...                 9   \n",
       "2334  https://twitter.com/dog_rates/status/666293911...                 3   \n",
       "2335  https://twitter.com/dog_rates/status/666287406...                 1   \n",
       "2336  https://twitter.com/dog_rates/status/666273097...                11   \n",
       "2337  https://twitter.com/dog_rates/status/666268910...                10   \n",
       "2338  https://twitter.com/dog_rates/status/666104133...                 1   \n",
       "2339  https://twitter.com/dog_rates/status/666102155...                11   \n",
       "2340  https://twitter.com/dog_rates/status/666099513...                 8   \n",
       "2341  https://twitter.com/dog_rates/status/666094000...                 9   \n",
       "2342  https://twitter.com/dog_rates/status/666082916...                 6   \n",
       "2343  https://twitter.com/dog_rates/status/666073100...                10   \n",
       "2344  https://twitter.com/dog_rates/status/666071193...                 9   \n",
       "2345  https://twitter.com/dog_rates/status/666063827...                10   \n",
       "2346  https://twitter.com/dog_rates/status/666058600...                 8   \n",
       "2347  https://twitter.com/dog_rates/status/666057090...                 9   \n",
       "2348  https://twitter.com/dog_rates/status/666055525...                10   \n",
       "2349  https://twitter.com/dog_rates/status/666051853...                 2   \n",
       "2350  https://twitter.com/dog_rates/status/666050758...                10   \n",
       "2351  https://twitter.com/dog_rates/status/666049248...                 5   \n",
       "2352  https://twitter.com/dog_rates/status/666044226...                 6   \n",
       "2353  https://twitter.com/dog_rates/status/666033412...                 9   \n",
       "2354  https://twitter.com/dog_rates/status/666029285...                 7   \n",
       "2355  https://twitter.com/dog_rates/status/666020888...                 8   \n",
       "\n",
       "      rating_denominator      name  doggo floofer  pupper  puppo  \n",
       "0                     10   Phineas   None    None    None   None  \n",
       "1                     10     Tilly   None    None    None   None  \n",
       "2                     10    Archie   None    None    None   None  \n",
       "3                     10     Darla   None    None    None   None  \n",
       "4                     10  Franklin   None    None    None   None  \n",
       "5                     10      None   None    None    None   None  \n",
       "6                     10       Jax   None    None    None   None  \n",
       "7                     10      None   None    None    None   None  \n",
       "8                     10      Zoey   None    None    None   None  \n",
       "9                     10    Cassie  doggo    None    None   None  \n",
       "10                    10      Koda   None    None    None   None  \n",
       "11                    10     Bruno   None    None    None   None  \n",
       "12                    10      None   None    None    None  puppo  \n",
       "13                    10       Ted   None    None    None   None  \n",
       "14                    10    Stuart   None    None    None  puppo  \n",
       "15                    10    Oliver   None    None    None   None  \n",
       "16                    10       Jim   None    None    None   None  \n",
       "17                    10      Zeke   None    None    None   None  \n",
       "18                    10   Ralphus   None    None    None   None  \n",
       "19                    10    Canela   None    None    None   None  \n",
       "20                    10    Gerald   None    None    None   None  \n",
       "21                    10   Jeffrey   None    None    None   None  \n",
       "22                    10      such   None    None    None   None  \n",
       "23                    10    Canela   None    None    None   None  \n",
       "24                    10      None   None    None    None   None  \n",
       "25                    10      None   None    None    None   None  \n",
       "26                    10      Maya   None    None    None   None  \n",
       "27                    10    Mingus   None    None    None   None  \n",
       "28                    10     Derek   None    None    None   None  \n",
       "29                    10    Roscoe   None    None  pupper   None  \n",
       "...                  ...       ...    ...     ...     ...    ...  \n",
       "2326                  10     quite   None    None    None   None  \n",
       "2327                  10         a   None    None    None   None  \n",
       "2328                  10      None   None    None    None   None  \n",
       "2329                  10      None   None    None    None   None  \n",
       "2330                  10      None   None    None    None   None  \n",
       "2331                  10      None   None    None    None   None  \n",
       "2332                  10      None   None    None    None   None  \n",
       "2333                  10        an   None    None    None   None  \n",
       "2334                  10         a   None    None    None   None  \n",
       "2335                   2        an   None    None    None   None  \n",
       "2336                  10      None   None    None    None   None  \n",
       "2337                  10      None   None    None    None   None  \n",
       "2338                  10      None   None    None    None   None  \n",
       "2339                  10      None   None    None    None   None  \n",
       "2340                  10      None   None    None    None   None  \n",
       "2341                  10      None   None    None    None   None  \n",
       "2342                  10      None   None    None    None   None  \n",
       "2343                  10      None   None    None    None   None  \n",
       "2344                  10      None   None    None    None   None  \n",
       "2345                  10       the   None    None    None   None  \n",
       "2346                  10       the   None    None    None   None  \n",
       "2347                  10         a   None    None    None   None  \n",
       "2348                  10         a   None    None    None   None  \n",
       "2349                  10        an   None    None    None   None  \n",
       "2350                  10         a   None    None    None   None  \n",
       "2351                  10      None   None    None    None   None  \n",
       "2352                  10         a   None    None    None   None  \n",
       "2353                  10         a   None    None    None   None  \n",
       "2354                  10         a   None    None    None   None  \n",
       "2355                  10      None   None    None    None   None  \n",
       "\n",
       "[2356 rows x 17 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Output df_1 dataset\n",
    "df_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Welsh_springer_spaniel</td>\n",
       "      <td>0.465074</td>\n",
       "      <td>True</td>\n",
       "      <td>collie</td>\n",
       "      <td>0.156665</td>\n",
       "      <td>True</td>\n",
       "      <td>Shetland_sheepdog</td>\n",
       "      <td>0.061428</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.506826</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.074192</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.072010</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.596461</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.138584</td>\n",
       "      <td>True</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.116197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.408143</td>\n",
       "      <td>True</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.360687</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.222752</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.560311</td>\n",
       "      <td>True</td>\n",
       "      <td>Rottweiler</td>\n",
       "      <td>0.243682</td>\n",
       "      <td>True</td>\n",
       "      <td>Doberman</td>\n",
       "      <td>0.154629</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>666050758794694657</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5Jof1WUAEuVxN.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Bernese_mountain_dog</td>\n",
       "      <td>0.651137</td>\n",
       "      <td>True</td>\n",
       "      <td>English_springer</td>\n",
       "      <td>0.263788</td>\n",
       "      <td>True</td>\n",
       "      <td>Greater_Swiss_Mountain_dog</td>\n",
       "      <td>0.016199</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>666051853826850816</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5KoJ1WoAAJash.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>box_turtle</td>\n",
       "      <td>0.933012</td>\n",
       "      <td>False</td>\n",
       "      <td>mud_turtle</td>\n",
       "      <td>0.045885</td>\n",
       "      <td>False</td>\n",
       "      <td>terrapin</td>\n",
       "      <td>0.017885</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>666055525042405380</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5N9tpXIAAifs1.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>chow</td>\n",
       "      <td>0.692517</td>\n",
       "      <td>True</td>\n",
       "      <td>Tibetan_mastiff</td>\n",
       "      <td>0.058279</td>\n",
       "      <td>True</td>\n",
       "      <td>fur_coat</td>\n",
       "      <td>0.054449</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>666057090499244032</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5PY90WoAAQGLo.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>shopping_cart</td>\n",
       "      <td>0.962465</td>\n",
       "      <td>False</td>\n",
       "      <td>shopping_basket</td>\n",
       "      <td>0.014594</td>\n",
       "      <td>False</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.007959</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>666058600524156928</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5Qw94XAAA_2dP.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>miniature_poodle</td>\n",
       "      <td>0.201493</td>\n",
       "      <td>True</td>\n",
       "      <td>komondor</td>\n",
       "      <td>0.192305</td>\n",
       "      <td>True</td>\n",
       "      <td>soft-coated_wheaten_terrier</td>\n",
       "      <td>0.082086</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>666063827256086533</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5Vg_wXIAAXfnj.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.775930</td>\n",
       "      <td>True</td>\n",
       "      <td>Tibetan_mastiff</td>\n",
       "      <td>0.093718</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.072427</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>666071193221509120</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5cN_3WEAAlOoZ.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Gordon_setter</td>\n",
       "      <td>0.503672</td>\n",
       "      <td>True</td>\n",
       "      <td>Yorkshire_terrier</td>\n",
       "      <td>0.174201</td>\n",
       "      <td>True</td>\n",
       "      <td>Pekinese</td>\n",
       "      <td>0.109454</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>666073100786774016</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5d9DZXAAALcwe.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Walker_hound</td>\n",
       "      <td>0.260857</td>\n",
       "      <td>True</td>\n",
       "      <td>English_foxhound</td>\n",
       "      <td>0.175382</td>\n",
       "      <td>True</td>\n",
       "      <td>Ibizan_hound</td>\n",
       "      <td>0.097471</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>666082916733198337</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5m4VGWEAAtKc8.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>pug</td>\n",
       "      <td>0.489814</td>\n",
       "      <td>True</td>\n",
       "      <td>bull_mastiff</td>\n",
       "      <td>0.404722</td>\n",
       "      <td>True</td>\n",
       "      <td>French_bulldog</td>\n",
       "      <td>0.048960</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>666094000022159362</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5w9gUW4AAsBNN.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.195217</td>\n",
       "      <td>True</td>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.078260</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.075628</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>666099513787052032</td>\n",
       "      <td>https://pbs.twimg.com/media/CT51-JJUEAA6hV8.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Lhasa</td>\n",
       "      <td>0.582330</td>\n",
       "      <td>True</td>\n",
       "      <td>Shih-Tzu</td>\n",
       "      <td>0.166192</td>\n",
       "      <td>True</td>\n",
       "      <td>Dandie_Dinmont</td>\n",
       "      <td>0.089688</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>666102155909144576</td>\n",
       "      <td>https://pbs.twimg.com/media/CT54YGiWUAEZnoK.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>English_setter</td>\n",
       "      <td>0.298617</td>\n",
       "      <td>True</td>\n",
       "      <td>Newfoundland</td>\n",
       "      <td>0.149842</td>\n",
       "      <td>True</td>\n",
       "      <td>borzoi</td>\n",
       "      <td>0.133649</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>666104133288665088</td>\n",
       "      <td>https://pbs.twimg.com/media/CT56LSZWoAAlJj2.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>hen</td>\n",
       "      <td>0.965932</td>\n",
       "      <td>False</td>\n",
       "      <td>cock</td>\n",
       "      <td>0.033919</td>\n",
       "      <td>False</td>\n",
       "      <td>partridge</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>666268910803644416</td>\n",
       "      <td>https://pbs.twimg.com/media/CT8QCd1WEAADXws.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>desktop_computer</td>\n",
       "      <td>0.086502</td>\n",
       "      <td>False</td>\n",
       "      <td>desk</td>\n",
       "      <td>0.085547</td>\n",
       "      <td>False</td>\n",
       "      <td>bookcase</td>\n",
       "      <td>0.079480</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>666273097616637952</td>\n",
       "      <td>https://pbs.twimg.com/media/CT8T1mtUwAA3aqm.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Italian_greyhound</td>\n",
       "      <td>0.176053</td>\n",
       "      <td>True</td>\n",
       "      <td>toy_terrier</td>\n",
       "      <td>0.111884</td>\n",
       "      <td>True</td>\n",
       "      <td>basenji</td>\n",
       "      <td>0.111152</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>666287406224695296</td>\n",
       "      <td>https://pbs.twimg.com/media/CT8g3BpUEAAuFjg.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Maltese_dog</td>\n",
       "      <td>0.857531</td>\n",
       "      <td>True</td>\n",
       "      <td>toy_poodle</td>\n",
       "      <td>0.063064</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_poodle</td>\n",
       "      <td>0.025581</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>666293911632134144</td>\n",
       "      <td>https://pbs.twimg.com/media/CT8mx7KW4AEQu8N.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>three-toed_sloth</td>\n",
       "      <td>0.914671</td>\n",
       "      <td>False</td>\n",
       "      <td>otter</td>\n",
       "      <td>0.015250</td>\n",
       "      <td>False</td>\n",
       "      <td>great_grey_owl</td>\n",
       "      <td>0.013207</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>666337882303524864</td>\n",
       "      <td>https://pbs.twimg.com/media/CT9OwFIWEAMuRje.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>ox</td>\n",
       "      <td>0.416669</td>\n",
       "      <td>False</td>\n",
       "      <td>Newfoundland</td>\n",
       "      <td>0.278407</td>\n",
       "      <td>True</td>\n",
       "      <td>groenendael</td>\n",
       "      <td>0.102643</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>666345417576210432</td>\n",
       "      <td>https://pbs.twimg.com/media/CT9Vn7PWoAA_ZCM.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.858744</td>\n",
       "      <td>True</td>\n",
       "      <td>Chesapeake_Bay_retriever</td>\n",
       "      <td>0.054787</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.014241</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>666353288456101888</td>\n",
       "      <td>https://pbs.twimg.com/media/CT9cx0tUEAAhNN_.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>malamute</td>\n",
       "      <td>0.336874</td>\n",
       "      <td>True</td>\n",
       "      <td>Siberian_husky</td>\n",
       "      <td>0.147655</td>\n",
       "      <td>True</td>\n",
       "      <td>Eskimo_dog</td>\n",
       "      <td>0.093412</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>666362758909284353</td>\n",
       "      <td>https://pbs.twimg.com/media/CT9lXGsUcAAyUFt.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>guinea_pig</td>\n",
       "      <td>0.996496</td>\n",
       "      <td>False</td>\n",
       "      <td>skunk</td>\n",
       "      <td>0.002402</td>\n",
       "      <td>False</td>\n",
       "      <td>hamster</td>\n",
       "      <td>0.000461</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>666373753744588802</td>\n",
       "      <td>https://pbs.twimg.com/media/CT9vZEYWUAAlZ05.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>soft-coated_wheaten_terrier</td>\n",
       "      <td>0.326467</td>\n",
       "      <td>True</td>\n",
       "      <td>Afghan_hound</td>\n",
       "      <td>0.259551</td>\n",
       "      <td>True</td>\n",
       "      <td>briard</td>\n",
       "      <td>0.206803</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>666396247373291520</td>\n",
       "      <td>https://pbs.twimg.com/media/CT-D2ZHWIAA3gK1.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.978108</td>\n",
       "      <td>True</td>\n",
       "      <td>toy_terrier</td>\n",
       "      <td>0.009397</td>\n",
       "      <td>True</td>\n",
       "      <td>papillon</td>\n",
       "      <td>0.004577</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>666407126856765440</td>\n",
       "      <td>https://pbs.twimg.com/media/CT-NvwmW4AAugGZ.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>black-and-tan_coonhound</td>\n",
       "      <td>0.529139</td>\n",
       "      <td>True</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.244220</td>\n",
       "      <td>True</td>\n",
       "      <td>flat-coated_retriever</td>\n",
       "      <td>0.173810</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>666411507551481857</td>\n",
       "      <td>https://pbs.twimg.com/media/CT-RugiWIAELEaq.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>coho</td>\n",
       "      <td>0.404640</td>\n",
       "      <td>False</td>\n",
       "      <td>barracouta</td>\n",
       "      <td>0.271485</td>\n",
       "      <td>False</td>\n",
       "      <td>gar</td>\n",
       "      <td>0.189945</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2045</th>\n",
       "      <td>886366144734445568</td>\n",
       "      <td>https://pbs.twimg.com/media/DE0BTnQUwAApKEH.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>French_bulldog</td>\n",
       "      <td>0.999201</td>\n",
       "      <td>True</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.000361</td>\n",
       "      <td>True</td>\n",
       "      <td>Boston_bull</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2046</th>\n",
       "      <td>886680336477933568</td>\n",
       "      <td>https://pbs.twimg.com/media/DE4fEDzWAAAyHMM.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>convertible</td>\n",
       "      <td>0.738995</td>\n",
       "      <td>False</td>\n",
       "      <td>sports_car</td>\n",
       "      <td>0.139952</td>\n",
       "      <td>False</td>\n",
       "      <td>car_wheel</td>\n",
       "      <td>0.044173</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2047</th>\n",
       "      <td>886736880519319552</td>\n",
       "      <td>https://pbs.twimg.com/media/DE5Se8FXcAAJFx4.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>kuvasz</td>\n",
       "      <td>0.309706</td>\n",
       "      <td>True</td>\n",
       "      <td>Great_Pyrenees</td>\n",
       "      <td>0.186136</td>\n",
       "      <td>True</td>\n",
       "      <td>Dandie_Dinmont</td>\n",
       "      <td>0.086346</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2048</th>\n",
       "      <td>886983233522544640</td>\n",
       "      <td>https://pbs.twimg.com/media/DE8yicJW0AAAvBJ.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.793469</td>\n",
       "      <td>True</td>\n",
       "      <td>toy_terrier</td>\n",
       "      <td>0.143528</td>\n",
       "      <td>True</td>\n",
       "      <td>can_opener</td>\n",
       "      <td>0.032253</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2049</th>\n",
       "      <td>887101392804085760</td>\n",
       "      <td>https://pbs.twimg.com/media/DE-eAq6UwAA-jaE.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Samoyed</td>\n",
       "      <td>0.733942</td>\n",
       "      <td>True</td>\n",
       "      <td>Eskimo_dog</td>\n",
       "      <td>0.035029</td>\n",
       "      <td>True</td>\n",
       "      <td>Staffordshire_bullterrier</td>\n",
       "      <td>0.029705</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2050</th>\n",
       "      <td>887343217045368832</td>\n",
       "      <td>https://pbs.twimg.com/ext_tw_video_thumb/88734...</td>\n",
       "      <td>1</td>\n",
       "      <td>Mexican_hairless</td>\n",
       "      <td>0.330741</td>\n",
       "      <td>True</td>\n",
       "      <td>sea_lion</td>\n",
       "      <td>0.275645</td>\n",
       "      <td>False</td>\n",
       "      <td>Weimaraner</td>\n",
       "      <td>0.134203</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2051</th>\n",
       "      <td>887473957103951883</td>\n",
       "      <td>https://pbs.twimg.com/media/DFDw2tyUQAAAFke.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>Pembroke</td>\n",
       "      <td>0.809197</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.054950</td>\n",
       "      <td>True</td>\n",
       "      <td>beagle</td>\n",
       "      <td>0.038915</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2052</th>\n",
       "      <td>887517139158093824</td>\n",
       "      <td>https://pbs.twimg.com/ext_tw_video_thumb/88751...</td>\n",
       "      <td>1</td>\n",
       "      <td>limousine</td>\n",
       "      <td>0.130432</td>\n",
       "      <td>False</td>\n",
       "      <td>tow_truck</td>\n",
       "      <td>0.029175</td>\n",
       "      <td>False</td>\n",
       "      <td>shopping_cart</td>\n",
       "      <td>0.026321</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2053</th>\n",
       "      <td>887705289381826560</td>\n",
       "      <td>https://pbs.twimg.com/media/DFHDQBbXgAEqY7t.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>basset</td>\n",
       "      <td>0.821664</td>\n",
       "      <td>True</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.087582</td>\n",
       "      <td>True</td>\n",
       "      <td>Weimaraner</td>\n",
       "      <td>0.026236</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2054</th>\n",
       "      <td>888078434458587136</td>\n",
       "      <td>https://pbs.twimg.com/media/DFMWn56WsAAkA7B.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>French_bulldog</td>\n",
       "      <td>0.995026</td>\n",
       "      <td>True</td>\n",
       "      <td>pug</td>\n",
       "      <td>0.000932</td>\n",
       "      <td>True</td>\n",
       "      <td>bull_mastiff</td>\n",
       "      <td>0.000903</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2055</th>\n",
       "      <td>888202515573088257</td>\n",
       "      <td>https://pbs.twimg.com/media/DFDw2tyUQAAAFke.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>Pembroke</td>\n",
       "      <td>0.809197</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.054950</td>\n",
       "      <td>True</td>\n",
       "      <td>beagle</td>\n",
       "      <td>0.038915</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2056</th>\n",
       "      <td>888554962724278272</td>\n",
       "      <td>https://pbs.twimg.com/media/DFTH_O-UQAACu20.jpg</td>\n",
       "      <td>3</td>\n",
       "      <td>Siberian_husky</td>\n",
       "      <td>0.700377</td>\n",
       "      <td>True</td>\n",
       "      <td>Eskimo_dog</td>\n",
       "      <td>0.166511</td>\n",
       "      <td>True</td>\n",
       "      <td>malamute</td>\n",
       "      <td>0.111411</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2057</th>\n",
       "      <td>888804989199671297</td>\n",
       "      <td>https://pbs.twimg.com/media/DFWra-3VYAA2piG.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.469760</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.184172</td>\n",
       "      <td>True</td>\n",
       "      <td>English_setter</td>\n",
       "      <td>0.073482</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2058</th>\n",
       "      <td>888917238123831296</td>\n",
       "      <td>https://pbs.twimg.com/media/DFYRgsOUQAARGhO.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.714719</td>\n",
       "      <td>True</td>\n",
       "      <td>Tibetan_mastiff</td>\n",
       "      <td>0.120184</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.105506</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2059</th>\n",
       "      <td>889278841981685760</td>\n",
       "      <td>https://pbs.twimg.com/ext_tw_video_thumb/88927...</td>\n",
       "      <td>1</td>\n",
       "      <td>whippet</td>\n",
       "      <td>0.626152</td>\n",
       "      <td>True</td>\n",
       "      <td>borzoi</td>\n",
       "      <td>0.194742</td>\n",
       "      <td>True</td>\n",
       "      <td>Saluki</td>\n",
       "      <td>0.027351</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060</th>\n",
       "      <td>889531135344209921</td>\n",
       "      <td>https://pbs.twimg.com/media/DFg_2PVW0AEHN3p.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.953442</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.013834</td>\n",
       "      <td>True</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.007958</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061</th>\n",
       "      <td>889638837579907072</td>\n",
       "      <td>https://pbs.twimg.com/media/DFihzFfXsAYGDPR.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>French_bulldog</td>\n",
       "      <td>0.991650</td>\n",
       "      <td>True</td>\n",
       "      <td>boxer</td>\n",
       "      <td>0.002129</td>\n",
       "      <td>True</td>\n",
       "      <td>Staffordshire_bullterrier</td>\n",
       "      <td>0.001498</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2062</th>\n",
       "      <td>889665388333682689</td>\n",
       "      <td>https://pbs.twimg.com/media/DFi579UWsAAatzw.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Pembroke</td>\n",
       "      <td>0.966327</td>\n",
       "      <td>True</td>\n",
       "      <td>Cardigan</td>\n",
       "      <td>0.027356</td>\n",
       "      <td>True</td>\n",
       "      <td>basenji</td>\n",
       "      <td>0.004633</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2063</th>\n",
       "      <td>889880896479866881</td>\n",
       "      <td>https://pbs.twimg.com/media/DFl99B1WsAITKsg.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>French_bulldog</td>\n",
       "      <td>0.377417</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.151317</td>\n",
       "      <td>True</td>\n",
       "      <td>muzzle</td>\n",
       "      <td>0.082981</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2064</th>\n",
       "      <td>890006608113172480</td>\n",
       "      <td>https://pbs.twimg.com/media/DFnwSY4WAAAMliS.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Samoyed</td>\n",
       "      <td>0.957979</td>\n",
       "      <td>True</td>\n",
       "      <td>Pomeranian</td>\n",
       "      <td>0.013884</td>\n",
       "      <td>True</td>\n",
       "      <td>chow</td>\n",
       "      <td>0.008167</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2065</th>\n",
       "      <td>890240255349198849</td>\n",
       "      <td>https://pbs.twimg.com/media/DFrEyVuW0AAO3t9.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Pembroke</td>\n",
       "      <td>0.511319</td>\n",
       "      <td>True</td>\n",
       "      <td>Cardigan</td>\n",
       "      <td>0.451038</td>\n",
       "      <td>True</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.029248</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2066</th>\n",
       "      <td>890609185150312448</td>\n",
       "      <td>https://pbs.twimg.com/media/DFwUU__XcAEpyXI.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Irish_terrier</td>\n",
       "      <td>0.487574</td>\n",
       "      <td>True</td>\n",
       "      <td>Irish_setter</td>\n",
       "      <td>0.193054</td>\n",
       "      <td>True</td>\n",
       "      <td>Chesapeake_Bay_retriever</td>\n",
       "      <td>0.118184</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2067</th>\n",
       "      <td>890729181411237888</td>\n",
       "      <td>https://pbs.twimg.com/media/DFyBahAVwAAhUTd.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>Pomeranian</td>\n",
       "      <td>0.566142</td>\n",
       "      <td>True</td>\n",
       "      <td>Eskimo_dog</td>\n",
       "      <td>0.178406</td>\n",
       "      <td>True</td>\n",
       "      <td>Pembroke</td>\n",
       "      <td>0.076507</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2068</th>\n",
       "      <td>890971913173991426</td>\n",
       "      <td>https://pbs.twimg.com/media/DF1eOmZXUAALUcq.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Appenzeller</td>\n",
       "      <td>0.341703</td>\n",
       "      <td>True</td>\n",
       "      <td>Border_collie</td>\n",
       "      <td>0.199287</td>\n",
       "      <td>True</td>\n",
       "      <td>ice_lolly</td>\n",
       "      <td>0.193548</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2069</th>\n",
       "      <td>891087950875897856</td>\n",
       "      <td>https://pbs.twimg.com/media/DF3HwyEWsAABqE6.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chesapeake_Bay_retriever</td>\n",
       "      <td>0.425595</td>\n",
       "      <td>True</td>\n",
       "      <td>Irish_terrier</td>\n",
       "      <td>0.116317</td>\n",
       "      <td>True</td>\n",
       "      <td>Indian_elephant</td>\n",
       "      <td>0.076902</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2070</th>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>https://pbs.twimg.com/media/DF6hr6BUMAAzZgT.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>basset</td>\n",
       "      <td>0.555712</td>\n",
       "      <td>True</td>\n",
       "      <td>English_springer</td>\n",
       "      <td>0.225770</td>\n",
       "      <td>True</td>\n",
       "      <td>German_short-haired_pointer</td>\n",
       "      <td>0.175219</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2071</th>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>https://pbs.twimg.com/media/DF_q7IAWsAEuuN8.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>paper_towel</td>\n",
       "      <td>0.170278</td>\n",
       "      <td>False</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.168086</td>\n",
       "      <td>True</td>\n",
       "      <td>spatula</td>\n",
       "      <td>0.040836</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2072</th>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>https://pbs.twimg.com/media/DGBdLU1WsAANxJ9.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.716012</td>\n",
       "      <td>True</td>\n",
       "      <td>malamute</td>\n",
       "      <td>0.078253</td>\n",
       "      <td>True</td>\n",
       "      <td>kelpie</td>\n",
       "      <td>0.031379</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2073</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>https://pbs.twimg.com/media/DGGmoV4XsAAUL6n.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.323581</td>\n",
       "      <td>True</td>\n",
       "      <td>Pekinese</td>\n",
       "      <td>0.090647</td>\n",
       "      <td>True</td>\n",
       "      <td>papillon</td>\n",
       "      <td>0.068957</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2074</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>orange</td>\n",
       "      <td>0.097049</td>\n",
       "      <td>False</td>\n",
       "      <td>bagel</td>\n",
       "      <td>0.085851</td>\n",
       "      <td>False</td>\n",
       "      <td>banana</td>\n",
       "      <td>0.076110</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2075 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id                                            jpg_url  \\\n",
       "0     666020888022790149    https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg   \n",
       "1     666029285002620928    https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg   \n",
       "2     666033412701032449    https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg   \n",
       "3     666044226329800704    https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg   \n",
       "4     666049248165822465    https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg   \n",
       "5     666050758794694657    https://pbs.twimg.com/media/CT5Jof1WUAEuVxN.jpg   \n",
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       "7     666055525042405380    https://pbs.twimg.com/media/CT5N9tpXIAAifs1.jpg   \n",
       "8     666057090499244032    https://pbs.twimg.com/media/CT5PY90WoAAQGLo.jpg   \n",
       "9     666058600524156928    https://pbs.twimg.com/media/CT5Qw94XAAA_2dP.jpg   \n",
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       "11    666071193221509120    https://pbs.twimg.com/media/CT5cN_3WEAAlOoZ.jpg   \n",
       "12    666073100786774016    https://pbs.twimg.com/media/CT5d9DZXAAALcwe.jpg   \n",
       "13    666082916733198337    https://pbs.twimg.com/media/CT5m4VGWEAAtKc8.jpg   \n",
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       "16    666102155909144576    https://pbs.twimg.com/media/CT54YGiWUAEZnoK.jpg   \n",
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       "22    666337882303524864    https://pbs.twimg.com/media/CT9OwFIWEAMuRje.jpg   \n",
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       "26    666373753744588802    https://pbs.twimg.com/media/CT9vZEYWUAAlZ05.jpg   \n",
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       "28    666407126856765440    https://pbs.twimg.com/media/CT-NvwmW4AAugGZ.jpg   \n",
       "29    666411507551481857    https://pbs.twimg.com/media/CT-RugiWIAELEaq.jpg   \n",
       "...                  ...                                                ...   \n",
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       "2053  887705289381826560    https://pbs.twimg.com/media/DFHDQBbXgAEqY7t.jpg   \n",
       "2054  888078434458587136    https://pbs.twimg.com/media/DFMWn56WsAAkA7B.jpg   \n",
       "2055  888202515573088257    https://pbs.twimg.com/media/DFDw2tyUQAAAFke.jpg   \n",
       "2056  888554962724278272    https://pbs.twimg.com/media/DFTH_O-UQAACu20.jpg   \n",
       "2057  888804989199671297    https://pbs.twimg.com/media/DFWra-3VYAA2piG.jpg   \n",
       "2058  888917238123831296    https://pbs.twimg.com/media/DFYRgsOUQAARGhO.jpg   \n",
       "2059  889278841981685760  https://pbs.twimg.com/ext_tw_video_thumb/88927...   \n",
       "2060  889531135344209921    https://pbs.twimg.com/media/DFg_2PVW0AEHN3p.jpg   \n",
       "2061  889638837579907072    https://pbs.twimg.com/media/DFihzFfXsAYGDPR.jpg   \n",
       "2062  889665388333682689    https://pbs.twimg.com/media/DFi579UWsAAatzw.jpg   \n",
       "2063  889880896479866881    https://pbs.twimg.com/media/DFl99B1WsAITKsg.jpg   \n",
       "2064  890006608113172480    https://pbs.twimg.com/media/DFnwSY4WAAAMliS.jpg   \n",
       "2065  890240255349198849    https://pbs.twimg.com/media/DFrEyVuW0AAO3t9.jpg   \n",
       "2066  890609185150312448    https://pbs.twimg.com/media/DFwUU__XcAEpyXI.jpg   \n",
       "2067  890729181411237888    https://pbs.twimg.com/media/DFyBahAVwAAhUTd.jpg   \n",
       "2068  890971913173991426    https://pbs.twimg.com/media/DF1eOmZXUAALUcq.jpg   \n",
       "2069  891087950875897856    https://pbs.twimg.com/media/DF3HwyEWsAABqE6.jpg   \n",
       "2070  891327558926688256    https://pbs.twimg.com/media/DF6hr6BUMAAzZgT.jpg   \n",
       "2071  891689557279858688    https://pbs.twimg.com/media/DF_q7IAWsAEuuN8.jpg   \n",
       "2072  891815181378084864    https://pbs.twimg.com/media/DGBdLU1WsAANxJ9.jpg   \n",
       "2073  892177421306343426    https://pbs.twimg.com/media/DGGmoV4XsAAUL6n.jpg   \n",
       "2074  892420643555336193    https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg   \n",
       "\n",
       "      img_num                           p1   p1_conf  p1_dog  \\\n",
       "0           1       Welsh_springer_spaniel  0.465074    True   \n",
       "1           1                      redbone  0.506826    True   \n",
       "2           1              German_shepherd  0.596461    True   \n",
       "3           1          Rhodesian_ridgeback  0.408143    True   \n",
       "4           1           miniature_pinscher  0.560311    True   \n",
       "5           1         Bernese_mountain_dog  0.651137    True   \n",
       "6           1                   box_turtle  0.933012   False   \n",
       "7           1                         chow  0.692517    True   \n",
       "8           1                shopping_cart  0.962465   False   \n",
       "9           1             miniature_poodle  0.201493    True   \n",
       "10          1             golden_retriever  0.775930    True   \n",
       "11          1                Gordon_setter  0.503672    True   \n",
       "12          1                 Walker_hound  0.260857    True   \n",
       "13          1                          pug  0.489814    True   \n",
       "14          1                   bloodhound  0.195217    True   \n",
       "15          1                        Lhasa  0.582330    True   \n",
       "16          1               English_setter  0.298617    True   \n",
       "17          1                          hen  0.965932   False   \n",
       "18          1             desktop_computer  0.086502   False   \n",
       "19          1            Italian_greyhound  0.176053    True   \n",
       "20          1                  Maltese_dog  0.857531    True   \n",
       "21          1             three-toed_sloth  0.914671   False   \n",
       "22          1                           ox  0.416669   False   \n",
       "23          1             golden_retriever  0.858744    True   \n",
       "24          1                     malamute  0.336874    True   \n",
       "25          1                   guinea_pig  0.996496   False   \n",
       "26          1  soft-coated_wheaten_terrier  0.326467    True   \n",
       "27          1                    Chihuahua  0.978108    True   \n",
       "28          1      black-and-tan_coonhound  0.529139    True   \n",
       "29          1                         coho  0.404640   False   \n",
       "...       ...                          ...       ...     ...   \n",
       "2045        1               French_bulldog  0.999201    True   \n",
       "2046        1                  convertible  0.738995   False   \n",
       "2047        1                       kuvasz  0.309706    True   \n",
       "2048        2                    Chihuahua  0.793469    True   \n",
       "2049        1                      Samoyed  0.733942    True   \n",
       "2050        1             Mexican_hairless  0.330741    True   \n",
       "2051        2                     Pembroke  0.809197    True   \n",
       "2052        1                    limousine  0.130432   False   \n",
       "2053        1                       basset  0.821664    True   \n",
       "2054        1               French_bulldog  0.995026    True   \n",
       "2055        2                     Pembroke  0.809197    True   \n",
       "2056        3               Siberian_husky  0.700377    True   \n",
       "2057        1             golden_retriever  0.469760    True   \n",
       "2058        1             golden_retriever  0.714719    True   \n",
       "2059        1                      whippet  0.626152    True   \n",
       "2060        1             golden_retriever  0.953442    True   \n",
       "2061        1               French_bulldog  0.991650    True   \n",
       "2062        1                     Pembroke  0.966327    True   \n",
       "2063        1               French_bulldog  0.377417    True   \n",
       "2064        1                      Samoyed  0.957979    True   \n",
       "2065        1                     Pembroke  0.511319    True   \n",
       "2066        1                Irish_terrier  0.487574    True   \n",
       "2067        2                   Pomeranian  0.566142    True   \n",
       "2068        1                  Appenzeller  0.341703    True   \n",
       "2069        1     Chesapeake_Bay_retriever  0.425595    True   \n",
       "2070        2                       basset  0.555712    True   \n",
       "2071        1                  paper_towel  0.170278   False   \n",
       "2072        1                    Chihuahua  0.716012    True   \n",
       "2073        1                    Chihuahua  0.323581    True   \n",
       "2074        1                       orange  0.097049   False   \n",
       "\n",
       "                            p2   p2_conf  p2_dog                           p3  \\\n",
       "0                       collie  0.156665    True            Shetland_sheepdog   \n",
       "1           miniature_pinscher  0.074192    True          Rhodesian_ridgeback   \n",
       "2                     malinois  0.138584    True                   bloodhound   \n",
       "3                      redbone  0.360687    True           miniature_pinscher   \n",
       "4                   Rottweiler  0.243682    True                     Doberman   \n",
       "5             English_springer  0.263788    True   Greater_Swiss_Mountain_dog   \n",
       "6                   mud_turtle  0.045885   False                     terrapin   \n",
       "7              Tibetan_mastiff  0.058279    True                     fur_coat   \n",
       "8              shopping_basket  0.014594   False             golden_retriever   \n",
       "9                     komondor  0.192305    True  soft-coated_wheaten_terrier   \n",
       "10             Tibetan_mastiff  0.093718    True           Labrador_retriever   \n",
       "11           Yorkshire_terrier  0.174201    True                     Pekinese   \n",
       "12            English_foxhound  0.175382    True                 Ibizan_hound   \n",
       "13                bull_mastiff  0.404722    True               French_bulldog   \n",
       "14             German_shepherd  0.078260    True                     malinois   \n",
       "15                    Shih-Tzu  0.166192    True               Dandie_Dinmont   \n",
       "16                Newfoundland  0.149842    True                       borzoi   \n",
       "17                        cock  0.033919   False                    partridge   \n",
       "18                        desk  0.085547   False                     bookcase   \n",
       "19                 toy_terrier  0.111884    True                      basenji   \n",
       "20                  toy_poodle  0.063064    True             miniature_poodle   \n",
       "21                       otter  0.015250   False               great_grey_owl   \n",
       "22                Newfoundland  0.278407    True                  groenendael   \n",
       "23    Chesapeake_Bay_retriever  0.054787    True           Labrador_retriever   \n",
       "24              Siberian_husky  0.147655    True                   Eskimo_dog   \n",
       "25                       skunk  0.002402   False                      hamster   \n",
       "26                Afghan_hound  0.259551    True                       briard   \n",
       "27                 toy_terrier  0.009397    True                     papillon   \n",
       "28                  bloodhound  0.244220    True        flat-coated_retriever   \n",
       "29                  barracouta  0.271485   False                          gar   \n",
       "...                        ...       ...     ...                          ...   \n",
       "2045                 Chihuahua  0.000361    True                  Boston_bull   \n",
       "2046                sports_car  0.139952   False                    car_wheel   \n",
       "2047            Great_Pyrenees  0.186136    True               Dandie_Dinmont   \n",
       "2048               toy_terrier  0.143528    True                   can_opener   \n",
       "2049                Eskimo_dog  0.035029    True    Staffordshire_bullterrier   \n",
       "2050                  sea_lion  0.275645   False                   Weimaraner   \n",
       "2051       Rhodesian_ridgeback  0.054950    True                       beagle   \n",
       "2052                 tow_truck  0.029175   False                shopping_cart   \n",
       "2053                   redbone  0.087582    True                   Weimaraner   \n",
       "2054                       pug  0.000932    True                 bull_mastiff   \n",
       "2055       Rhodesian_ridgeback  0.054950    True                       beagle   \n",
       "2056                Eskimo_dog  0.166511    True                     malamute   \n",
       "2057        Labrador_retriever  0.184172    True               English_setter   \n",
       "2058           Tibetan_mastiff  0.120184    True           Labrador_retriever   \n",
       "2059                    borzoi  0.194742    True                       Saluki   \n",
       "2060        Labrador_retriever  0.013834    True                      redbone   \n",
       "2061                     boxer  0.002129    True    Staffordshire_bullterrier   \n",
       "2062                  Cardigan  0.027356    True                      basenji   \n",
       "2063        Labrador_retriever  0.151317    True                       muzzle   \n",
       "2064                Pomeranian  0.013884    True                         chow   \n",
       "2065                  Cardigan  0.451038    True                    Chihuahua   \n",
       "2066              Irish_setter  0.193054    True     Chesapeake_Bay_retriever   \n",
       "2067                Eskimo_dog  0.178406    True                     Pembroke   \n",
       "2068             Border_collie  0.199287    True                    ice_lolly   \n",
       "2069             Irish_terrier  0.116317    True              Indian_elephant   \n",
       "2070          English_springer  0.225770    True  German_short-haired_pointer   \n",
       "2071        Labrador_retriever  0.168086    True                      spatula   \n",
       "2072                  malamute  0.078253    True                       kelpie   \n",
       "2073                  Pekinese  0.090647    True                     papillon   \n",
       "2074                     bagel  0.085851   False                       banana   \n",
       "\n",
       "       p3_conf  p3_dog  \n",
       "0     0.061428    True  \n",
       "1     0.072010    True  \n",
       "2     0.116197    True  \n",
       "3     0.222752    True  \n",
       "4     0.154629    True  \n",
       "5     0.016199    True  \n",
       "6     0.017885   False  \n",
       "7     0.054449   False  \n",
       "8     0.007959    True  \n",
       "9     0.082086    True  \n",
       "10    0.072427    True  \n",
       "11    0.109454    True  \n",
       "12    0.097471    True  \n",
       "13    0.048960    True  \n",
       "14    0.075628    True  \n",
       "15    0.089688    True  \n",
       "16    0.133649    True  \n",
       "17    0.000052   False  \n",
       "18    0.079480   False  \n",
       "19    0.111152    True  \n",
       "20    0.025581    True  \n",
       "21    0.013207   False  \n",
       "22    0.102643    True  \n",
       "23    0.014241    True  \n",
       "24    0.093412    True  \n",
       "25    0.000461   False  \n",
       "26    0.206803    True  \n",
       "27    0.004577    True  \n",
       "28    0.173810    True  \n",
       "29    0.189945   False  \n",
       "...        ...     ...  \n",
       "2045  0.000076    True  \n",
       "2046  0.044173   False  \n",
       "2047  0.086346    True  \n",
       "2048  0.032253   False  \n",
       "2049  0.029705    True  \n",
       "2050  0.134203    True  \n",
       "2051  0.038915    True  \n",
       "2052  0.026321   False  \n",
       "2053  0.026236    True  \n",
       "2054  0.000903    True  \n",
       "2055  0.038915    True  \n",
       "2056  0.111411    True  \n",
       "2057  0.073482    True  \n",
       "2058  0.105506    True  \n",
       "2059  0.027351    True  \n",
       "2060  0.007958    True  \n",
       "2061  0.001498    True  \n",
       "2062  0.004633    True  \n",
       "2063  0.082981   False  \n",
       "2064  0.008167    True  \n",
       "2065  0.029248    True  \n",
       "2066  0.118184    True  \n",
       "2067  0.076507    True  \n",
       "2068  0.193548   False  \n",
       "2069  0.076902   False  \n",
       "2070  0.175219    True  \n",
       "2071  0.040836   False  \n",
       "2072  0.031379    True  \n",
       "2073  0.068957    True  \n",
       "2074  0.076110   False  \n",
       "\n",
       "[2075 rows x 12 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Output df_2 dataset\n",
    "df_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "      <td>{'hashtags': [{'text': 'BarkWeek', 'indices': ...</td>\n",
       "      <td>{'media': [{'id': 891087942176911360, 'id_str'...</td>\n",
       "      <td>17225</td>\n",
       "      <td>False</td>\n",
       "      <td>Here we have a majestic great white breaching ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2540</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-28 16:27:12</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 890971906207338496, 'id_str'...</td>\n",
       "      <td>10040</td>\n",
       "      <td>False</td>\n",
       "      <td>Meet Jax. He enjoys ice cream so much he gets ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1615</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-28 00:22:40</td>\n",
       "      <td>[0, 118]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 890729118844600320, 'id_str'...</td>\n",
       "      <td>55175</td>\n",
       "      <td>False</td>\n",
       "      <td>When you watch your owner call another dog a g...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15394</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-27 16:25:51</td>\n",
       "      <td>[0, 122]</td>\n",
       "      <td>{'hashtags': [{'text': 'BarkWeek', 'indices': ...</td>\n",
       "      <td>{'media': [{'id': 890609177319665665, 'id_str'...</td>\n",
       "      <td>23758</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Zoey. She doesn't want to be one of th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3546</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-26 15:59:51</td>\n",
       "      <td>[0, 133]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 890240245463175168, 'id_str'...</td>\n",
       "      <td>27083</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Cassie. She is a college pup. Studying...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5958</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-26 00:31:25</td>\n",
       "      <td>[0, 130]</td>\n",
       "      <td>{'hashtags': [{'text': 'BarkWeek', 'indices': ...</td>\n",
       "      <td>{'media': [{'id': 890006600089468928, 'id_str'...</td>\n",
       "      <td>26218</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Koda. He is a South Australian decksha...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6004</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 16:11:53</td>\n",
       "      <td>[0, 107]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 889880888800096258, 'id_str'...</td>\n",
       "      <td>23769</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Bruno. He is a service shark. Only get...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4054</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 01:55:32</td>\n",
       "      <td>[0, 106]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 889665366129029120, 'id_str'...</td>\n",
       "      <td>40798</td>\n",
       "      <td>False</td>\n",
       "      <td>Here's a puppo that seems to be on the fence a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8164</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 00:10:02</td>\n",
       "      <td>[0, 91]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 889638825424826374, 'id_str'...</td>\n",
       "      <td>22969</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Ted. He does his best. Sometimes that'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3635</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-24 17:02:04</td>\n",
       "      <td>[0, 118]</td>\n",
       "      <td>{'hashtags': [{'text': 'BarkWeek', 'indices': ...</td>\n",
       "      <td>{'media': [{'id': 889531127467266049, 'id_str'...</td>\n",
       "      <td>12939</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Stuart. He's sporting his favorite fan...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1848</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-24 00:19:32</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>{'hashtags': [{'text': 'BarkWeek', 'indices': ...</td>\n",
       "      <td>{'media': [{'id': 889278779352338437, 'id_str'...</td>\n",
       "      <td>21385</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Oliver. You're witnessing one of his m...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4343</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-23 00:22:39</td>\n",
       "      <td>[0, 86]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 888917229776945152, 'id_str'...</td>\n",
       "      <td>24840</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Jim. He found a fren. Taught him how t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3676</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-22 16:56:37</td>\n",
       "      <td>[0, 128]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 888804981515575296, 'id_str'...</td>\n",
       "      <td>21760</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Zeke. He has a new stick. Very proud o...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3452</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-22 00:23:06</td>\n",
       "      <td>[0, 87]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 888554915546542081, 'id_str'...</td>\n",
       "      <td>16800</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Ralphus. He's powering up. Attempting ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2829</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-20 16:49:33</td>\n",
       "      <td>[0, 127]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 888078426338406400, 'id_str'...</td>\n",
       "      <td>18517</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Gerald. He was just told he didn't get...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2832</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 16:06:48</td>\n",
       "      <td>[0, 127]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 887705281597243393, 'id_str'...</td>\n",
       "      <td>25760</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Jeffrey. He has a monopoly on the pool...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4422</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 03:39:09</td>\n",
       "      <td>[0, 108]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 887517108413886465, 'id_str'...</td>\n",
       "      <td>39405</td>\n",
       "      <td>False</td>\n",
       "      <td>I've yet to rate a Venezuelan Hover Wiener. Th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9595</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 00:47:34</td>\n",
       "      <td>[0, 99]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 887473949361045505, 'id_str'...</td>\n",
       "      <td>58455</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Canela. She attempted some fancy porch...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14691</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-18 16:08:03</td>\n",
       "      <td>[0, 88]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 887343120832229379, 'id_str'...</td>\n",
       "      <td>28654</td>\n",
       "      <td>False</td>\n",
       "      <td>You may not have known you needed to see this ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8567</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-18 00:07:08</td>\n",
       "      <td>[0, 129]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 887101385971384320, 'id_str'...</td>\n",
       "      <td>26098</td>\n",
       "      <td>False</td>\n",
       "      <td>This... is a Jubilant Antarctic House Bear. We...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4870</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-17 16:17:36</td>\n",
       "      <td>[0, 101]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 886983218871902208, 'id_str'...</td>\n",
       "      <td>29477</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Maya. She's very shy. Rarely leaves he...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6166</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-16 23:58:41</td>\n",
       "      <td>[0, 121]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 886736868116754432, 'id_str'...</td>\n",
       "      <td>10194</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Mingus. He's a wonderful father to his...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2562</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-16 20:14:00</td>\n",
       "      <td>[0, 71]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 886680331239161856, 'id_str'...</td>\n",
       "      <td>19115</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Derek. He's late for a dog meeting. 13...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3657</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-15 23:25:31</td>\n",
       "      <td>[0, 131]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 886366138128449536, 'id_str'...</td>\n",
       "      <td>17979</td>\n",
       "      <td>False</td>\n",
       "      <td>This is Roscoe. Another pupper fallen victim t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2559</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-15 16:51:35</td>\n",
       "      <td>[27, 105]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101</td>\n",
       "      <td>False</td>\n",
       "      <td>@NonWhiteHat @MayhewMayhem omg hello tanner yo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2296</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 00:24:19</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666411498068123649, 'id_str'...</td>\n",
       "      <td>361</td>\n",
       "      <td>False</td>\n",
       "      <td>This is quite the dog. Gets really excited whe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>257</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2297</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 00:06:54</td>\n",
       "      <td>[0, 139]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666407121513275392, 'id_str'...</td>\n",
       "      <td>91</td>\n",
       "      <td>False</td>\n",
       "      <td>This is a southern Vesuvius bumblegruff. Can d...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2298</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 23:23:41</td>\n",
       "      <td>[0, 137]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666396240351993856, 'id_str'...</td>\n",
       "      <td>145</td>\n",
       "      <td>False</td>\n",
       "      <td>Oh goodness. A super rare northeast Qdoba kang...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2299</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 21:54:18</td>\n",
       "      <td>[0, 81]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666373746337402880, 'id_str'...</td>\n",
       "      <td>157</td>\n",
       "      <td>False</td>\n",
       "      <td>Those are sunglasses and a jean jacket. 11/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2300</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 21:10:36</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666362717482020864, 'id_str'...</td>\n",
       "      <td>638</td>\n",
       "      <td>False</td>\n",
       "      <td>Unique dog here. Very small. Lives in containe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>462</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2301</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 20:32:58</td>\n",
       "      <td>[0, 135]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666353280906170368, 'id_str'...</td>\n",
       "      <td>169</td>\n",
       "      <td>False</td>\n",
       "      <td>Here we have a mixed Asiago from the Galápagos...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>56</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2302</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 20:01:42</td>\n",
       "      <td>[0, 112]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666345414279471104, 'id_str'...</td>\n",
       "      <td>230</td>\n",
       "      <td>False</td>\n",
       "      <td>Look at this jokester thinking seat belt laws ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>120</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2303</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 19:31:45</td>\n",
       "      <td>[0, 139]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666337857791987715, 'id_str'...</td>\n",
       "      <td>161</td>\n",
       "      <td>False</td>\n",
       "      <td>This is an extremely rare horned Parthenon. No...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2304</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 16:37:02</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666293909010702337, 'id_str'...</td>\n",
       "      <td>416</td>\n",
       "      <td>False</td>\n",
       "      <td>This is a funny dog. Weird toes. Won't come do...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>287</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2305</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 16:11:11</td>\n",
       "      <td>[0, 136]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666287399580733440, 'id_str'...</td>\n",
       "      <td>118</td>\n",
       "      <td>False</td>\n",
       "      <td>This is an Albanian 3 1/2 legged  Episcopalian...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2306</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 15:14:19</td>\n",
       "      <td>[0, 46]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666273081518768128, 'id_str'...</td>\n",
       "      <td>147</td>\n",
       "      <td>False</td>\n",
       "      <td>Can take selfies 11/10 https://t.co/ws2AMaNwPW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2307</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 14:57:41</td>\n",
       "      <td>[0, 82]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666268904428277760, 'id_str'...</td>\n",
       "      <td>96</td>\n",
       "      <td>False</td>\n",
       "      <td>Very concerned about fellow dog trapped in com...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2308</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 04:02:55</td>\n",
       "      <td>[0, 134]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666104129232740352, 'id_str'...</td>\n",
       "      <td>12513</td>\n",
       "      <td>False</td>\n",
       "      <td>Not familiar with this breed. No tail (weird)....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5356</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2309</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:55:04</td>\n",
       "      <td>[0, 128]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666102150364286977, 'id_str'...</td>\n",
       "      <td>62</td>\n",
       "      <td>False</td>\n",
       "      <td>Oh my. Here you are seeing an Adobe Setter giv...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2310</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:44:34</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666099505364733952, 'id_str'...</td>\n",
       "      <td>131</td>\n",
       "      <td>False</td>\n",
       "      <td>Can stand on stump for what seems like a while...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2311</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:22:39</td>\n",
       "      <td>[0, 132]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666093996847063040, 'id_str'...</td>\n",
       "      <td>138</td>\n",
       "      <td>False</td>\n",
       "      <td>This appears to be a Mongolian Presbyterian mi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2312</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 02:38:37</td>\n",
       "      <td>[0, 125]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666082912819875840, 'id_str'...</td>\n",
       "      <td>89</td>\n",
       "      <td>False</td>\n",
       "      <td>Here we have a well-established sunblockerspan...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2313</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:59:36</td>\n",
       "      <td>[0, 137]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666073098362486784, 'id_str'...</td>\n",
       "      <td>270</td>\n",
       "      <td>False</td>\n",
       "      <td>Let's hope this flight isn't Malaysian (lol). ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>129</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2314</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:52:02</td>\n",
       "      <td>[0, 137]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666071190449033216, 'id_str'...</td>\n",
       "      <td>124</td>\n",
       "      <td>False</td>\n",
       "      <td>Here we have a northern speckled Rhododendron....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2315</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:22:45</td>\n",
       "      <td>[0, 107]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666063820255862784, 'id_str'...</td>\n",
       "      <td>387</td>\n",
       "      <td>False</td>\n",
       "      <td>This is the happiest dog you will ever see. Ve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>178</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2316</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:01:59</td>\n",
       "      <td>[0, 135]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666058597072306176, 'id_str'...</td>\n",
       "      <td>96</td>\n",
       "      <td>False</td>\n",
       "      <td>Here is the Rand Paul of retrievers folks! He'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2317</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:55:59</td>\n",
       "      <td>[0, 124]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666057085227016192, 'id_str'...</td>\n",
       "      <td>243</td>\n",
       "      <td>False</td>\n",
       "      <td>My oh my. This is a rare blond Canadian terrie...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2318</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:49:46</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666055517517848576, 'id_str'...</td>\n",
       "      <td>359</td>\n",
       "      <td>False</td>\n",
       "      <td>Here is a Siberian heavily armored polar bear ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>193</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2319</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:35:11</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666051848592334848, 'id_str'...</td>\n",
       "      <td>1005</td>\n",
       "      <td>False</td>\n",
       "      <td>This is an odd dog. Hard on the outside but lo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>685</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2320</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:30:50</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666050754986266625, 'id_str'...</td>\n",
       "      <td>110</td>\n",
       "      <td>False</td>\n",
       "      <td>This is a truly beautiful English Wilson Staff...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2321</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:24:50</td>\n",
       "      <td>[0, 120]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666049244999131136, 'id_str'...</td>\n",
       "      <td>84</td>\n",
       "      <td>False</td>\n",
       "      <td>Here we have a 1949 1st generation vulpix. Enj...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2322</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:04:52</td>\n",
       "      <td>[0, 137]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666044217047650304, 'id_str'...</td>\n",
       "      <td>242</td>\n",
       "      <td>False</td>\n",
       "      <td>This is a purebred Piers Morgan. Loves to Netf...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>113</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2323</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 23:21:54</td>\n",
       "      <td>[0, 130]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666033409081393153, 'id_str'...</td>\n",
       "      <td>97</td>\n",
       "      <td>False</td>\n",
       "      <td>Here is a very happy pup. Big fan of well-main...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2324</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 23:05:30</td>\n",
       "      <td>[0, 139]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666029276303482880, 'id_str'...</td>\n",
       "      <td>110</td>\n",
       "      <td>False</td>\n",
       "      <td>This is a western brown Mitsubishi terrier. Up...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2325</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 22:32:08</td>\n",
       "      <td>[0, 131]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 666020881337073664, 'id_str'...</td>\n",
       "      <td>2225</td>\n",
       "      <td>False</td>\n",
       "      <td>Here we have a Japanese Irish Setter. Lost eye...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>416</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2326 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      contributors  coordinates          created_at display_text_range  \\\n",
       "0              NaN          NaN 2017-08-01 16:23:56            [0, 85]   \n",
       "1              NaN          NaN 2017-08-01 00:17:27           [0, 138]   \n",
       "2              NaN          NaN 2017-07-31 00:18:03           [0, 121]   \n",
       "3              NaN          NaN 2017-07-30 15:58:51            [0, 79]   \n",
       "4              NaN          NaN 2017-07-29 16:00:24           [0, 138]   \n",
       "5              NaN          NaN 2017-07-29 00:08:17           [0, 138]   \n",
       "6              NaN          NaN 2017-07-28 16:27:12           [0, 140]   \n",
       "7              NaN          NaN 2017-07-28 00:22:40           [0, 118]   \n",
       "8              NaN          NaN 2017-07-27 16:25:51           [0, 122]   \n",
       "9              NaN          NaN 2017-07-26 15:59:51           [0, 133]   \n",
       "10             NaN          NaN 2017-07-26 00:31:25           [0, 130]   \n",
       "11             NaN          NaN 2017-07-25 16:11:53           [0, 107]   \n",
       "12             NaN          NaN 2017-07-25 01:55:32           [0, 106]   \n",
       "13             NaN          NaN 2017-07-25 00:10:02            [0, 91]   \n",
       "14             NaN          NaN 2017-07-24 17:02:04           [0, 118]   \n",
       "15             NaN          NaN 2017-07-24 00:19:32           [0, 138]   \n",
       "16             NaN          NaN 2017-07-23 00:22:39            [0, 86]   \n",
       "17             NaN          NaN 2017-07-22 16:56:37           [0, 128]   \n",
       "18             NaN          NaN 2017-07-22 00:23:06            [0, 87]   \n",
       "19             NaN          NaN 2017-07-20 16:49:33           [0, 127]   \n",
       "20             NaN          NaN 2017-07-19 16:06:48           [0, 127]   \n",
       "21             NaN          NaN 2017-07-19 03:39:09           [0, 108]   \n",
       "22             NaN          NaN 2017-07-19 00:47:34            [0, 99]   \n",
       "23             NaN          NaN 2017-07-18 16:08:03            [0, 88]   \n",
       "24             NaN          NaN 2017-07-18 00:07:08           [0, 129]   \n",
       "25             NaN          NaN 2017-07-17 16:17:36           [0, 101]   \n",
       "26             NaN          NaN 2017-07-16 23:58:41           [0, 121]   \n",
       "27             NaN          NaN 2017-07-16 20:14:00            [0, 71]   \n",
       "28             NaN          NaN 2017-07-15 23:25:31           [0, 131]   \n",
       "29             NaN          NaN 2017-07-15 16:51:35          [27, 105]   \n",
       "...            ...          ...                 ...                ...   \n",
       "2296           NaN          NaN 2015-11-17 00:24:19           [0, 140]   \n",
       "2297           NaN          NaN 2015-11-17 00:06:54           [0, 139]   \n",
       "2298           NaN          NaN 2015-11-16 23:23:41           [0, 137]   \n",
       "2299           NaN          NaN 2015-11-16 21:54:18            [0, 81]   \n",
       "2300           NaN          NaN 2015-11-16 21:10:36           [0, 140]   \n",
       "2301           NaN          NaN 2015-11-16 20:32:58           [0, 135]   \n",
       "2302           NaN          NaN 2015-11-16 20:01:42           [0, 112]   \n",
       "2303           NaN          NaN 2015-11-16 19:31:45           [0, 139]   \n",
       "2304           NaN          NaN 2015-11-16 16:37:02           [0, 138]   \n",
       "2305           NaN          NaN 2015-11-16 16:11:11           [0, 136]   \n",
       "2306           NaN          NaN 2015-11-16 15:14:19            [0, 46]   \n",
       "2307           NaN          NaN 2015-11-16 14:57:41            [0, 82]   \n",
       "2308           NaN          NaN 2015-11-16 04:02:55           [0, 134]   \n",
       "2309           NaN          NaN 2015-11-16 03:55:04           [0, 128]   \n",
       "2310           NaN          NaN 2015-11-16 03:44:34           [0, 140]   \n",
       "2311           NaN          NaN 2015-11-16 03:22:39           [0, 132]   \n",
       "2312           NaN          NaN 2015-11-16 02:38:37           [0, 125]   \n",
       "2313           NaN          NaN 2015-11-16 01:59:36           [0, 137]   \n",
       "2314           NaN          NaN 2015-11-16 01:52:02           [0, 137]   \n",
       "2315           NaN          NaN 2015-11-16 01:22:45           [0, 107]   \n",
       "2316           NaN          NaN 2015-11-16 01:01:59           [0, 135]   \n",
       "2317           NaN          NaN 2015-11-16 00:55:59           [0, 124]   \n",
       "2318           NaN          NaN 2015-11-16 00:49:46           [0, 140]   \n",
       "2319           NaN          NaN 2015-11-16 00:35:11           [0, 138]   \n",
       "2320           NaN          NaN 2015-11-16 00:30:50           [0, 140]   \n",
       "2321           NaN          NaN 2015-11-16 00:24:50           [0, 120]   \n",
       "2322           NaN          NaN 2015-11-16 00:04:52           [0, 137]   \n",
       "2323           NaN          NaN 2015-11-15 23:21:54           [0, 130]   \n",
       "2324           NaN          NaN 2015-11-15 23:05:30           [0, 139]   \n",
       "2325           NaN          NaN 2015-11-15 22:32:08           [0, 131]   \n",
       "\n",
       "                                               entities  \\\n",
       "0     {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "1     {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2     {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "3     {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "4     {'hashtags': [{'text': 'BarkWeek', 'indices': ...   \n",
       "5     {'hashtags': [{'text': 'BarkWeek', 'indices': ...   \n",
       "6     {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "7     {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "8     {'hashtags': [{'text': 'BarkWeek', 'indices': ...   \n",
       "9     {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "10    {'hashtags': [{'text': 'BarkWeek', 'indices': ...   \n",
       "11    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "12    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "13    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "14    {'hashtags': [{'text': 'BarkWeek', 'indices': ...   \n",
       "15    {'hashtags': [{'text': 'BarkWeek', 'indices': ...   \n",
       "16    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "17    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "18    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "19    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "20    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "21    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "22    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "23    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "24    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "25    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "26    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "27    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "28    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "29    {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "...                                                 ...   \n",
       "2296  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2297  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2298  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2299  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2300  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2301  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2302  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2303  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2304  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2305  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2306  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2307  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2308  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2309  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2310  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2311  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2312  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2313  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2314  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2315  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2316  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2317  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2318  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2319  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2320  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2321  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2322  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2323  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2324  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2325  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "\n",
       "                                      extended_entities  favorite_count  \\\n",
       "0     {'media': [{'id': 892420639486877696, 'id_str'...           32822   \n",
       "1     {'media': [{'id': 892177413194625024, 'id_str'...           28373   \n",
       "2     {'media': [{'id': 891815175371796480, 'id_str'...           21301   \n",
       "3     {'media': [{'id': 891689552724799489, 'id_str'...           35780   \n",
       "4     {'media': [{'id': 891327551943041024, 'id_str'...           34206   \n",
       "5     {'media': [{'id': 891087942176911360, 'id_str'...           17225   \n",
       "6     {'media': [{'id': 890971906207338496, 'id_str'...           10040   \n",
       "7     {'media': [{'id': 890729118844600320, 'id_str'...           55175   \n",
       "8     {'media': [{'id': 890609177319665665, 'id_str'...           23758   \n",
       "9     {'media': [{'id': 890240245463175168, 'id_str'...           27083   \n",
       "10    {'media': [{'id': 890006600089468928, 'id_str'...           26218   \n",
       "11    {'media': [{'id': 889880888800096258, 'id_str'...           23769   \n",
       "12    {'media': [{'id': 889665366129029120, 'id_str'...           40798   \n",
       "13    {'media': [{'id': 889638825424826374, 'id_str'...           22969   \n",
       "14    {'media': [{'id': 889531127467266049, 'id_str'...           12939   \n",
       "15    {'media': [{'id': 889278779352338437, 'id_str'...           21385   \n",
       "16    {'media': [{'id': 888917229776945152, 'id_str'...           24840   \n",
       "17    {'media': [{'id': 888804981515575296, 'id_str'...           21760   \n",
       "18    {'media': [{'id': 888554915546542081, 'id_str'...           16800   \n",
       "19    {'media': [{'id': 888078426338406400, 'id_str'...           18517   \n",
       "20    {'media': [{'id': 887705281597243393, 'id_str'...           25760   \n",
       "21    {'media': [{'id': 887517108413886465, 'id_str'...           39405   \n",
       "22    {'media': [{'id': 887473949361045505, 'id_str'...           58455   \n",
       "23    {'media': [{'id': 887343120832229379, 'id_str'...           28654   \n",
       "24    {'media': [{'id': 887101385971384320, 'id_str'...           26098   \n",
       "25    {'media': [{'id': 886983218871902208, 'id_str'...           29477   \n",
       "26    {'media': [{'id': 886736868116754432, 'id_str'...           10194   \n",
       "27    {'media': [{'id': 886680331239161856, 'id_str'...           19115   \n",
       "28    {'media': [{'id': 886366138128449536, 'id_str'...           17979   \n",
       "29                                                  NaN             101   \n",
       "...                                                 ...             ...   \n",
       "2296  {'media': [{'id': 666411498068123649, 'id_str'...             361   \n",
       "2297  {'media': [{'id': 666407121513275392, 'id_str'...              91   \n",
       "2298  {'media': [{'id': 666396240351993856, 'id_str'...             145   \n",
       "2299  {'media': [{'id': 666373746337402880, 'id_str'...             157   \n",
       "2300  {'media': [{'id': 666362717482020864, 'id_str'...             638   \n",
       "2301  {'media': [{'id': 666353280906170368, 'id_str'...             169   \n",
       "2302  {'media': [{'id': 666345414279471104, 'id_str'...             230   \n",
       "2303  {'media': [{'id': 666337857791987715, 'id_str'...             161   \n",
       "2304  {'media': [{'id': 666293909010702337, 'id_str'...             416   \n",
       "2305  {'media': [{'id': 666287399580733440, 'id_str'...             118   \n",
       "2306  {'media': [{'id': 666273081518768128, 'id_str'...             147   \n",
       "2307  {'media': [{'id': 666268904428277760, 'id_str'...              96   \n",
       "2308  {'media': [{'id': 666104129232740352, 'id_str'...           12513   \n",
       "2309  {'media': [{'id': 666102150364286977, 'id_str'...              62   \n",
       "2310  {'media': [{'id': 666099505364733952, 'id_str'...             131   \n",
       "2311  {'media': [{'id': 666093996847063040, 'id_str'...             138   \n",
       "2312  {'media': [{'id': 666082912819875840, 'id_str'...              89   \n",
       "2313  {'media': [{'id': 666073098362486784, 'id_str'...             270   \n",
       "2314  {'media': [{'id': 666071190449033216, 'id_str'...             124   \n",
       "2315  {'media': [{'id': 666063820255862784, 'id_str'...             387   \n",
       "2316  {'media': [{'id': 666058597072306176, 'id_str'...              96   \n",
       "2317  {'media': [{'id': 666057085227016192, 'id_str'...             243   \n",
       "2318  {'media': [{'id': 666055517517848576, 'id_str'...             359   \n",
       "2319  {'media': [{'id': 666051848592334848, 'id_str'...            1005   \n",
       "2320  {'media': [{'id': 666050754986266625, 'id_str'...             110   \n",
       "2321  {'media': [{'id': 666049244999131136, 'id_str'...              84   \n",
       "2322  {'media': [{'id': 666044217047650304, 'id_str'...             242   \n",
       "2323  {'media': [{'id': 666033409081393153, 'id_str'...              97   \n",
       "2324  {'media': [{'id': 666029276303482880, 'id_str'...             110   \n",
       "2325  {'media': [{'id': 666020881337073664, 'id_str'...            2225   \n",
       "\n",
       "      favorited                                          full_text  geo  \\\n",
       "0         False  This is Phineas. He's a mystical boy. Only eve...  NaN   \n",
       "1         False  This is Tilly. She's just checking pup on you....  NaN   \n",
       "2         False  This is Archie. He is a rare Norwegian Pouncin...  NaN   \n",
       "3         False  This is Darla. She commenced a snooze mid meal...  NaN   \n",
       "4         False  This is Franklin. He would like you to stop ca...  NaN   \n",
       "5         False  Here we have a majestic great white breaching ...  NaN   \n",
       "6         False  Meet Jax. He enjoys ice cream so much he gets ...  NaN   \n",
       "7         False  When you watch your owner call another dog a g...  NaN   \n",
       "8         False  This is Zoey. She doesn't want to be one of th...  NaN   \n",
       "9         False  This is Cassie. She is a college pup. Studying...  NaN   \n",
       "10        False  This is Koda. He is a South Australian decksha...  NaN   \n",
       "11        False  This is Bruno. He is a service shark. Only get...  NaN   \n",
       "12        False  Here's a puppo that seems to be on the fence a...  NaN   \n",
       "13        False  This is Ted. He does his best. Sometimes that'...  NaN   \n",
       "14        False  This is Stuart. He's sporting his favorite fan...  NaN   \n",
       "15        False  This is Oliver. You're witnessing one of his m...  NaN   \n",
       "16        False  This is Jim. He found a fren. Taught him how t...  NaN   \n",
       "17        False  This is Zeke. He has a new stick. Very proud o...  NaN   \n",
       "18        False  This is Ralphus. He's powering up. Attempting ...  NaN   \n",
       "19        False  This is Gerald. He was just told he didn't get...  NaN   \n",
       "20        False  This is Jeffrey. He has a monopoly on the pool...  NaN   \n",
       "21        False  I've yet to rate a Venezuelan Hover Wiener. Th...  NaN   \n",
       "22        False  This is Canela. She attempted some fancy porch...  NaN   \n",
       "23        False  You may not have known you needed to see this ...  NaN   \n",
       "24        False  This... is a Jubilant Antarctic House Bear. We...  NaN   \n",
       "25        False  This is Maya. She's very shy. Rarely leaves he...  NaN   \n",
       "26        False  This is Mingus. He's a wonderful father to his...  NaN   \n",
       "27        False  This is Derek. He's late for a dog meeting. 13...  NaN   \n",
       "28        False  This is Roscoe. Another pupper fallen victim t...  NaN   \n",
       "29        False  @NonWhiteHat @MayhewMayhem omg hello tanner yo...  NaN   \n",
       "...         ...                                                ...  ...   \n",
       "2296      False  This is quite the dog. Gets really excited whe...  NaN   \n",
       "2297      False  This is a southern Vesuvius bumblegruff. Can d...  NaN   \n",
       "2298      False  Oh goodness. A super rare northeast Qdoba kang...  NaN   \n",
       "2299      False  Those are sunglasses and a jean jacket. 11/10 ...  NaN   \n",
       "2300      False  Unique dog here. Very small. Lives in containe...  NaN   \n",
       "2301      False  Here we have a mixed Asiago from the Galápagos...  NaN   \n",
       "2302      False  Look at this jokester thinking seat belt laws ...  NaN   \n",
       "2303      False  This is an extremely rare horned Parthenon. No...  NaN   \n",
       "2304      False  This is a funny dog. Weird toes. Won't come do...  NaN   \n",
       "2305      False  This is an Albanian 3 1/2 legged  Episcopalian...  NaN   \n",
       "2306      False     Can take selfies 11/10 https://t.co/ws2AMaNwPW  NaN   \n",
       "2307      False  Very concerned about fellow dog trapped in com...  NaN   \n",
       "2308      False  Not familiar with this breed. No tail (weird)....  NaN   \n",
       "2309      False  Oh my. Here you are seeing an Adobe Setter giv...  NaN   \n",
       "2310      False  Can stand on stump for what seems like a while...  NaN   \n",
       "2311      False  This appears to be a Mongolian Presbyterian mi...  NaN   \n",
       "2312      False  Here we have a well-established sunblockerspan...  NaN   \n",
       "2313      False  Let's hope this flight isn't Malaysian (lol). ...  NaN   \n",
       "2314      False  Here we have a northern speckled Rhododendron....  NaN   \n",
       "2315      False  This is the happiest dog you will ever see. Ve...  NaN   \n",
       "2316      False  Here is the Rand Paul of retrievers folks! He'...  NaN   \n",
       "2317      False  My oh my. This is a rare blond Canadian terrie...  NaN   \n",
       "2318      False  Here is a Siberian heavily armored polar bear ...  NaN   \n",
       "2319      False  This is an odd dog. Hard on the outside but lo...  NaN   \n",
       "2320      False  This is a truly beautiful English Wilson Staff...  NaN   \n",
       "2321      False  Here we have a 1949 1st generation vulpix. Enj...  NaN   \n",
       "2322      False  This is a purebred Piers Morgan. Loves to Netf...  NaN   \n",
       "2323      False  Here is a very happy pup. Big fan of well-main...  NaN   \n",
       "2324      False  This is a western brown Mitsubishi terrier. Up...  NaN   \n",
       "2325      False  Here we have a Japanese Irish Setter. Lost eye...  NaN   \n",
       "\n",
       "                            ...                          quoted_status  \\\n",
       "0                           ...                                    NaN   \n",
       "1                           ...                                    NaN   \n",
       "2                           ...                                    NaN   \n",
       "3                           ...                                    NaN   \n",
       "4                           ...                                    NaN   \n",
       "5                           ...                                    NaN   \n",
       "6                           ...                                    NaN   \n",
       "7                           ...                                    NaN   \n",
       "8                           ...                                    NaN   \n",
       "9                           ...                                    NaN   \n",
       "10                          ...                                    NaN   \n",
       "11                          ...                                    NaN   \n",
       "12                          ...                                    NaN   \n",
       "13                          ...                                    NaN   \n",
       "14                          ...                                    NaN   \n",
       "15                          ...                                    NaN   \n",
       "16                          ...                                    NaN   \n",
       "17                          ...                                    NaN   \n",
       "18                          ...                                    NaN   \n",
       "19                          ...                                    NaN   \n",
       "20                          ...                                    NaN   \n",
       "21                          ...                                    NaN   \n",
       "22                          ...                                    NaN   \n",
       "23                          ...                                    NaN   \n",
       "24                          ...                                    NaN   \n",
       "25                          ...                                    NaN   \n",
       "26                          ...                                    NaN   \n",
       "27                          ...                                    NaN   \n",
       "28                          ...                                    NaN   \n",
       "29                          ...                                    NaN   \n",
       "...                         ...                                    ...   \n",
       "2296                        ...                                    NaN   \n",
       "2297                        ...                                    NaN   \n",
       "2298                        ...                                    NaN   \n",
       "2299                        ...                                    NaN   \n",
       "2300                        ...                                    NaN   \n",
       "2301                        ...                                    NaN   \n",
       "2302                        ...                                    NaN   \n",
       "2303                        ...                                    NaN   \n",
       "2304                        ...                                    NaN   \n",
       "2305                        ...                                    NaN   \n",
       "2306                        ...                                    NaN   \n",
       "2307                        ...                                    NaN   \n",
       "2308                        ...                                    NaN   \n",
       "2309                        ...                                    NaN   \n",
       "2310                        ...                                    NaN   \n",
       "2311                        ...                                    NaN   \n",
       "2312                        ...                                    NaN   \n",
       "2313                        ...                                    NaN   \n",
       "2314                        ...                                    NaN   \n",
       "2315                        ...                                    NaN   \n",
       "2316                        ...                                    NaN   \n",
       "2317                        ...                                    NaN   \n",
       "2318                        ...                                    NaN   \n",
       "2319                        ...                                    NaN   \n",
       "2320                        ...                                    NaN   \n",
       "2321                        ...                                    NaN   \n",
       "2322                        ...                                    NaN   \n",
       "2323                        ...                                    NaN   \n",
       "2324                        ...                                    NaN   \n",
       "2325                        ...                                    NaN   \n",
       "\n",
       "      quoted_status_id quoted_status_id_str  quoted_status_permalink  \\\n",
       "0                  NaN                  NaN                      NaN   \n",
       "1                  NaN                  NaN                      NaN   \n",
       "2                  NaN                  NaN                      NaN   \n",
       "3                  NaN                  NaN                      NaN   \n",
       "4                  NaN                  NaN                      NaN   \n",
       "5                  NaN                  NaN                      NaN   \n",
       "6                  NaN                  NaN                      NaN   \n",
       "7                  NaN                  NaN                      NaN   \n",
       "8                  NaN                  NaN                      NaN   \n",
       "9                  NaN                  NaN                      NaN   \n",
       "10                 NaN                  NaN                      NaN   \n",
       "11                 NaN                  NaN                      NaN   \n",
       "12                 NaN                  NaN                      NaN   \n",
       "13                 NaN                  NaN                      NaN   \n",
       "14                 NaN                  NaN                      NaN   \n",
       "15                 NaN                  NaN                      NaN   \n",
       "16                 NaN                  NaN                      NaN   \n",
       "17                 NaN                  NaN                      NaN   \n",
       "18                 NaN                  NaN                      NaN   \n",
       "19                 NaN                  NaN                      NaN   \n",
       "20                 NaN                  NaN                      NaN   \n",
       "21                 NaN                  NaN                      NaN   \n",
       "22                 NaN                  NaN                      NaN   \n",
       "23                 NaN                  NaN                      NaN   \n",
       "24                 NaN                  NaN                      NaN   \n",
       "25                 NaN                  NaN                      NaN   \n",
       "26                 NaN                  NaN                      NaN   \n",
       "27                 NaN                  NaN                      NaN   \n",
       "28                 NaN                  NaN                      NaN   \n",
       "29                 NaN                  NaN                      NaN   \n",
       "...                ...                  ...                      ...   \n",
       "2296               NaN                  NaN                      NaN   \n",
       "2297               NaN                  NaN                      NaN   \n",
       "2298               NaN                  NaN                      NaN   \n",
       "2299               NaN                  NaN                      NaN   \n",
       "2300               NaN                  NaN                      NaN   \n",
       "2301               NaN                  NaN                      NaN   \n",
       "2302               NaN                  NaN                      NaN   \n",
       "2303               NaN                  NaN                      NaN   \n",
       "2304               NaN                  NaN                      NaN   \n",
       "2305               NaN                  NaN                      NaN   \n",
       "2306               NaN                  NaN                      NaN   \n",
       "2307               NaN                  NaN                      NaN   \n",
       "2308               NaN                  NaN                      NaN   \n",
       "2309               NaN                  NaN                      NaN   \n",
       "2310               NaN                  NaN                      NaN   \n",
       "2311               NaN                  NaN                      NaN   \n",
       "2312               NaN                  NaN                      NaN   \n",
       "2313               NaN                  NaN                      NaN   \n",
       "2314               NaN                  NaN                      NaN   \n",
       "2315               NaN                  NaN                      NaN   \n",
       "2316               NaN                  NaN                      NaN   \n",
       "2317               NaN                  NaN                      NaN   \n",
       "2318               NaN                  NaN                      NaN   \n",
       "2319               NaN                  NaN                      NaN   \n",
       "2320               NaN                  NaN                      NaN   \n",
       "2321               NaN                  NaN                      NaN   \n",
       "2322               NaN                  NaN                      NaN   \n",
       "2323               NaN                  NaN                      NaN   \n",
       "2324               NaN                  NaN                      NaN   \n",
       "2325               NaN                  NaN                      NaN   \n",
       "\n",
       "      retweet_count  retweeted  retweeted_status  \\\n",
       "0              6848      False               NaN   \n",
       "1              5159      False               NaN   \n",
       "2              3404      False               NaN   \n",
       "3              7059      False               NaN   \n",
       "4              7569      False               NaN   \n",
       "5              2540      False               NaN   \n",
       "6              1615      False               NaN   \n",
       "7             15394      False               NaN   \n",
       "8              3546      False               NaN   \n",
       "9              5958      False               NaN   \n",
       "10             6004      False               NaN   \n",
       "11             4054      False               NaN   \n",
       "12             8164      False               NaN   \n",
       "13             3635      False               NaN   \n",
       "14             1848      False               NaN   \n",
       "15             4343      False               NaN   \n",
       "16             3676      False               NaN   \n",
       "17             3452      False               NaN   \n",
       "18             2829      False               NaN   \n",
       "19             2832      False               NaN   \n",
       "20             4422      False               NaN   \n",
       "21             9595      False               NaN   \n",
       "22            14691      False               NaN   \n",
       "23             8567      False               NaN   \n",
       "24             4870      False               NaN   \n",
       "25             6166      False               NaN   \n",
       "26             2562      False               NaN   \n",
       "27             3657      False               NaN   \n",
       "28             2559      False               NaN   \n",
       "29                4      False               NaN   \n",
       "...             ...        ...               ...   \n",
       "2296            257      False               NaN   \n",
       "2297             30      False               NaN   \n",
       "2298             66      False               NaN   \n",
       "2299             72      False               NaN   \n",
       "2300            462      False               NaN   \n",
       "2301             56      False               NaN   \n",
       "2302            120      False               NaN   \n",
       "2303             78      False               NaN   \n",
       "2304            287      False               NaN   \n",
       "2305             54      False               NaN   \n",
       "2306             66      False               NaN   \n",
       "2307             38      False               NaN   \n",
       "2308           5356      False               NaN   \n",
       "2309             11      False               NaN   \n",
       "2310             53      False               NaN   \n",
       "2311             63      False               NaN   \n",
       "2312             37      False               NaN   \n",
       "2313            129      False               NaN   \n",
       "2314             49      False               NaN   \n",
       "2315            178      False               NaN   \n",
       "2316             46      False               NaN   \n",
       "2317            111      False               NaN   \n",
       "2318            193      False               NaN   \n",
       "2319            685      False               NaN   \n",
       "2320             49      False               NaN   \n",
       "2321             35      False               NaN   \n",
       "2322            113      False               NaN   \n",
       "2323             35      False               NaN   \n",
       "2324             39      False               NaN   \n",
       "2325            416      False               NaN   \n",
       "\n",
       "                                                 source truncated  \\\n",
       "0     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "1     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "3     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "4     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "5     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "6     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "7     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "8     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "9     <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "10    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "11    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "12    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "13    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "14    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "15    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "16    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "17    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "18    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "19    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "20    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "21    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "22    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "23    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "24    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "25    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "26    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "27    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "28    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "29    <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "...                                                 ...       ...   \n",
       "2296  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2297  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2298  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2299  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2300  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2301  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2302  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2303  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2304  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2305  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2306  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2307  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2308  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2309  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2310  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2311  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2312  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2313  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2314  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2315  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2316  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2317  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2318  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2319  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2320  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2321  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2322  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2323  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2324  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "2325  <a href=\"http://twitter.com/download/iphone\" r...     False   \n",
       "\n",
       "                                                   user  \n",
       "0     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "1     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "3     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "4     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "5     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "6     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "7     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "8     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "9     {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "10    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "11    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "12    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "13    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "14    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "15    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "16    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "17    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "18    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "19    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "20    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "21    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "22    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "23    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "24    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "25    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "26    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "27    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "28    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "29    {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "...                                                 ...  \n",
       "2296  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2297  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2298  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2299  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2300  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2301  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2302  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2303  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2304  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2305  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2306  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2307  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2308  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2309  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2310  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2311  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2312  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2313  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2314  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2315  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2316  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2317  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2318  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2319  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2320  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2321  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2322  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2323  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2324  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2325  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "\n",
       "[2326 rows x 32 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Output df_3 dataset\n",
    "df_3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2356 entries, 0 to 2355\n",
      "Data columns (total 17 columns):\n",
      "tweet_id                      2356 non-null int64\n",
      "in_reply_to_status_id         78 non-null float64\n",
      "in_reply_to_user_id           78 non-null float64\n",
      "timestamp                     2356 non-null object\n",
      "source                        2356 non-null object\n",
      "text                          2356 non-null object\n",
      "retweeted_status_id           181 non-null float64\n",
      "retweeted_status_user_id      181 non-null float64\n",
      "retweeted_status_timestamp    181 non-null object\n",
      "expanded_urls                 2297 non-null object\n",
      "rating_numerator              2356 non-null int64\n",
      "rating_denominator            2356 non-null int64\n",
      "name                          2356 non-null object\n",
      "doggo                         2356 non-null object\n",
      "floofer                       2356 non-null object\n",
      "pupper                        2356 non-null object\n",
      "puppo                         2356 non-null object\n",
      "dtypes: float64(4), int64(3), object(10)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# Check info\n",
    "df_1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2075 entries, 0 to 2074\n",
      "Data columns (total 12 columns):\n",
      "tweet_id    2075 non-null int64\n",
      "jpg_url     2075 non-null object\n",
      "img_num     2075 non-null int64\n",
      "p1          2075 non-null object\n",
      "p1_conf     2075 non-null float64\n",
      "p1_dog      2075 non-null bool\n",
      "p2          2075 non-null object\n",
      "p2_conf     2075 non-null float64\n",
      "p2_dog      2075 non-null bool\n",
      "p3          2075 non-null object\n",
      "p3_conf     2075 non-null float64\n",
      "p3_dog      2075 non-null bool\n",
      "dtypes: bool(3), float64(3), int64(2), object(4)\n",
      "memory usage: 152.1+ KB\n"
     ]
    }
   ],
   "source": [
    "# Check info\n",
    "df_2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2326 entries, 0 to 2325\n",
      "Data columns (total 32 columns):\n",
      "contributors                     0 non-null float64\n",
      "coordinates                      0 non-null float64\n",
      "created_at                       2326 non-null datetime64[ns]\n",
      "display_text_range               2326 non-null object\n",
      "entities                         2326 non-null object\n",
      "extended_entities                2056 non-null object\n",
      "favorite_count                   2326 non-null int64\n",
      "favorited                        2326 non-null bool\n",
      "full_text                        2326 non-null object\n",
      "geo                              0 non-null float64\n",
      "id                               2326 non-null int64\n",
      "id_str                           2326 non-null int64\n",
      "in_reply_to_screen_name          77 non-null object\n",
      "in_reply_to_status_id            77 non-null float64\n",
      "in_reply_to_status_id_str        77 non-null float64\n",
      "in_reply_to_user_id              77 non-null float64\n",
      "in_reply_to_user_id_str          77 non-null float64\n",
      "is_quote_status                  2326 non-null bool\n",
      "lang                             2326 non-null object\n",
      "place                            1 non-null object\n",
      "possibly_sensitive               2194 non-null float64\n",
      "possibly_sensitive_appealable    2194 non-null float64\n",
      "quoted_status                    22 non-null object\n",
      "quoted_status_id                 25 non-null float64\n",
      "quoted_status_id_str             25 non-null float64\n",
      "quoted_status_permalink          25 non-null object\n",
      "retweet_count                    2326 non-null int64\n",
      "retweeted                        2326 non-null bool\n",
      "retweeted_status                 159 non-null object\n",
      "source                           2326 non-null object\n",
      "truncated                        2326 non-null bool\n",
      "user                             2326 non-null object\n",
      "dtypes: bool(4), datetime64[ns](1), float64(11), int64(4), object(12)\n",
      "memory usage: 518.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# Check info\n",
    "df_3.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.356000e+03</td>\n",
       "      <td>7.800000e+01</td>\n",
       "      <td>7.800000e+01</td>\n",
       "      <td>1.810000e+02</td>\n",
       "      <td>1.810000e+02</td>\n",
       "      <td>2356.000000</td>\n",
       "      <td>2356.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.427716e+17</td>\n",
       "      <td>7.455079e+17</td>\n",
       "      <td>2.014171e+16</td>\n",
       "      <td>7.720400e+17</td>\n",
       "      <td>1.241698e+16</td>\n",
       "      <td>13.126486</td>\n",
       "      <td>10.455433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.856705e+16</td>\n",
       "      <td>7.582492e+16</td>\n",
       "      <td>1.252797e+17</td>\n",
       "      <td>6.236928e+16</td>\n",
       "      <td>9.599254e+16</td>\n",
       "      <td>45.876648</td>\n",
       "      <td>6.745237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>6.660209e+17</td>\n",
       "      <td>6.658147e+17</td>\n",
       "      <td>1.185634e+07</td>\n",
       "      <td>6.661041e+17</td>\n",
       "      <td>7.832140e+05</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.783989e+17</td>\n",
       "      <td>6.757419e+17</td>\n",
       "      <td>3.086374e+08</td>\n",
       "      <td>7.186315e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.196279e+17</td>\n",
       "      <td>7.038708e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>7.804657e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.993373e+17</td>\n",
       "      <td>8.257804e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>8.203146e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8.924206e+17</td>\n",
       "      <td>8.862664e+17</td>\n",
       "      <td>8.405479e+17</td>\n",
       "      <td>8.874740e+17</td>\n",
       "      <td>7.874618e+17</td>\n",
       "      <td>1776.000000</td>\n",
       "      <td>170.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "count  2.356000e+03           7.800000e+01         7.800000e+01   \n",
       "mean   7.427716e+17           7.455079e+17         2.014171e+16   \n",
       "std    6.856705e+16           7.582492e+16         1.252797e+17   \n",
       "min    6.660209e+17           6.658147e+17         1.185634e+07   \n",
       "25%    6.783989e+17           6.757419e+17         3.086374e+08   \n",
       "50%    7.196279e+17           7.038708e+17         4.196984e+09   \n",
       "75%    7.993373e+17           8.257804e+17         4.196984e+09   \n",
       "max    8.924206e+17           8.862664e+17         8.405479e+17   \n",
       "\n",
       "       retweeted_status_id  retweeted_status_user_id  rating_numerator  \\\n",
       "count         1.810000e+02              1.810000e+02       2356.000000   \n",
       "mean          7.720400e+17              1.241698e+16         13.126486   \n",
       "std           6.236928e+16              9.599254e+16         45.876648   \n",
       "min           6.661041e+17              7.832140e+05          0.000000   \n",
       "25%           7.186315e+17              4.196984e+09         10.000000   \n",
       "50%           7.804657e+17              4.196984e+09         11.000000   \n",
       "75%           8.203146e+17              4.196984e+09         12.000000   \n",
       "max           8.874740e+17              7.874618e+17       1776.000000   \n",
       "\n",
       "       rating_denominator  \n",
       "count         2356.000000  \n",
       "mean            10.455433  \n",
       "std              6.745237  \n",
       "min              0.000000  \n",
       "25%             10.000000  \n",
       "50%             10.000000  \n",
       "75%             10.000000  \n",
       "max            170.000000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the summary statistics of df_1\n",
    "df_1.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p3_conf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.075000e+03</td>\n",
       "      <td>2075.000000</td>\n",
       "      <td>2075.000000</td>\n",
       "      <td>2.075000e+03</td>\n",
       "      <td>2.075000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.384514e+17</td>\n",
       "      <td>1.203855</td>\n",
       "      <td>0.594548</td>\n",
       "      <td>1.345886e-01</td>\n",
       "      <td>6.032417e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.785203e+16</td>\n",
       "      <td>0.561875</td>\n",
       "      <td>0.271174</td>\n",
       "      <td>1.006657e-01</td>\n",
       "      <td>5.090593e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>6.660209e+17</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.044333</td>\n",
       "      <td>1.011300e-08</td>\n",
       "      <td>1.740170e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.764835e+17</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.364412</td>\n",
       "      <td>5.388625e-02</td>\n",
       "      <td>1.622240e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.119988e+17</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.588230</td>\n",
       "      <td>1.181810e-01</td>\n",
       "      <td>4.944380e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.932034e+17</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.843855</td>\n",
       "      <td>1.955655e-01</td>\n",
       "      <td>9.180755e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8.924206e+17</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.880140e-01</td>\n",
       "      <td>2.734190e-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           tweet_id      img_num      p1_conf       p2_conf       p3_conf\n",
       "count  2.075000e+03  2075.000000  2075.000000  2.075000e+03  2.075000e+03\n",
       "mean   7.384514e+17     1.203855     0.594548  1.345886e-01  6.032417e-02\n",
       "std    6.785203e+16     0.561875     0.271174  1.006657e-01  5.090593e-02\n",
       "min    6.660209e+17     1.000000     0.044333  1.011300e-08  1.740170e-10\n",
       "25%    6.764835e+17     1.000000     0.364412  5.388625e-02  1.622240e-02\n",
       "50%    7.119988e+17     1.000000     0.588230  1.181810e-01  4.944380e-02\n",
       "75%    7.932034e+17     1.000000     0.843855  1.955655e-01  9.180755e-02\n",
       "max    8.924206e+17     4.000000     1.000000  4.880140e-01  2.734190e-01"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the summary statistics of df_2\n",
    "df_2.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>contributors</th>\n",
       "      <th>coordinates</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>geo</th>\n",
       "      <th>id</th>\n",
       "      <th>id_str</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_status_id_str</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>in_reply_to_user_id_str</th>\n",
       "      <th>possibly_sensitive</th>\n",
       "      <th>possibly_sensitive_appealable</th>\n",
       "      <th>quoted_status_id</th>\n",
       "      <th>quoted_status_id_str</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2326.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.326000e+03</td>\n",
       "      <td>2.326000e+03</td>\n",
       "      <td>7.700000e+01</td>\n",
       "      <td>7.700000e+01</td>\n",
       "      <td>7.700000e+01</td>\n",
       "      <td>7.700000e+01</td>\n",
       "      <td>2194.0</td>\n",
       "      <td>2194.0</td>\n",
       "      <td>2.500000e+01</td>\n",
       "      <td>2.500000e+01</td>\n",
       "      <td>2326.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6849.752794</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.417346e+17</td>\n",
       "      <td>7.417346e+17</td>\n",
       "      <td>7.440692e+17</td>\n",
       "      <td>7.440692e+17</td>\n",
       "      <td>2.040329e+16</td>\n",
       "      <td>2.040329e+16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.111370e+17</td>\n",
       "      <td>8.111370e+17</td>\n",
       "      <td>2414.567928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10642.285840</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.816442e+16</td>\n",
       "      <td>6.816442e+16</td>\n",
       "      <td>7.524295e+16</td>\n",
       "      <td>7.524295e+16</td>\n",
       "      <td>1.260797e+17</td>\n",
       "      <td>1.260797e+17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.424241e+16</td>\n",
       "      <td>6.424241e+16</td>\n",
       "      <td>4087.595207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.660209e+17</td>\n",
       "      <td>6.660209e+17</td>\n",
       "      <td>6.658147e+17</td>\n",
       "      <td>6.658147e+17</td>\n",
       "      <td>1.185634e+07</td>\n",
       "      <td>1.185634e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.721083e+17</td>\n",
       "      <td>6.721083e+17</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1193.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.780814e+17</td>\n",
       "      <td>6.780814e+17</td>\n",
       "      <td>6.757073e+17</td>\n",
       "      <td>6.757073e+17</td>\n",
       "      <td>3.589728e+08</td>\n",
       "      <td>3.589728e+08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.719056e+17</td>\n",
       "      <td>7.719056e+17</td>\n",
       "      <td>486.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2964.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.178159e+17</td>\n",
       "      <td>7.178159e+17</td>\n",
       "      <td>7.032559e+17</td>\n",
       "      <td>7.032559e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.322683e+17</td>\n",
       "      <td>8.322683e+17</td>\n",
       "      <td>1123.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8375.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.986402e+17</td>\n",
       "      <td>7.986402e+17</td>\n",
       "      <td>8.233264e+17</td>\n",
       "      <td>8.233264e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.664587e+17</td>\n",
       "      <td>8.664587e+17</td>\n",
       "      <td>2794.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>141282.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.924206e+17</td>\n",
       "      <td>8.924206e+17</td>\n",
       "      <td>8.862664e+17</td>\n",
       "      <td>8.862664e+17</td>\n",
       "      <td>8.405479e+17</td>\n",
       "      <td>8.405479e+17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.860534e+17</td>\n",
       "      <td>8.860534e+17</td>\n",
       "      <td>69120.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       contributors  coordinates  favorite_count  geo            id  \\\n",
       "count           0.0          0.0     2326.000000  0.0  2.326000e+03   \n",
       "mean            NaN          NaN     6849.752794  NaN  7.417346e+17   \n",
       "std             NaN          NaN    10642.285840  NaN  6.816442e+16   \n",
       "min             NaN          NaN        0.000000  NaN  6.660209e+17   \n",
       "25%             NaN          NaN     1193.250000  NaN  6.780814e+17   \n",
       "50%             NaN          NaN     2964.000000  NaN  7.178159e+17   \n",
       "75%             NaN          NaN     8375.000000  NaN  7.986402e+17   \n",
       "max             NaN          NaN   141282.000000  NaN  8.924206e+17   \n",
       "\n",
       "             id_str  in_reply_to_status_id  in_reply_to_status_id_str  \\\n",
       "count  2.326000e+03           7.700000e+01               7.700000e+01   \n",
       "mean   7.417346e+17           7.440692e+17               7.440692e+17   \n",
       "std    6.816442e+16           7.524295e+16               7.524295e+16   \n",
       "min    6.660209e+17           6.658147e+17               6.658147e+17   \n",
       "25%    6.780814e+17           6.757073e+17               6.757073e+17   \n",
       "50%    7.178159e+17           7.032559e+17               7.032559e+17   \n",
       "75%    7.986402e+17           8.233264e+17               8.233264e+17   \n",
       "max    8.924206e+17           8.862664e+17               8.862664e+17   \n",
       "\n",
       "       in_reply_to_user_id  in_reply_to_user_id_str  possibly_sensitive  \\\n",
       "count         7.700000e+01             7.700000e+01              2194.0   \n",
       "mean          2.040329e+16             2.040329e+16                 0.0   \n",
       "std           1.260797e+17             1.260797e+17                 0.0   \n",
       "min           1.185634e+07             1.185634e+07                 0.0   \n",
       "25%           3.589728e+08             3.589728e+08                 0.0   \n",
       "50%           4.196984e+09             4.196984e+09                 0.0   \n",
       "75%           4.196984e+09             4.196984e+09                 0.0   \n",
       "max           8.405479e+17             8.405479e+17                 0.0   \n",
       "\n",
       "       possibly_sensitive_appealable  quoted_status_id  quoted_status_id_str  \\\n",
       "count                         2194.0      2.500000e+01          2.500000e+01   \n",
       "mean                             0.0      8.111370e+17          8.111370e+17   \n",
       "std                              0.0      6.424241e+16          6.424241e+16   \n",
       "min                              0.0      6.721083e+17          6.721083e+17   \n",
       "25%                              0.0      7.719056e+17          7.719056e+17   \n",
       "50%                              0.0      8.322683e+17          8.322683e+17   \n",
       "75%                              0.0      8.664587e+17          8.664587e+17   \n",
       "max                              0.0      8.860534e+17          8.860534e+17   \n",
       "\n",
       "       retweet_count  \n",
       "count    2326.000000  \n",
       "mean     2414.567928  \n",
       "std      4087.595207  \n",
       "min         0.000000  \n",
       "25%       486.000000  \n",
       "50%      1123.000000  \n",
       "75%      2794.500000  \n",
       "max     69120.000000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the summary statistics of df_3\n",
    "df_3.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None          745\n",
       "a              55\n",
       "Charlie        12\n",
       "Cooper         11\n",
       "Oliver         11\n",
       "Lucy           11\n",
       "Tucker         10\n",
       "Penny          10\n",
       "Lola           10\n",
       "Bo              9\n",
       "Winston         9\n",
       "Sadie           8\n",
       "the             8\n",
       "Bailey          7\n",
       "Toby            7\n",
       "an              7\n",
       "Buddy           7\n",
       "Daisy           7\n",
       "Jax             6\n",
       "Koda            6\n",
       "Rusty           6\n",
       "Jack            6\n",
       "Oscar           6\n",
       "Scout           6\n",
       "Dave            6\n",
       "Milo            6\n",
       "Leo             6\n",
       "Bella           6\n",
       "Stanley         6\n",
       "Bentley         5\n",
       "             ... \n",
       "Glacier         1\n",
       "Timmy           1\n",
       "Raphael         1\n",
       "Izzy            1\n",
       "Rupert          1\n",
       "Skittle         1\n",
       "this            1\n",
       "Edd             1\n",
       "Trigger         1\n",
       "Rumble          1\n",
       "Chesterson      1\n",
       "River           1\n",
       "Aqua            1\n",
       "Biden           1\n",
       "Darby           1\n",
       "Hanz            1\n",
       "Tater           1\n",
       "Yukon           1\n",
       "Alejandro       1\n",
       "Gòrdón          1\n",
       "Diogi           1\n",
       "Jarvis          1\n",
       "such            1\n",
       "Deacon          1\n",
       "Reptar          1\n",
       "Naphaniel       1\n",
       "Dallas          1\n",
       "space           1\n",
       "Mollie          1\n",
       "Kollin          1\n",
       "Name: name, Length: 957, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the value_counts of name column\n",
    "df_1.name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
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       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>891087950875897856</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 00:08:17 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a majestic great white breaching ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891087950...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>890729181411237888</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-28 00:22:40 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>When you watch your owner call another dog a g...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890729181...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>889665388333682689</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 01:55:32 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here's a puppo that seems to be on the fence a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889665388...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>puppo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>887343217045368832</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-18 16:08:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>You may not have known you needed to see this ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887343217...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>887101392804085760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-18 00:07:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This... is a Jubilant Antarctic House Bear. We...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887101392...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>886267009285017600</td>\n",
       "      <td>8.862664e+17</td>\n",
       "      <td>2.281182e+09</td>\n",
       "      <td>2017-07-15 16:51:35 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>@NonWhiteHat @MayhewMayhem omg hello tanner yo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>886054160059072513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-15 02:45:48 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @Athletics: 12/10 #BATP https://t.co/WxwJmv...</td>\n",
       "      <td>8.860537e+17</td>\n",
       "      <td>19607400.0</td>\n",
       "      <td>2017-07-15 02:44:07 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/886053434...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>885518971528720385</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-13 15:19:09 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>I have a new hero and his name is Howard. 14/1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/4bonds2carbon/status/88551...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>885167619883638784</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-12 16:03:00 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a corgi undercover as a malamute....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/885167619...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>884441805382717440</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-10 15:58:53 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>I present to you, Pup in Hat. Pup in Hat is gr...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/884441805...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>884247878851493888</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-10 03:08:17 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>OMG HE DIDN'T MEAN TO HE WAS JUST TRYING A LIT...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/kaijohnson_19/status/88396...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>883117836046086144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-07 00:17:54 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Please only send dogs. We don't rate mechanics...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/883117836...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>881633300179243008</td>\n",
       "      <td>8.816070e+17</td>\n",
       "      <td>4.738443e+07</td>\n",
       "      <td>2017-07-02 21:58:53 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>@roushfenway These are good dogs but 17/10 is ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>880872448815771648</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-30 19:35:32 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Ugh not again. We only rate dogs. Please don't...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/880872448...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>880095782870896641</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-28 16:09:20 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Please don't send in photos without dogs in th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/880095782...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>879674319642796034</td>\n",
       "      <td>8.795538e+17</td>\n",
       "      <td>3.105441e+09</td>\n",
       "      <td>2017-06-27 12:14:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>@RealKentMurphy 14/10 confirmed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>878604707211726852</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-24 13:24:20 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Martha is stunning how h*ckin dare you. 13/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/bbcworld/status/8785998685...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>877611172832227328</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-21 19:36:23 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @rachel2195: @dog_rates the boyfriend and h...</td>\n",
       "      <td>8.768508e+17</td>\n",
       "      <td>512804507.0</td>\n",
       "      <td>2017-06-19 17:14:49 +0000</td>\n",
       "      <td>https://twitter.com/rachel2195/status/87685077...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>876537666061221889</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-18 20:30:39 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>I can say with the pupmost confidence that the...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/mpstowerham/status/8761629...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>875097192612077568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-14 21:06:43 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>You'll get your package when that precious man...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/drboondoc/status/874413398...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>875021211251597312</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-14 16:04:48 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Guys please stop sending pictures without any ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/875021211...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>874057562936811520</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-12 00:15:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>I can't believe this keeps happening. This, is...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/874057562...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>873580283840344065</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-10 16:39:04 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>We usually don't rate Deck-bound Saskatoon Bla...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/873580283...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>872967104147763200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-09 00:02:31 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here's a very large dog. He has a date later. ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/872967104...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>872820683541237760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-08 14:20:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here are my favorite #dogsatpollingstations \\n...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/872820683...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>872668790621863937</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-08 04:17:07 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @loganamnosis: Penelope here is doing me qu...</td>\n",
       "      <td>8.726576e+17</td>\n",
       "      <td>154767397.0</td>\n",
       "      <td>2017-06-08 03:32:35 +0000</td>\n",
       "      <td>https://twitter.com/loganamnosis/status/872657...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>872486979161796608</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-07 16:14:40 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>We. Only. Rate. Dogs. Do not send in other thi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/872486979...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>871102520638267392</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-03 20:33:19 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Never doubt a doggo 14/10 https://t.co/AbBLh2FZCH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/animalcog/status/871075758...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>870804317367881728</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-03 00:48:22 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Real funny guys. Sending in a pic without a do...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/870804317...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>870726314365509632</td>\n",
       "      <td>8.707262e+17</td>\n",
       "      <td>1.648776e+07</td>\n",
       "      <td>2017-06-02 19:38:25 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>@ComplicitOwl @ShopWeRateDogs &amp;gt;10/10 is res...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2294</th>\n",
       "      <td>667138269671505920</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-19 00:32:12 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Extremely intelligent dog here. Has learned to...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/667138269...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2298</th>\n",
       "      <td>667070482143944705</td>\n",
       "      <td>6.670655e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2015-11-18 20:02:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>After much debate this dog is being upgraded t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2299</th>\n",
       "      <td>667065535570550784</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-18 19:43:11 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a Hufflepuff. Loves vest. Eyes wi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/667065535...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2301</th>\n",
       "      <td>667044094246576128</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-18 18:17:59 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>12/10 gimme now https://t.co/QZAnwgnOMB</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/667044094...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2305</th>\n",
       "      <td>666837028449972224</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-18 04:35:11 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>My goodness. Very rare dog here. Large. Tail d...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666837028...</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2306</th>\n",
       "      <td>666835007768551424</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-18 04:27:09 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>These are Peruvian Feldspars. Their names are ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666835007...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2307</th>\n",
       "      <td>666826780179869698</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-18 03:54:28 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>12/10 simply brilliant pup https://t.co/V6ZzG4...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666826780...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2310</th>\n",
       "      <td>666786068205871104</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-18 01:12:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Unfamiliar with this breed. Ears pointy af. Wo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666786068...</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2316</th>\n",
       "      <td>666649482315059201</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 16:09:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Cool dog. Enjoys couch. Low monotone bark. Ver...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666649482...</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2320</th>\n",
       "      <td>666437273139982337</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 02:06:42 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we see a lone northeastern Cumberbatch. H...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666437273...</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2321</th>\n",
       "      <td>666435652385423360</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 02:00:15 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>\"Can you behave? You're ruining my wedding day...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666435652...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2322</th>\n",
       "      <td>666430724426358785</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 01:40:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Oh boy what a pup! Sunglasses take this one to...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666430724...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2323</th>\n",
       "      <td>666428276349472768</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 01:30:57 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have an Austrian Pulitzer. Collectors ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666428276...</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2324</th>\n",
       "      <td>666421158376562688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 01:02:40 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>*internally screaming* 12/10 https://t.co/YMcr...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666421158...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2328</th>\n",
       "      <td>666396247373291520</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 23:23:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Oh goodness. A super rare northeast Qdoba kang...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666396247...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2329</th>\n",
       "      <td>666373753744588802</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 21:54:18 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Those are sunglasses and a jean jacket. 11/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666373753...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2330</th>\n",
       "      <td>666362758909284353</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 21:10:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Unique dog here. Very small. Lives in containe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666362758...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2331</th>\n",
       "      <td>666353288456101888</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 20:32:58 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a mixed Asiago from the Galápagos...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666353288...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2332</th>\n",
       "      <td>666345417576210432</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 20:01:42 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Look at this jokester thinking seat belt laws ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666345417...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2336</th>\n",
       "      <td>666273097616637952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 15:14:19 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Can take selfies 11/10 https://t.co/ws2AMaNwPW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666273097...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2337</th>\n",
       "      <td>666268910803644416</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 14:57:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Very concerned about fellow dog trapped in com...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666268910...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2338</th>\n",
       "      <td>666104133288665088</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 04:02:55 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Not familiar with this breed. No tail (weird)....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666104133...</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2339</th>\n",
       "      <td>666102155909144576</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:55:04 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Oh my. Here you are seeing an Adobe Setter giv...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666102155...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2340</th>\n",
       "      <td>666099513787052032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:44:34 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Can stand on stump for what seems like a while...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666099513...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2341</th>\n",
       "      <td>666094000022159362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:22:39 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This appears to be a Mongolian Presbyterian mi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666094000...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2342</th>\n",
       "      <td>666082916733198337</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 02:38:37 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a well-established sunblockerspan...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666082916...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2343</th>\n",
       "      <td>666073100786774016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:59:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Let's hope this flight isn't Malaysian (lol). ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666073100...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2344</th>\n",
       "      <td>666071193221509120</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:52:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a northern speckled Rhododendron....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666071193...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2351</th>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:24:50 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a 1949 1st generation vulpix. Enj...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666049248...</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2355</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 22:32:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a Japanese Irish Setter. Lost eye...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666020888...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>745 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "5     891087950875897856                    NaN                  NaN   \n",
       "7     890729181411237888                    NaN                  NaN   \n",
       "12    889665388333682689                    NaN                  NaN   \n",
       "24    887343217045368832                    NaN                  NaN   \n",
       "25    887101392804085760                    NaN                  NaN   \n",
       "30    886267009285017600           8.862664e+17         2.281182e+09   \n",
       "32    886054160059072513                    NaN                  NaN   \n",
       "35    885518971528720385                    NaN                  NaN   \n",
       "37    885167619883638784                    NaN                  NaN   \n",
       "41    884441805382717440                    NaN                  NaN   \n",
       "42    884247878851493888                    NaN                  NaN   \n",
       "47    883117836046086144                    NaN                  NaN   \n",
       "55    881633300179243008           8.816070e+17         4.738443e+07   \n",
       "59    880872448815771648                    NaN                  NaN   \n",
       "62    880095782870896641                    NaN                  NaN   \n",
       "64    879674319642796034           8.795538e+17         3.105441e+09   \n",
       "72    878604707211726852                    NaN                  NaN   \n",
       "78    877611172832227328                    NaN                  NaN   \n",
       "83    876537666061221889                    NaN                  NaN   \n",
       "88    875097192612077568                    NaN                  NaN   \n",
       "89    875021211251597312                    NaN                  NaN   \n",
       "93    874057562936811520                    NaN                  NaN   \n",
       "96    873580283840344065                    NaN                  NaN   \n",
       "99    872967104147763200                    NaN                  NaN   \n",
       "100   872820683541237760                    NaN                  NaN   \n",
       "101   872668790621863937                    NaN                  NaN   \n",
       "103   872486979161796608                    NaN                  NaN   \n",
       "110   871102520638267392                    NaN                  NaN   \n",
       "112   870804317367881728                    NaN                  NaN   \n",
       "113   870726314365509632           8.707262e+17         1.648776e+07   \n",
       "...                  ...                    ...                  ...   \n",
       "2294  667138269671505920                    NaN                  NaN   \n",
       "2298  667070482143944705           6.670655e+17         4.196984e+09   \n",
       "2299  667065535570550784                    NaN                  NaN   \n",
       "2301  667044094246576128                    NaN                  NaN   \n",
       "2305  666837028449972224                    NaN                  NaN   \n",
       "2306  666835007768551424                    NaN                  NaN   \n",
       "2307  666826780179869698                    NaN                  NaN   \n",
       "2310  666786068205871104                    NaN                  NaN   \n",
       "2316  666649482315059201                    NaN                  NaN   \n",
       "2320  666437273139982337                    NaN                  NaN   \n",
       "2321  666435652385423360                    NaN                  NaN   \n",
       "2322  666430724426358785                    NaN                  NaN   \n",
       "2323  666428276349472768                    NaN                  NaN   \n",
       "2324  666421158376562688                    NaN                  NaN   \n",
       "2328  666396247373291520                    NaN                  NaN   \n",
       "2329  666373753744588802                    NaN                  NaN   \n",
       "2330  666362758909284353                    NaN                  NaN   \n",
       "2331  666353288456101888                    NaN                  NaN   \n",
       "2332  666345417576210432                    NaN                  NaN   \n",
       "2336  666273097616637952                    NaN                  NaN   \n",
       "2337  666268910803644416                    NaN                  NaN   \n",
       "2338  666104133288665088                    NaN                  NaN   \n",
       "2339  666102155909144576                    NaN                  NaN   \n",
       "2340  666099513787052032                    NaN                  NaN   \n",
       "2341  666094000022159362                    NaN                  NaN   \n",
       "2342  666082916733198337                    NaN                  NaN   \n",
       "2343  666073100786774016                    NaN                  NaN   \n",
       "2344  666071193221509120                    NaN                  NaN   \n",
       "2351  666049248165822465                    NaN                  NaN   \n",
       "2355  666020888022790149                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "5     2017-07-29 00:08:17 +0000   \n",
       "7     2017-07-28 00:22:40 +0000   \n",
       "12    2017-07-25 01:55:32 +0000   \n",
       "24    2017-07-18 16:08:03 +0000   \n",
       "25    2017-07-18 00:07:08 +0000   \n",
       "30    2017-07-15 16:51:35 +0000   \n",
       "32    2017-07-15 02:45:48 +0000   \n",
       "35    2017-07-13 15:19:09 +0000   \n",
       "37    2017-07-12 16:03:00 +0000   \n",
       "41    2017-07-10 15:58:53 +0000   \n",
       "42    2017-07-10 03:08:17 +0000   \n",
       "47    2017-07-07 00:17:54 +0000   \n",
       "55    2017-07-02 21:58:53 +0000   \n",
       "59    2017-06-30 19:35:32 +0000   \n",
       "62    2017-06-28 16:09:20 +0000   \n",
       "64    2017-06-27 12:14:36 +0000   \n",
       "72    2017-06-24 13:24:20 +0000   \n",
       "78    2017-06-21 19:36:23 +0000   \n",
       "83    2017-06-18 20:30:39 +0000   \n",
       "88    2017-06-14 21:06:43 +0000   \n",
       "89    2017-06-14 16:04:48 +0000   \n",
       "93    2017-06-12 00:15:36 +0000   \n",
       "96    2017-06-10 16:39:04 +0000   \n",
       "99    2017-06-09 00:02:31 +0000   \n",
       "100   2017-06-08 14:20:41 +0000   \n",
       "101   2017-06-08 04:17:07 +0000   \n",
       "103   2017-06-07 16:14:40 +0000   \n",
       "110   2017-06-03 20:33:19 +0000   \n",
       "112   2017-06-03 00:48:22 +0000   \n",
       "113   2017-06-02 19:38:25 +0000   \n",
       "...                         ...   \n",
       "2294  2015-11-19 00:32:12 +0000   \n",
       "2298  2015-11-18 20:02:51 +0000   \n",
       "2299  2015-11-18 19:43:11 +0000   \n",
       "2301  2015-11-18 18:17:59 +0000   \n",
       "2305  2015-11-18 04:35:11 +0000   \n",
       "2306  2015-11-18 04:27:09 +0000   \n",
       "2307  2015-11-18 03:54:28 +0000   \n",
       "2310  2015-11-18 01:12:41 +0000   \n",
       "2316  2015-11-17 16:09:56 +0000   \n",
       "2320  2015-11-17 02:06:42 +0000   \n",
       "2321  2015-11-17 02:00:15 +0000   \n",
       "2322  2015-11-17 01:40:41 +0000   \n",
       "2323  2015-11-17 01:30:57 +0000   \n",
       "2324  2015-11-17 01:02:40 +0000   \n",
       "2328  2015-11-16 23:23:41 +0000   \n",
       "2329  2015-11-16 21:54:18 +0000   \n",
       "2330  2015-11-16 21:10:36 +0000   \n",
       "2331  2015-11-16 20:32:58 +0000   \n",
       "2332  2015-11-16 20:01:42 +0000   \n",
       "2336  2015-11-16 15:14:19 +0000   \n",
       "2337  2015-11-16 14:57:41 +0000   \n",
       "2338  2015-11-16 04:02:55 +0000   \n",
       "2339  2015-11-16 03:55:04 +0000   \n",
       "2340  2015-11-16 03:44:34 +0000   \n",
       "2341  2015-11-16 03:22:39 +0000   \n",
       "2342  2015-11-16 02:38:37 +0000   \n",
       "2343  2015-11-16 01:59:36 +0000   \n",
       "2344  2015-11-16 01:52:02 +0000   \n",
       "2351  2015-11-16 00:24:50 +0000   \n",
       "2355  2015-11-15 22:32:08 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "5     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "7     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "12    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "24    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "25    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "30    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "32    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "35    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "37    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "41    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "42    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "47    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "55    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "59    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "62    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "64    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "72    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "78    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "83    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "88    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "89    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "93    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "96    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "99    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "100   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "101   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "103   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "110   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "112   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "113   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "...                                                 ...   \n",
       "2294  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2298  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2299  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2301  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2305  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2306  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2307  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2310  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2316  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2320  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2321  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2322  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2323  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2324  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2328  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2329  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2330  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2331  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2332  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2336  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2337  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2338  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2339  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2340  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2341  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2342  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2343  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2344  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2351  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2355  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "5     Here we have a majestic great white breaching ...                  NaN   \n",
       "7     When you watch your owner call another dog a g...                  NaN   \n",
       "12    Here's a puppo that seems to be on the fence a...                  NaN   \n",
       "24    You may not have known you needed to see this ...                  NaN   \n",
       "25    This... is a Jubilant Antarctic House Bear. We...                  NaN   \n",
       "30    @NonWhiteHat @MayhewMayhem omg hello tanner yo...                  NaN   \n",
       "32    RT @Athletics: 12/10 #BATP https://t.co/WxwJmv...         8.860537e+17   \n",
       "35    I have a new hero and his name is Howard. 14/1...                  NaN   \n",
       "37    Here we have a corgi undercover as a malamute....                  NaN   \n",
       "41    I present to you, Pup in Hat. Pup in Hat is gr...                  NaN   \n",
       "42    OMG HE DIDN'T MEAN TO HE WAS JUST TRYING A LIT...                  NaN   \n",
       "47    Please only send dogs. We don't rate mechanics...                  NaN   \n",
       "55    @roushfenway These are good dogs but 17/10 is ...                  NaN   \n",
       "59    Ugh not again. We only rate dogs. Please don't...                  NaN   \n",
       "62    Please don't send in photos without dogs in th...                  NaN   \n",
       "64                      @RealKentMurphy 14/10 confirmed                  NaN   \n",
       "72    Martha is stunning how h*ckin dare you. 13/10 ...                  NaN   \n",
       "78    RT @rachel2195: @dog_rates the boyfriend and h...         8.768508e+17   \n",
       "83    I can say with the pupmost confidence that the...                  NaN   \n",
       "88    You'll get your package when that precious man...                  NaN   \n",
       "89    Guys please stop sending pictures without any ...                  NaN   \n",
       "93    I can't believe this keeps happening. This, is...                  NaN   \n",
       "96    We usually don't rate Deck-bound Saskatoon Bla...                  NaN   \n",
       "99    Here's a very large dog. He has a date later. ...                  NaN   \n",
       "100   Here are my favorite #dogsatpollingstations \\n...                  NaN   \n",
       "101   RT @loganamnosis: Penelope here is doing me qu...         8.726576e+17   \n",
       "103   We. Only. Rate. Dogs. Do not send in other thi...                  NaN   \n",
       "110   Never doubt a doggo 14/10 https://t.co/AbBLh2FZCH                  NaN   \n",
       "112   Real funny guys. Sending in a pic without a do...                  NaN   \n",
       "113   @ComplicitOwl @ShopWeRateDogs &gt;10/10 is res...                  NaN   \n",
       "...                                                 ...                  ...   \n",
       "2294  Extremely intelligent dog here. Has learned to...                  NaN   \n",
       "2298  After much debate this dog is being upgraded t...                  NaN   \n",
       "2299  Here we have a Hufflepuff. Loves vest. Eyes wi...                  NaN   \n",
       "2301            12/10 gimme now https://t.co/QZAnwgnOMB                  NaN   \n",
       "2305  My goodness. Very rare dog here. Large. Tail d...                  NaN   \n",
       "2306  These are Peruvian Feldspars. Their names are ...                  NaN   \n",
       "2307  12/10 simply brilliant pup https://t.co/V6ZzG4...                  NaN   \n",
       "2310  Unfamiliar with this breed. Ears pointy af. Wo...                  NaN   \n",
       "2316  Cool dog. Enjoys couch. Low monotone bark. Ver...                  NaN   \n",
       "2320  Here we see a lone northeastern Cumberbatch. H...                  NaN   \n",
       "2321  \"Can you behave? You're ruining my wedding day...                  NaN   \n",
       "2322  Oh boy what a pup! Sunglasses take this one to...                  NaN   \n",
       "2323  Here we have an Austrian Pulitzer. Collectors ...                  NaN   \n",
       "2324  *internally screaming* 12/10 https://t.co/YMcr...                  NaN   \n",
       "2328  Oh goodness. A super rare northeast Qdoba kang...                  NaN   \n",
       "2329  Those are sunglasses and a jean jacket. 11/10 ...                  NaN   \n",
       "2330  Unique dog here. Very small. Lives in containe...                  NaN   \n",
       "2331  Here we have a mixed Asiago from the Galápagos...                  NaN   \n",
       "2332  Look at this jokester thinking seat belt laws ...                  NaN   \n",
       "2336     Can take selfies 11/10 https://t.co/ws2AMaNwPW                  NaN   \n",
       "2337  Very concerned about fellow dog trapped in com...                  NaN   \n",
       "2338  Not familiar with this breed. No tail (weird)....                  NaN   \n",
       "2339  Oh my. Here you are seeing an Adobe Setter giv...                  NaN   \n",
       "2340  Can stand on stump for what seems like a while...                  NaN   \n",
       "2341  This appears to be a Mongolian Presbyterian mi...                  NaN   \n",
       "2342  Here we have a well-established sunblockerspan...                  NaN   \n",
       "2343  Let's hope this flight isn't Malaysian (lol). ...                  NaN   \n",
       "2344  Here we have a northern speckled Rhododendron....                  NaN   \n",
       "2351  Here we have a 1949 1st generation vulpix. Enj...                  NaN   \n",
       "2355  Here we have a Japanese Irish Setter. Lost eye...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "5                          NaN                        NaN   \n",
       "7                          NaN                        NaN   \n",
       "12                         NaN                        NaN   \n",
       "24                         NaN                        NaN   \n",
       "25                         NaN                        NaN   \n",
       "30                         NaN                        NaN   \n",
       "32                  19607400.0  2017-07-15 02:44:07 +0000   \n",
       "35                         NaN                        NaN   \n",
       "37                         NaN                        NaN   \n",
       "41                         NaN                        NaN   \n",
       "42                         NaN                        NaN   \n",
       "47                         NaN                        NaN   \n",
       "55                         NaN                        NaN   \n",
       "59                         NaN                        NaN   \n",
       "62                         NaN                        NaN   \n",
       "64                         NaN                        NaN   \n",
       "72                         NaN                        NaN   \n",
       "78                 512804507.0  2017-06-19 17:14:49 +0000   \n",
       "83                         NaN                        NaN   \n",
       "88                         NaN                        NaN   \n",
       "89                         NaN                        NaN   \n",
       "93                         NaN                        NaN   \n",
       "96                         NaN                        NaN   \n",
       "99                         NaN                        NaN   \n",
       "100                        NaN                        NaN   \n",
       "101                154767397.0  2017-06-08 03:32:35 +0000   \n",
       "103                        NaN                        NaN   \n",
       "110                        NaN                        NaN   \n",
       "112                        NaN                        NaN   \n",
       "113                        NaN                        NaN   \n",
       "...                        ...                        ...   \n",
       "2294                       NaN                        NaN   \n",
       "2298                       NaN                        NaN   \n",
       "2299                       NaN                        NaN   \n",
       "2301                       NaN                        NaN   \n",
       "2305                       NaN                        NaN   \n",
       "2306                       NaN                        NaN   \n",
       "2307                       NaN                        NaN   \n",
       "2310                       NaN                        NaN   \n",
       "2316                       NaN                        NaN   \n",
       "2320                       NaN                        NaN   \n",
       "2321                       NaN                        NaN   \n",
       "2322                       NaN                        NaN   \n",
       "2323                       NaN                        NaN   \n",
       "2324                       NaN                        NaN   \n",
       "2328                       NaN                        NaN   \n",
       "2329                       NaN                        NaN   \n",
       "2330                       NaN                        NaN   \n",
       "2331                       NaN                        NaN   \n",
       "2332                       NaN                        NaN   \n",
       "2336                       NaN                        NaN   \n",
       "2337                       NaN                        NaN   \n",
       "2338                       NaN                        NaN   \n",
       "2339                       NaN                        NaN   \n",
       "2340                       NaN                        NaN   \n",
       "2341                       NaN                        NaN   \n",
       "2342                       NaN                        NaN   \n",
       "2343                       NaN                        NaN   \n",
       "2344                       NaN                        NaN   \n",
       "2351                       NaN                        NaN   \n",
       "2355                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "5     https://twitter.com/dog_rates/status/891087950...                13   \n",
       "7     https://twitter.com/dog_rates/status/890729181...                13   \n",
       "12    https://twitter.com/dog_rates/status/889665388...                13   \n",
       "24    https://twitter.com/dog_rates/status/887343217...                13   \n",
       "25    https://twitter.com/dog_rates/status/887101392...                12   \n",
       "30                                                  NaN                12   \n",
       "32    https://twitter.com/dog_rates/status/886053434...                12   \n",
       "35    https://twitter.com/4bonds2carbon/status/88551...                14   \n",
       "37    https://twitter.com/dog_rates/status/885167619...                13   \n",
       "41    https://twitter.com/dog_rates/status/884441805...                14   \n",
       "42    https://twitter.com/kaijohnson_19/status/88396...                13   \n",
       "47    https://twitter.com/dog_rates/status/883117836...                13   \n",
       "55                                                  NaN                17   \n",
       "59    https://twitter.com/dog_rates/status/880872448...                12   \n",
       "62    https://twitter.com/dog_rates/status/880095782...                11   \n",
       "64                                                  NaN                14   \n",
       "72    https://twitter.com/bbcworld/status/8785998685...                13   \n",
       "78    https://twitter.com/rachel2195/status/87685077...                14   \n",
       "83    https://twitter.com/mpstowerham/status/8761629...                14   \n",
       "88    https://twitter.com/drboondoc/status/874413398...                13   \n",
       "89    https://twitter.com/dog_rates/status/875021211...                12   \n",
       "93    https://twitter.com/dog_rates/status/874057562...                12   \n",
       "96    https://twitter.com/dog_rates/status/873580283...                13   \n",
       "99    https://twitter.com/dog_rates/status/872967104...                12   \n",
       "100   https://twitter.com/dog_rates/status/872820683...                13   \n",
       "101   https://twitter.com/loganamnosis/status/872657...                14   \n",
       "103   https://twitter.com/dog_rates/status/872486979...                12   \n",
       "110   https://twitter.com/animalcog/status/871075758...                14   \n",
       "112   https://twitter.com/dog_rates/status/870804317...                11   \n",
       "113                                                 NaN                10   \n",
       "...                                                 ...               ...   \n",
       "2294  https://twitter.com/dog_rates/status/667138269...                10   \n",
       "2298                                                NaN                10   \n",
       "2299  https://twitter.com/dog_rates/status/667065535...                 8   \n",
       "2301  https://twitter.com/dog_rates/status/667044094...                12   \n",
       "2305  https://twitter.com/dog_rates/status/666837028...                 3   \n",
       "2306  https://twitter.com/dog_rates/status/666835007...                10   \n",
       "2307  https://twitter.com/dog_rates/status/666826780...                12   \n",
       "2310  https://twitter.com/dog_rates/status/666786068...                 2   \n",
       "2316  https://twitter.com/dog_rates/status/666649482...                 4   \n",
       "2320  https://twitter.com/dog_rates/status/666437273...                 7   \n",
       "2321  https://twitter.com/dog_rates/status/666435652...                10   \n",
       "2322  https://twitter.com/dog_rates/status/666430724...                 6   \n",
       "2323  https://twitter.com/dog_rates/status/666428276...                 7   \n",
       "2324  https://twitter.com/dog_rates/status/666421158...                12   \n",
       "2328  https://twitter.com/dog_rates/status/666396247...                 9   \n",
       "2329  https://twitter.com/dog_rates/status/666373753...                11   \n",
       "2330  https://twitter.com/dog_rates/status/666362758...                 6   \n",
       "2331  https://twitter.com/dog_rates/status/666353288...                 8   \n",
       "2332  https://twitter.com/dog_rates/status/666345417...                10   \n",
       "2336  https://twitter.com/dog_rates/status/666273097...                11   \n",
       "2337  https://twitter.com/dog_rates/status/666268910...                10   \n",
       "2338  https://twitter.com/dog_rates/status/666104133...                 1   \n",
       "2339  https://twitter.com/dog_rates/status/666102155...                11   \n",
       "2340  https://twitter.com/dog_rates/status/666099513...                 8   \n",
       "2341  https://twitter.com/dog_rates/status/666094000...                 9   \n",
       "2342  https://twitter.com/dog_rates/status/666082916...                 6   \n",
       "2343  https://twitter.com/dog_rates/status/666073100...                10   \n",
       "2344  https://twitter.com/dog_rates/status/666071193...                 9   \n",
       "2351  https://twitter.com/dog_rates/status/666049248...                 5   \n",
       "2355  https://twitter.com/dog_rates/status/666020888...                 8   \n",
       "\n",
       "      rating_denominator  name  doggo floofer  pupper  puppo  \n",
       "5                     10  None   None    None    None   None  \n",
       "7                     10  None   None    None    None   None  \n",
       "12                    10  None   None    None    None  puppo  \n",
       "24                    10  None   None    None    None   None  \n",
       "25                    10  None   None    None    None   None  \n",
       "30                    10  None   None    None    None   None  \n",
       "32                    10  None   None    None    None   None  \n",
       "35                    10  None   None    None    None   None  \n",
       "37                    10  None   None    None    None   None  \n",
       "41                    10  None   None    None    None   None  \n",
       "42                    10  None   None    None    None   None  \n",
       "47                    10  None   None    None    None   None  \n",
       "55                    10  None   None    None    None   None  \n",
       "59                    10  None   None    None    None   None  \n",
       "62                    10  None   None    None    None   None  \n",
       "64                    10  None   None    None    None   None  \n",
       "72                    10  None   None    None    None   None  \n",
       "78                    10  None   None    None  pupper   None  \n",
       "83                    10  None   None    None    None   None  \n",
       "88                    10  None   None    None    None   None  \n",
       "89                    10  None   None    None    None   None  \n",
       "93                    10  None   None    None    None   None  \n",
       "96                    10  None   None    None    None   None  \n",
       "99                    10  None  doggo    None    None   None  \n",
       "100                   10  None   None    None    None   None  \n",
       "101                   10  None   None    None    None   None  \n",
       "103                   10  None   None    None    None   None  \n",
       "110                   10  None  doggo    None    None   None  \n",
       "112                   10  None   None    None    None   None  \n",
       "113                   10  None   None    None    None   None  \n",
       "...                  ...   ...    ...     ...     ...    ...  \n",
       "2294                  10  None   None    None    None   None  \n",
       "2298                  10  None   None    None    None   None  \n",
       "2299                  10  None   None    None    None   None  \n",
       "2301                  10  None   None    None    None   None  \n",
       "2305                  10  None   None    None    None   None  \n",
       "2306                  10  None   None    None    None   None  \n",
       "2307                  10  None   None    None    None   None  \n",
       "2310                  10  None   None    None    None   None  \n",
       "2316                  10  None   None    None    None   None  \n",
       "2320                  10  None   None    None    None   None  \n",
       "2321                  10  None   None    None    None   None  \n",
       "2322                  10  None   None    None    None   None  \n",
       "2323                  10  None   None    None    None   None  \n",
       "2324                  10  None   None    None    None   None  \n",
       "2328                  10  None   None    None    None   None  \n",
       "2329                  10  None   None    None    None   None  \n",
       "2330                  10  None   None    None    None   None  \n",
       "2331                  10  None   None    None    None   None  \n",
       "2332                  10  None   None    None    None   None  \n",
       "2336                  10  None   None    None    None   None  \n",
       "2337                  10  None   None    None    None   None  \n",
       "2338                  10  None   None    None    None   None  \n",
       "2339                  10  None   None    None    None   None  \n",
       "2340                  10  None   None    None    None   None  \n",
       "2341                  10  None   None    None    None   None  \n",
       "2342                  10  None   None    None    None   None  \n",
       "2343                  10  None   None    None    None   None  \n",
       "2344                  10  None   None    None    None   None  \n",
       "2351                  10  None   None    None    None   None  \n",
       "2355                  10  None   None    None    None   None  \n",
       "\n",
       "[745 rows x 17 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Selsct name with \"None\"\n",
    "none = df_1[df_1.name == \"None\"]\n",
    "none"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is a pupper approaching maximum borkdrive. Zooming at never before seen speeds. 14/10 paw-inspiring af \n",
      "(IG: puffie_the_chow) https://t.co/ghXBIIeQZF\n",
      "Here is a perfect example of someone who has their priorities in order. 13/10 for both owner and Forrest https://t.co/LRyMrU7Wfq\n",
      "Guys this is getting so out of hand. We only rate dogs. This is a Galapagos Speed Panda. Pls only send dogs... 10/10 https://t.co/8lpAGaZRFn\n",
      "This is a mighty rare blue-tailed hammer sherk. Human almost lost a limb trying to take these. Be careful guys. 8/10 https://t.co/TGenMeXreW\n",
      "Viewer discretion is advised. This is a terrible attack in progress. Not even in water (tragic af). 4/10 bad sherk https://t.co/L3U0j14N5R\n",
      "This is a carrot. We only rate dogs. Please only send in dogs. You all really should know this by now ...11/10 https://t.co/9e48aPrBm2\n",
      "This is a very rare Great Alaskan Bush Pupper. Hard to stumble upon without spooking. 12/10 would pet passionately https://t.co/xOBKCdpzaa\n",
      "People please. This is a Deadly Mediterranean Plop T-Rex. We only rate dogs. Only send in dogs. Thanks you... 11/10 https://t.co/2ATDsgHD4n\n",
      "This is a taco. We only rate dogs. Please only send in dogs. Dogs are what we rate. Not tacos. Thank you... 10/10 https://t.co/cxl6xGY8B9\n",
      "Here is a heartbreaking scene of an incredible pupper being laid to rest. 10/10 RIP pupper https://t.co/81mvJ0rGRu\n",
      "Here is a whole flock of puppers.  60/50 I'll take the lot https://t.co/9dpcw6MdWa\n",
      "This is a Butternut Cumberfloof. It's not windy they just look like that. 11/10 back at it again with the red socks https://t.co/hMjzhdUHaW\n",
      "This is a Wild Tuscan Poofwiggle. Careful not to startle. Rare tongue slip. One eye magical. 12/10 would def pet https://t.co/4EnShAQjv6\n",
      "\"Pupper is a present to world. Here is a bow for pupper.\" 12/10 precious as hell https://t.co/ItSsE92gCW\n",
      "This is a rare Arctic Wubberfloof. Unamused by the happenings. No longer has the appetites. 12/10 would totally hug https://t.co/krvbacIX0N\n",
      "Guys this really needs to stop. We've been over this way too many times. This is a giraffe. We only rate dogs.. 7/10 https://t.co/yavgkHYPOC\n",
      "This is a dog swinging. I really enjoyed it so I hope you all do as well. 11/10 https://t.co/Ozo9KHTRND\n",
      "This is a Sizzlin Menorah spaniel from Brooklyn named Wylie. Lovable eyes. Chiller as hell. 10/10 and I'm out.. poof https://t.co/7E0AiJXPmI\n",
      "Seriously guys?! Only send in dogs. I only rate dogs. This is a baby black bear... 11/10 https://t.co/H7kpabTfLj\n",
      "C'mon guys. We've been over this. We only rate dogs. This is a cow. Please only submit dogs. Thank you...... 9/10 https://t.co/WjcELNEqN2\n",
      "This is a fluffy albino Bacardi Columbia mix. Excellent at the tweets. 11/10 would hug gently https://t.co/diboDRUuEI\n",
      "This is a Sagitariot Baklava mix. Loves her new hat. 11/10 radiant pup https://t.co/Bko5kFJYUU\n",
      "This is a heavily opinionated dog. Loves walls. Nobody knows how the hair works. Always ready for a kiss. 4/10 https://t.co/dFiaKZ9cDl\n",
      "This is a Lofted Aphrodisiac Terrier named Kip. Big fan of bed n breakfasts. Fits perfectly. 10/10 would pet firmly https://t.co/gKlLpNzIl3\n",
      "This is a baby Rand Paul. Curls for days. 11/10 would cuddle the hell out of https://t.co/xHXNaPAYRe\n",
      "This is a Tuscaloosa Alcatraz named Jacob (Yacōb). Loves to sit in swing. Stellar tongue. 11/10 look at his feet https://t.co/2IslQ8ZSc7\n",
      "This is a Helvetica Listerine named Rufus. This time Rufus will be ready for the UPS guy. He'll never expect it 9/10 https://t.co/34OhVhMkVr\n",
      "This is a Deciduous Trimester mix named Spork. Only 1 ear works. No seat belt. Incredibly reckless. 9/10 still cute https://t.co/CtuJoLHiDo\n",
      "This is a Rich Mahogany Seltzer named Cherokee. Just got destroyed by a snowball. Isn't very happy about it. 9/10 https://t.co/98ZBi6o4dj\n",
      "This is a Speckled Cauliflower Yosemite named Hemry. He's terrified of intruder dog. Not one bit comfortable. 9/10 https://t.co/yV3Qgjh8iN\n",
      "This is a spotted Lipitor Rumpelstiltskin named Alphred. He can't wait for the Turkey. 10/10 would pet really well https://t.co/6GUGO7azNX\n",
      "This is a brave dog. Excellent free climber. Trying to get closer to God. Not very loyal though. Doesn't bark. 5/10 https://t.co/ODnILTr4QM\n",
      "This is a Coriander Baton Rouge named Alfredo. Loves to cuddle with smaller well-dressed dog. 10/10 would hug lots https://t.co/eCRdwouKCl\n",
      "This is a Slovakian Helter Skelter Feta named Leroi. Likes to skip on roofs. Good traction. Much balance. 10/10 wow! https://t.co/Dmy2mY2Qj5\n",
      "This is a wild Toblerone from Papua New Guinea. Mouth always open. Addicted to hay. Acts blind. 7/10 handsome dog https://t.co/IGmVbz07tZ\n",
      "Here is a horned dog. Much grace. Can jump over moons (dam!). Paws not soft. Bad at barking. 7/10 can still pet tho https://t.co/2Su7gmsnZm\n",
      "This is a Birmingham Quagmire named Chuk. Loves to relax and watch the game while sippin on that iced mocha. 10/10 https://t.co/HvNg9JWxFt\n",
      "Here is a mother dog caring for her pups. Snazzy red mohawk. Doesn't wag tail. Pups look confused. Overall 4/10 https://t.co/YOHe6lf09m\n",
      "This is a Trans Siberian Kellogg named Alfonso. Huge ass eyeballs. Actually Dobby from Harry Potter. 7/10 https://t.co/XpseHBlAAb\n",
      "This is a Shotokon Macadamia mix named Cheryl. Sophisticated af. Looks like a disappointed librarian. Shh (lol) 9/10 https://t.co/J4GnJ5Swba\n",
      "This is a rare Hungarian Pinot named Jessiga. She is either mid-stroke or got stuck in the washing machine. 8/10 https://t.co/ZU0i0KJyqD\n",
      "This is a southwest Coriander named Klint. Hat looks expensive. Still on house arrest :(\n",
      "9/10 https://t.co/IQTOMqDUIe\n",
      "This is a northern Wahoo named Kohl. He runs this town. Chases tumbleweeds. Draws gun wicked fast. 11/10 legendary https://t.co/J4vn2rOYFk\n",
      "This is a Dasani Kingfisher from Maine. His name is Daryl. Daryl doesn't like being swallowed by a panda. 8/10 https://t.co/jpaeu6LNmW\n",
      "This is a curly Ticonderoga named Pepe. No feet. Loves to jet ski. 11/10 would hug until forever https://t.co/cyDfaK8NBc\n",
      "This is a purebred Bacardi named Octaviath. Can shoot spaghetti out of mouth. 10/10 https://t.co/uEvsGLOFHa\n",
      "This is a golden Buckminsterfullerene named Johm. Drives trucks. Lumberjack (?). Enjoys wall. 8/10 would hug softly https://t.co/uQbZJM2DQB\n",
      "This is a southern Vesuvius bumblegruff. Can drive a truck (wow). Made friends with 5 other nifty dogs (neat). 7/10 https://t.co/LopTBkKa8h\n",
      "This is a funny dog. Weird toes. Won't come down. Loves branch. Refuses to eat his food. Hard to cuddle with. 3/10 https://t.co/IIXis0zta0\n",
      "My oh my. This is a rare blond Canadian terrier on wheels. Only $8.98. Rather docile. 9/10 very rare https://t.co/yWBqbrzy8O\n",
      "Here is a Siberian heavily armored polar bear mix. Strong owner. 10/10 I would do unspeakable things to pet this dog https://t.co/rdivxLiqEt\n",
      "This is a truly beautiful English Wilson Staff retriever. Has a nice phone. Privileged. 10/10 would trade lives with https://t.co/fvIbQfHjIe\n",
      "This is a purebred Piers Morgan. Loves to Netflix and chill. Always looks like he forgot to unplug the iron. 6/10 https://t.co/DWnyCjf2mx\n",
      "Here is a very happy pup. Big fan of well-maintained decks. Just look at that tongue. 9/10 would cuddle af https://t.co/y671yMhoiR\n",
      "This is a western brown Mitsubishi terrier. Upset about leaf. Actually 2 dogs here. 7/10 would walk the shit out of https://t.co/r7mOb2m0UI\n"
     ]
    }
   ],
   "source": [
    "# Check text for incomplete name \"a\"\n",
    "a = df_1[df_1.name == \"a\"]\n",
    "\n",
    "for i in a.iloc[:,5]:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tweet_id                         0\n",
       "in_reply_to_status_id         2278\n",
       "in_reply_to_user_id           2278\n",
       "timestamp                        0\n",
       "source                           0\n",
       "text                             0\n",
       "retweeted_status_id           2175\n",
       "retweeted_status_user_id      2175\n",
       "retweeted_status_timestamp    2175\n",
       "expanded_urls                   59\n",
       "rating_numerator                 0\n",
       "rating_denominator               0\n",
       "name                             0\n",
       "doggo                            0\n",
       "floofer                          0\n",
       "pupper                           0\n",
       "puppo                            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check missing values in df_1\n",
    "df_1.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10     2333\n",
       "11        3\n",
       "50        3\n",
       "80        2\n",
       "20        2\n",
       "2         1\n",
       "16        1\n",
       "40        1\n",
       "70        1\n",
       "15        1\n",
       "90        1\n",
       "110       1\n",
       "120       1\n",
       "130       1\n",
       "150       1\n",
       "170       1\n",
       "7         1\n",
       "0         1\n",
       "Name: rating_denominator, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the value counts of rating_denominator\n",
    "df_1.rating_denominator.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12      558\n",
       "11      464\n",
       "10      461\n",
       "13      351\n",
       "9       158\n",
       "8       102\n",
       "7        55\n",
       "14       54\n",
       "5        37\n",
       "6        32\n",
       "3        19\n",
       "4        17\n",
       "1         9\n",
       "2         9\n",
       "420       2\n",
       "0         2\n",
       "15        2\n",
       "75        2\n",
       "80        1\n",
       "20        1\n",
       "24        1\n",
       "26        1\n",
       "44        1\n",
       "50        1\n",
       "60        1\n",
       "165       1\n",
       "84        1\n",
       "88        1\n",
       "144       1\n",
       "182       1\n",
       "143       1\n",
       "666       1\n",
       "960       1\n",
       "1776      1\n",
       "17        1\n",
       "27        1\n",
       "45        1\n",
       "99        1\n",
       "121       1\n",
       "204       1\n",
       "Name: rating_numerator, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the values counts of rating_numerator\n",
    "df_1.rating_numerator.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check for duplicates\n",
    "df_1.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check for duplicates\n",
    "df_2.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "golden_retriever             150\n",
       "Labrador_retriever           100\n",
       "Pembroke                      89\n",
       "Chihuahua                     83\n",
       "pug                           57\n",
       "chow                          44\n",
       "Samoyed                       43\n",
       "toy_poodle                    39\n",
       "Pomeranian                    38\n",
       "malamute                      30\n",
       "cocker_spaniel                30\n",
       "French_bulldog                26\n",
       "Chesapeake_Bay_retriever      23\n",
       "miniature_pinscher            23\n",
       "seat_belt                     22\n",
       "Siberian_husky                20\n",
       "German_shepherd               20\n",
       "Staffordshire_bullterrier     20\n",
       "web_site                      19\n",
       "Cardigan                      19\n",
       "teddy                         18\n",
       "Eskimo_dog                    18\n",
       "Shetland_sheepdog             18\n",
       "beagle                        18\n",
       "Maltese_dog                   18\n",
       "Shih-Tzu                      17\n",
       "Rottweiler                    17\n",
       "Lakeland_terrier              17\n",
       "kuvasz                        16\n",
       "Italian_greyhound             16\n",
       "                            ... \n",
       "barbell                        1\n",
       "lion                           1\n",
       "zebra                          1\n",
       "shopping_basket                1\n",
       "American_black_bear            1\n",
       "damselfly                      1\n",
       "cuirass                        1\n",
       "desktop_computer               1\n",
       "nail                           1\n",
       "African_grey                   1\n",
       "mortarboard                    1\n",
       "king_penguin                   1\n",
       "china_cabinet                  1\n",
       "slug                           1\n",
       "restaurant                     1\n",
       "Egyptian_cat                   1\n",
       "stove                          1\n",
       "revolver                       1\n",
       "convertible                    1\n",
       "cougar                         1\n",
       "lacewing                       1\n",
       "skunk                          1\n",
       "fiddler_crab                   1\n",
       "banana                         1\n",
       "dining_table                   1\n",
       "trombone                       1\n",
       "maillot                        1\n",
       "microwave                      1\n",
       "alp                            1\n",
       "long-horned_beetle             1\n",
       "Name: p1, Length: 378, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check value counts p1\n",
    "df_2.p1.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Labrador_retriever                104\n",
       "golden_retriever                   92\n",
       "Cardigan                           73\n",
       "Chihuahua                          44\n",
       "Pomeranian                         42\n",
       "French_bulldog                     41\n",
       "Chesapeake_Bay_retriever           41\n",
       "toy_poodle                         37\n",
       "cocker_spaniel                     34\n",
       "miniature_poodle                   33\n",
       "Siberian_husky                     33\n",
       "beagle                             28\n",
       "Pembroke                           27\n",
       "collie                             27\n",
       "Eskimo_dog                         27\n",
       "kuvasz                             26\n",
       "Italian_greyhound                  22\n",
       "American_Staffordshire_terrier     21\n",
       "Pekinese                           21\n",
       "malinois                           20\n",
       "toy_terrier                        20\n",
       "miniature_pinscher                 20\n",
       "Samoyed                            20\n",
       "chow                               20\n",
       "Norwegian_elkhound                 19\n",
       "Boston_bull                        19\n",
       "Staffordshire_bullterrier          18\n",
       "pug                                17\n",
       "Irish_terrier                      17\n",
       "kelpie                             16\n",
       "                                 ... \n",
       "toucan                              1\n",
       "rain_barrel                         1\n",
       "triceratops                         1\n",
       "volcano                             1\n",
       "saltshaker                          1\n",
       "hay                                 1\n",
       "sandbar                             1\n",
       "bathing_cap                         1\n",
       "hotdog                              1\n",
       "jigsaw_puzzle                       1\n",
       "hair_slide                          1\n",
       "folding_chair                       1\n",
       "wombat                              1\n",
       "timber_wolf                         1\n",
       "seashore                            1\n",
       "cannon                              1\n",
       "cardigan                            1\n",
       "affenpinscher                       1\n",
       "crib                                1\n",
       "standard_schnauzer                  1\n",
       "dugong                              1\n",
       "snorkel                             1\n",
       "nail                                1\n",
       "breakwater                          1\n",
       "menu                                1\n",
       "lighter                             1\n",
       "printer                             1\n",
       "stove                               1\n",
       "porcupine                           1\n",
       "coffee_mug                          1\n",
       "Name: p2, Length: 405, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check value counts p2\n",
    "df_2.p2.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Labrador_retriever                79\n",
       "Chihuahua                         58\n",
       "golden_retriever                  48\n",
       "Eskimo_dog                        38\n",
       "kelpie                            35\n",
       "kuvasz                            34\n",
       "chow                              32\n",
       "Staffordshire_bullterrier         32\n",
       "beagle                            31\n",
       "cocker_spaniel                    31\n",
       "Pekinese                          29\n",
       "Pomeranian                        29\n",
       "toy_poodle                        29\n",
       "Chesapeake_Bay_retriever          27\n",
       "Great_Pyrenees                    27\n",
       "Pembroke                          27\n",
       "malamute                          26\n",
       "French_bulldog                    26\n",
       "American_Staffordshire_terrier    24\n",
       "Cardigan                          23\n",
       "pug                               23\n",
       "basenji                           21\n",
       "toy_terrier                       20\n",
       "bull_mastiff                      20\n",
       "Siberian_husky                    19\n",
       "Boston_bull                       17\n",
       "Shetland_sheepdog                 17\n",
       "boxer                             16\n",
       "Lakeland_terrier                  16\n",
       "doormat                           16\n",
       "                                  ..\n",
       "oxcart                             1\n",
       "chimpanzee                         1\n",
       "rhinoceros_beetle                  1\n",
       "neck_brace                         1\n",
       "cowboy_boot                        1\n",
       "goose                              1\n",
       "rifle                              1\n",
       "sea_cucumber                       1\n",
       "tripod                             1\n",
       "Sussex_spaniel                     1\n",
       "greenhouse                         1\n",
       "wild_boar                          1\n",
       "whiptail                           1\n",
       "boathouse                          1\n",
       "Indian_elephant                    1\n",
       "drumstick                          1\n",
       "paintbrush                         1\n",
       "shoji                              1\n",
       "chain                              1\n",
       "shower_cap                         1\n",
       "gorilla                            1\n",
       "coffeepot                          1\n",
       "window_screen                      1\n",
       "grey_fox                           1\n",
       "European_fire_salamander           1\n",
       "shovel                             1\n",
       "barrow                             1\n",
       "meerkat                            1\n",
       "viaduct                            1\n",
       "cheetah                            1\n",
       "Name: p3, Length: 408, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check value counts p3\n",
    "df_2.p3.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "contributors                     2326\n",
       "coordinates                      2326\n",
       "created_at                          0\n",
       "display_text_range                  0\n",
       "entities                            0\n",
       "extended_entities                 270\n",
       "favorite_count                      0\n",
       "favorited                           0\n",
       "full_text                           0\n",
       "geo                              2326\n",
       "id                                  0\n",
       "id_str                              0\n",
       "in_reply_to_screen_name          2249\n",
       "in_reply_to_status_id            2249\n",
       "in_reply_to_status_id_str        2249\n",
       "in_reply_to_user_id              2249\n",
       "in_reply_to_user_id_str          2249\n",
       "is_quote_status                     0\n",
       "lang                                0\n",
       "place                            2325\n",
       "possibly_sensitive                132\n",
       "possibly_sensitive_appealable     132\n",
       "quoted_status                    2304\n",
       "quoted_status_id                 2301\n",
       "quoted_status_id_str             2301\n",
       "quoted_status_permalink          2301\n",
       "retweet_count                       0\n",
       "retweeted                           0\n",
       "retweeted_status                 2167\n",
       "source                              0\n",
       "truncated                           0\n",
       "user                                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check missing values in df_3\n",
    "df_3.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "535     [0, 122]\n",
       "1608     [0, 68]\n",
       "544     [0, 127]\n",
       "583     [0, 140]\n",
       "1417    [0, 101]\n",
       "1991     [0, 77]\n",
       "1823    [0, 140]\n",
       "2041    [0, 140]\n",
       "688     [0, 118]\n",
       "1104     [0, 57]\n",
       "1597    [0, 139]\n",
       "1730    [0, 133]\n",
       "1927    [0, 137]\n",
       "1222    [0, 108]\n",
       "1356    [0, 139]\n",
       "2120     [0, 70]\n",
       "1799    [0, 136]\n",
       "1529    [0, 140]\n",
       "1153     [0, 72]\n",
       "762      [0, 58]\n",
       "915      [0, 59]\n",
       "458     [0, 139]\n",
       "1753    [0, 137]\n",
       "2007    [0, 144]\n",
       "1278    [0, 122]\n",
       "669     [0, 107]\n",
       "2290    [0, 138]\n",
       "1304     [0, 90]\n",
       "446      [0, 96]\n",
       "1224    [0, 120]\n",
       "439      [0, 98]\n",
       "461      [0, 94]\n",
       "1447     [0, 82]\n",
       "1485     [0, 71]\n",
       "925      [0, 77]\n",
       "1781    [0, 103]\n",
       "658     [0, 114]\n",
       "1254     [0, 75]\n",
       "22       [0, 99]\n",
       "1334    [0, 137]\n",
       "989      [0, 38]\n",
       "1656    [0, 138]\n",
       "1697    [0, 139]\n",
       "468     [0, 109]\n",
       "2275    [0, 138]\n",
       "718     [0, 100]\n",
       "1040     [0, 64]\n",
       "1110     [0, 75]\n",
       "1632    [0, 138]\n",
       "202     [0, 140]\n",
       "Name: display_text_range, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check content of display_text_range\n",
    "df_3.iloc[:,3].sample(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quality issues\n",
    "`df_1`\n",
    "1. Timestamp is an object not a datetime\n",
    "\n",
    "2. Outliers in rating denominator \n",
    "\n",
    "3. Names sometimes begins with a lowercase\n",
    "\n",
    "4. Missing values (name, doggo, floofer, pupper, and puppo)\n",
    "\n",
    "5. Remove (in_reply_to_status_id, in_reply_to_user_id, retweeted_status_user_id, retweeted_status_id, and retweeted_status_timestamp) and other unwanted columns\n",
    "\n",
    "6. Extract missing names from text and proper naming of incomplete names\n",
    "\n",
    "`df_2`\n",
    "7. Underscore and inconsistent in letter casing of _(p1, p2,and p3)_ columns\n",
    "\n",
    "8. Extract dog confident level and dog breed\n",
    "\n",
    "`df_3`\n",
    "9. Missing values (contributors, coordinates, in_reply_to_screen_name, in_reply_to_status_id, in_reply_to_status_id_str, in_reply_to_user_id, in_reply_to_user_id_str, geo, place, quoted_status, quoted_status_id,quoted_status_id_str, quoted_status_permalink, and retweeted_status)\n",
    "\n",
    "10. Convert display_text_range column to display_text_length\n",
    "\n",
    "11. Drop unwanted columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 0,
        "height": 7,
        "hidden": false,
        "row": 40,
        "width": 12
       },
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "### Tidiness issues\n",
    "1.\tMerge doggo, floofer, pupper, and puppo columns and name it dog_stage in `df_1`\n",
    "\n",
    "2.\tMerge `df_1`, `df_2`, and `df_3`\t"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "col": 4,
        "height": 4,
        "hidden": false,
        "row": 32,
        "width": 4
       },
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "<a id=\"cleaningdata\"></a>\n",
    "<h2>Cleaning Data</h2>\n",
    "\n",
    "In this section, clean **all** of the issues you documented while assessing. \n",
    "\n",
    "**Note:** Make a copy of the original data before cleaning. Cleaning includes merging individual pieces of data according to the rules of [tidy data](https://cran.r-project.org/web/packages/tidyr/vignettes/tidy-data.html). The result should be a high-quality and tidy master pandas DataFrame (or DataFrames, if appropriate)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make copies of original pieces of data\n",
    "df_1_clean = df_1.copy()\n",
    "df_2_clean = df_2.copy()\n",
    "df_3_clean = df_3.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #1:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {
        "hidden": true
       },
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "source": [
    "#### Define\n",
    "Merge doggo, floofer, pupper, and puppo columns together and name it dog_stage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace \"None\" values with \"\"\n",
    "columns = [\"doggo\", \"floofer\", \"pupper\", \"puppo\"]\n",
    "for col in columns:\n",
    "    df_1_clean[col].replace(\"None\", \"\", inplace = True)\n",
    "\n",
    "# Define a custom function that combines the values of four columns into one\n",
    "def combine_cols(row):\n",
    "    return row[\"doggo\"] + row[\"floofer\"] + row[\"pupper\"] + row[\"puppo\"]\n",
    "\n",
    "# Apply the custom function to the dataframe\n",
    "df_1_clean[\"dog_stage\"] = df_1_clean.apply(combine_cols, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Separate multiple dog stage with comma\n",
    "df_1_clean.loc[df_1_clean.dog_stage == \"doggopupper\", \"dog_stage\"] = \"doggo, pupper\"\n",
    "df_1_clean.loc[df_1_clean.dog_stage == \"doggofloofer\", \"dog_stage\"] = \"doggo, floofer\"\n",
    "df_1_clean.loc[df_1_clean.dog_stage == \"doggopuppo\", \"dog_stage\"] = \"doggo, puppo\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                  1976\n",
       "pupper             245\n",
       "doggo               83\n",
       "puppo               29\n",
       "doggo, pupper       12\n",
       "floofer              9\n",
       "doggo, puppo         1\n",
       "doggo, floofer       1\n",
       "Name: dog_stage, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the value counts of dog_stage column\n",
    "df_1_clean.dog_stage.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define:\n",
    "Extract missing names from text. Name column with an imcomplet entry of \"a\". Replace incomplete names with nan."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Extract name of dogs from text\n",
    "a_names = df_1_clean[df_1_clean.name == \"a\"][\"text\"].str.extract(r\"named\\s(\\w+)\").dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1853</th>\n",
       "      <td>Wylie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1955</th>\n",
       "      <td>Kip</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2034</th>\n",
       "      <td>Jacob</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2066</th>\n",
       "      <td>Rufus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2116</th>\n",
       "      <td>Spork</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2125</th>\n",
       "      <td>Cherokee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2128</th>\n",
       "      <td>Hemry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2146</th>\n",
       "      <td>Alphred</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2161</th>\n",
       "      <td>Alfredo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2191</th>\n",
       "      <td>Leroi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>Chuk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2235</th>\n",
       "      <td>Alfonso</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2249</th>\n",
       "      <td>Cheryl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2255</th>\n",
       "      <td>Jessiga</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2264</th>\n",
       "      <td>Klint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2273</th>\n",
       "      <td>Kohl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2304</th>\n",
       "      <td>Pepe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2311</th>\n",
       "      <td>Octaviath</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2314</th>\n",
       "      <td>Johm</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              0\n",
       "1853      Wylie\n",
       "1955        Kip\n",
       "2034      Jacob\n",
       "2066      Rufus\n",
       "2116      Spork\n",
       "2125   Cherokee\n",
       "2128      Hemry\n",
       "2146    Alphred\n",
       "2161    Alfredo\n",
       "2191      Leroi\n",
       "2218       Chuk\n",
       "2235    Alfonso\n",
       "2249     Cheryl\n",
       "2255    Jessiga\n",
       "2264      Klint\n",
       "2273       Kohl\n",
       "2304       Pepe\n",
       "2311  Octaviath\n",
       "2314       Johm"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace extracted named in name column\n",
    "a_values = df_1_clean[df_1_clean.name == \"a\"][\"name\"].values\n",
    "df_1_clean.name = df_1_clean.name.replace(dict(zip(a_values, a_names.values)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace incompleted names (names with \"Nono\" and lower case) with numpy nan\n",
    "for name in df_1_clean.name:\n",
    "    if name == name.lower() or name == \"None\":\n",
    "        df_1_clean.name.replace(name, np.nan, inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Johm          55\n",
       "Charlie       12\n",
       "Oliver        11\n",
       "Cooper        11\n",
       "Lucy          11\n",
       "Penny         10\n",
       "Tucker        10\n",
       "Lola          10\n",
       "Bo             9\n",
       "Winston        9\n",
       "Sadie          8\n",
       "Bailey         7\n",
       "Daisy          7\n",
       "Toby           7\n",
       "Buddy          7\n",
       "Stanley        6\n",
       "Koda           6\n",
       "Oscar          6\n",
       "Rusty          6\n",
       "Jax            6\n",
       "Jack           6\n",
       "Leo            6\n",
       "Scout          6\n",
       "Milo           6\n",
       "Dave           6\n",
       "Bella          6\n",
       "Oakley         5\n",
       "Finn           5\n",
       "Sammy          5\n",
       "Larry          5\n",
       "              ..\n",
       "Tupawc         1\n",
       "Lorelei        1\n",
       "Pherb          1\n",
       "Cheesy         1\n",
       "Glacier        1\n",
       "Gòrdón         1\n",
       "Dallas         1\n",
       "Eevee          1\n",
       "Darby          1\n",
       "Mutt           1\n",
       "Adele          1\n",
       "Al             1\n",
       "Miguel         1\n",
       "Rumble         1\n",
       "Chesterson     1\n",
       "River          1\n",
       "Aqua           1\n",
       "Biden          1\n",
       "Hanz           1\n",
       "Naphaniel      1\n",
       "Tater          1\n",
       "Yukon          1\n",
       "Trigger        1\n",
       "Alejandro      1\n",
       "Diogi          1\n",
       "Jarvis         1\n",
       "Aubie          1\n",
       "Deacon         1\n",
       "Reptar         1\n",
       "Superpup       1\n",
       "Name: name, Length: 932, dtype: int64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check value counts for name column\n",
    "df_1_clean.name.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #3:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "Remove (in_reply_to_status_id, in_reply_to_user_id, retweeted_status_user_id, retweeted_status_id, and retweeted_status_timestamp) and other unwanted columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# To remove the retweets\n",
    "df_1_clean = df_1_clean[df_1_clean.retweeted_status_id.isnull()]\n",
    "\n",
    "# To remove the replies\n",
    "df_1_clean = df_1_clean[df_1_clean.in_reply_to_status_id.isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop unwanted columns \n",
    "df_1_clean.drop([\"in_reply_to_status_id\", \n",
    "                 \"in_reply_to_user_id\", \n",
    "                 \"retweeted_status_user_id\", \n",
    "                 \"retweeted_status_id\", \n",
    "                 \"retweeted_status_timestamp\",\n",
    "                 \"doggo\", \n",
    "                 \"floofer\", \n",
    "                 \"pupper\", \n",
    "                 \"puppo\"],\n",
    "               axis = 1,\n",
    "               inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2097 entries, 0 to 2355\n",
      "Data columns (total 9 columns):\n",
      "tweet_id              2097 non-null int64\n",
      "timestamp             2097 non-null object\n",
      "source                2097 non-null object\n",
      "text                  2097 non-null object\n",
      "expanded_urls         2094 non-null object\n",
      "rating_numerator      2097 non-null int64\n",
      "rating_denominator    2097 non-null int64\n",
      "name                  1445 non-null object\n",
      "dog_stage             2097 non-null object\n",
      "dtypes: int64(3), object(6)\n",
      "memory usage: 163.8+ KB\n"
     ]
    }
   ],
   "source": [
    "# Output info\n",
    "df_1_clean.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #4:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "Extract p1 and p1_conf, p2 and p2_conf, and p3 and p3_conf with p1_dog, p2_dog and p_3 True respectively into dog_breed and dog_conf "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a custom function that extract dog_breed and conf values with picture dog is True into  separate columns\n",
    "def get_classi(col):\n",
    "    if col[0] == True:\n",
    "        return col[1]\n",
    "    elif col[2] == True:\n",
    "        return col[3]\n",
    "    elif col[4] == True:\n",
    "        return col[5]\n",
    "    \n",
    "# Apply the custom function to creat \"dog_breed\" column\n",
    "df_2_clean[\"dog_breed\"] = df_2_clean.loc[:, [\"p1_dog\", \"p1\", \n",
    "                                             \"p2_dog\", \"p2\", \n",
    "                                             \"p3_dog\", \"p3\"]].apply(get_classi,\n",
    "                                                                    axis = 1)\n",
    "\n",
    "# Apply the custom function to creat \"dog_conf\" column\n",
    "df_2_clean[\"dog_conf\"] = df_2_clean.loc[:, [\"p1_dog\", \"p1_conf\", \n",
    "                                             \"p2_dog\", \"p2_conf\", \n",
    "                                             \"p3_dog\", \"p3_conf\"]].apply(get_classi,\n",
    "                                                                         axis = 1)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dog_breed</th>\n",
       "      <th>dog_conf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Welsh_springer_spaniel</td>\n",
       "      <td>0.465074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>redbone</td>\n",
       "      <td>0.506826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.596461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.408143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.560311</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                dog_breed  dog_conf\n",
       "0  Welsh_springer_spaniel  0.465074\n",
       "1                 redbone  0.506826\n",
       "2         German_shepherd  0.596461\n",
       "3     Rhodesian_ridgeback  0.408143\n",
       "4      miniature_pinscher  0.560311"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Output dataframe\n",
    "df_2_clean[[\"dog_breed\", \"dog_conf\"]].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #5:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "Drop unwanted columns from `df_2`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2_clean.drop([\"jpg_url\", \"img_num\", \n",
    "                 \"p1\", \"p1_conf\", \n",
    "                 \"p1_dog\", \"p2\",\n",
    "                 \"p2_conf\", \"p2_dog\", \n",
    "                 \"p3\", \"p3_conf\", \"p3_dog\"],\n",
    "                axis = 1,\n",
    "                inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2075 entries, 0 to 2074\n",
      "Data columns (total 3 columns):\n",
      "tweet_id     2075 non-null int64\n",
      "dog_breed    1751 non-null object\n",
      "dog_conf     1751 non-null float64\n",
      "dtypes: float64(1), int64(1), object(1)\n",
      "memory usage: 48.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df_2_clean.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #6:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "Extract the maximum text lenght from the display_text_range and assign to new column name display_text_length in `df_3`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract the difference between the min and max display_text_range\n",
    "df_3_clean[\"display_text_length\"] = df_3_clean[\"display_text_range\"].map(lambda x: x[1] - x[0])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>display_text_range</th>\n",
       "      <th>display_text_length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[0, 85]</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[0, 121]</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[0, 79]</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  display_text_range  display_text_length\n",
       "0            [0, 85]                   85\n",
       "1           [0, 138]                  138\n",
       "2           [0, 121]                  121\n",
       "3            [0, 79]                   79\n",
       "4           [0, 138]                  138"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_3_clean[[\"display_text_range\", \"display_text_length\"]].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #7:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "Drop unwanted coluns from df_3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop columns\n",
    "for col in df_3_clean.columns:\n",
    "    if col not in [\"full_text\", \n",
    "                   \"retweet_count\", \n",
    "                   \"favorite_count\", \n",
    "                   \"display_text_length\"]:\n",
    "        df_3_clean.drop(col, axis = 1, inplace = True)\n",
    "        \n",
    "# Rename full_text column to text\n",
    "df_3_clean.rename({\"full_text\" : \"text\"},\n",
    "                  axis = 1,\n",
    "                  inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>text</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>display_text_length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>32822</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>6848</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>28373</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>5159</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21301</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>3404</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35780</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>7059</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34206</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>7569</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   favorite_count                                               text  \\\n",
       "0           32822  This is Phineas. He's a mystical boy. Only eve...   \n",
       "1           28373  This is Tilly. She's just checking pup on you....   \n",
       "2           21301  This is Archie. He is a rare Norwegian Pouncin...   \n",
       "3           35780  This is Darla. She commenced a snooze mid meal...   \n",
       "4           34206  This is Franklin. He would like you to stop ca...   \n",
       "\n",
       "   retweet_count  display_text_length  \n",
       "0           6848                   85  \n",
       "1           5159                  138  \n",
       "2           3404                  121  \n",
       "3           7059                   79  \n",
       "4           7569                  138  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_3_clean.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #8:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "- Merge `df_3` to `df_1` \n",
    "- Merge `df_2` to the new datafram"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merge df_3_clean to df_1_clean\n",
    "master_tweet = pd.merge(df_1_clean,\n",
    "                        df_3_clean,\n",
    "                        on = \"text\",\n",
    "                        how = \"inner\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merge df_2_clean to master_tweet\n",
    "master_tweet = pd.merge(master_tweet,\n",
    "                        df_2_clean,\n",
    "                        on = \"tweet_id\",\n",
    "                        how = \"inner\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1963 entries, 0 to 1962\n",
      "Data columns (total 14 columns):\n",
      "tweet_id               1963 non-null int64\n",
      "timestamp              1963 non-null object\n",
      "source                 1963 non-null object\n",
      "text                   1963 non-null object\n",
      "expanded_urls          1963 non-null object\n",
      "rating_numerator       1963 non-null int64\n",
      "rating_denominator     1963 non-null int64\n",
      "name                   1397 non-null object\n",
      "dog_stage              1963 non-null object\n",
      "favorite_count         1963 non-null int64\n",
      "retweet_count          1963 non-null int64\n",
      "display_text_length    1963 non-null int64\n",
      "dog_breed              1658 non-null object\n",
      "dog_conf               1658 non-null float64\n",
      "dtypes: float64(1), int64(6), object(7)\n",
      "memory usage: 230.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# Chec the info of master_tweet\n",
    "master_tweet.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #9:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "Convert rating denominator to 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert denominator to 10\n",
    "for deno in master_tweet.rating_denominator:\n",
    "    if deno != 10:\n",
    "        master_tweet.rating_denominator.replace(deno, 10, inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10    1963\n",
       "Name: rating_denominator, dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check value counts for rating_denominator\n",
    "master_tweet.rating_denominator.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #10:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "Change Timestamp from object to datetime\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change the datatype of Timestamp from object to datetime\n",
    "master_tweet[\"timestamp\"] = pd.to_datetime(master_tweet[\"timestamp\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tweet_id                        int64\n",
       "timestamp              datetime64[ns]\n",
       "source                         object\n",
       "text                           object\n",
       "expanded_urls                  object\n",
       "rating_numerator                int64\n",
       "rating_denominator              int64\n",
       "name                           object\n",
       "dog_stage                      object\n",
       "favorite_count                  int64\n",
       "retweet_count                   int64\n",
       "display_text_length             int64\n",
       "dog_breed                      object\n",
       "dog_conf                      float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check info of master_tweet dataframe\n",
    "master_tweet.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Issue #11:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define\n",
    "Convert all dog breed to lower case and remove all underscores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert dog breed into lower case and remove all underscores\n",
    "master_tweet.dog_breed = master_tweet.dog_breed.str.replace(\"_\", \" \").str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "golden retriever                  156\n",
       "labrador retriever                103\n",
       "pembroke                           94\n",
       "chihuahua                          90\n",
       "pug                                62\n",
       "toy poodle                         49\n",
       "chow                               48\n",
       "pomeranian                         41\n",
       "samoyed                            41\n",
       "malamute                           33\n",
       "chesapeake bay retriever           31\n",
       "cocker spaniel                     30\n",
       "french bulldog                     30\n",
       "miniature pinscher                 24\n",
       "eskimo dog                         22\n",
       "german shepherd                    21\n",
       "cardigan                           21\n",
       "beagle                             20\n",
       "siberian husky                     20\n",
       "shih-tzu                           20\n",
       "staffordshire bullterrier          19\n",
       "maltese dog                        19\n",
       "shetland sheepdog                  18\n",
       "rottweiler                         18\n",
       "basset                             17\n",
       "italian greyhound                  17\n",
       "kuvasz                             17\n",
       "lakeland terrier                   17\n",
       "west highland white terrier        16\n",
       "american staffordshire terrier     15\n",
       "                                 ... \n",
       "ibizan hound                        4\n",
       "weimaraner                          4\n",
       "gordon setter                       4\n",
       "saluki                              4\n",
       "bluetick                            4\n",
       "brabancon griffon                   3\n",
       "toy terrier                         3\n",
       "giant schnauzer                     3\n",
       "cairn                               3\n",
       "komondor                            3\n",
       "curly-coated retriever              3\n",
       "leonberg                            3\n",
       "irish water spaniel                 3\n",
       "greater swiss mountain dog          3\n",
       "briard                              3\n",
       "afghan hound                        3\n",
       "wire-haired fox terrier             2\n",
       "australian terrier                  2\n",
       "sussex spaniel                      2\n",
       "appenzeller                         2\n",
       "groenendael                         2\n",
       "black-and-tan coonhound             2\n",
       "clumber                             1\n",
       "silky terrier                       1\n",
       "scotch terrier                      1\n",
       "entlebucher                         1\n",
       "japanese spaniel                    1\n",
       "standard schnauzer                  1\n",
       "irish wolfhound                     1\n",
       "bouvier des flandres                1\n",
       "Name: dog_breed, Length: 113, dtype: int64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "master_tweet.dog_breed.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"storingdata\"></a>\n",
    "<h2>Storing Data</h2>\n",
    "\n",
    "Save gathered, assessed, and cleaned master dataset to a CSV file named \"twitter_archive_master.csv\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "master_tweet.to_csv(\"twitter_archive_master.csv\", \n",
    "                    index = False, \n",
    "                    encoding =\"utf-8\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"analyzingandvisualizing\"></a>\n",
    "<h2>Analyzing and Visualizing Data</h2>\n",
    "\n",
    "In this section, analyze and visualize your wrangled data. You must produce at least **three (3) insights and one (1) visualization.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"twitter_archive_master.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = data.copy() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Insights:\n",
    "1.\tWhat time period has the highest activity?\n",
    "\n",
    "2.\tWhat are the most common dog breeds and dog breeds with the highest ratings as well as dog breeds with the lowest rating?\n",
    "\n",
    "3.\tWhat is the relationship between the numerical columns especially (favourite count and retweet count)?\n",
    "\n",
    "4.\tWhat is the distribution and relationship between dog stages and retweet count as well as favourite count?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What time period has the highest activity?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3982d0f8d0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[\"timestamp\"] = pd.to_datetime(df[\"timestamp\"])\n",
    "\n",
    "# Extract the hour from the timestamp and store it in a new column \"hour\"\n",
    "df[\"hour\"] = df[\"timestamp\"].dt.hour\n",
    "\n",
    "# Plot the frequency of tweets for each hour\n",
    "plt.figure(figsize = (10, 6))\n",
    "plt.hist(df[\"hour\"], bins=24)\n",
    "plt.xlabel(\"Hour\")\n",
    "plt.ylabel(\"Frequency\")\n",
    "plt.title(\"Time Period in Hours by Tweets\")\n",
    "plt.xticks(range(0, 24, 1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "According to the above graph, the majority of tweets occur between the hours of 0:00 and 5:00 and midday between 14 and 23, however tweet volume between 6 and 14 is extremely low. This indicates that there aren't almost any tweets during working hours."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What are the most common dog breeds and dog breeds with the highest ratings as well as dog breeds with the lowest rating?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "golden retriever      156\n",
       "labrador retriever    103\n",
       "pembroke               94\n",
       "chihuahua              90\n",
       "pug                    62\n",
       "toy poodle             49\n",
       "chow                   48\n",
       "pomeranian             41\n",
       "samoyed                41\n",
       "malamute               33\n",
       "Name: dog_breed, dtype: int64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Most common dog breeds\n",
    "df.dog_breed.value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dog_breed\n",
       "clumber                        2.700000\n",
       "soft-coated wheaten terrier    2.135714\n",
       "west highland white terrier    1.468750\n",
       "great pyrenees                 1.466667\n",
       "chow                           1.416667\n",
       "labrador retriever             1.373786\n",
       "borzoi                         1.360000\n",
       "siberian husky                 1.325000\n",
       "bouvier des flandres           1.300000\n",
       "pomeranian                     1.253659\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dog breeds with the highest ratings (Top 10)\n",
    "df[\"rating\"] = df.rating_numerator / df.rating_denominator\n",
    "highest_rating = df.groupby(\"dog_breed\")[\"rating\"].mean().sort_values(ascending=False).head(10)\n",
    "\n",
    "highest_rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dog_breed\n",
       "dandie dinmont            0.957143\n",
       "welsh springer spaniel    0.950000\n",
       "boston bull               0.941667\n",
       "dalmatian                 0.933333\n",
       "maltese dog               0.931579\n",
       "tibetan terrier           0.925000\n",
       "ibizan hound              0.925000\n",
       "scotch terrier            0.900000\n",
       "walker hound              0.900000\n",
       "japanese spaniel          0.500000\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dog breeds with the lowest ratings (Bottom 10)\n",
    "lowest_rating = df.groupby(\"dog_breed\")[\"rating\"].mean().sort_values(ascending=False).tail(10)\n",
    "\n",
    "lowest_rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f397dfe4390>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create the figure and subplots\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize = (12, 6))\n",
    "\n",
    "# Plot the highest rated dog breeds on the left subplot\n",
    "highest_rating.plot(kind = \"bar\", ax = ax1, color = \"navy\")\n",
    "ax1.set_title(\"Highest Rated Dog Breeds\")\n",
    "ax1.set_xlabel(\"Dog Breed\")\n",
    "ax1.set_ylabel(\"Average Rating\")\n",
    "\n",
    "# Plot the lowest rated dog breeds on the right subplot\n",
    "lowest_rating.plot(kind = \"bar\", ax = ax2, color = \"mediumseagreen\")\n",
    "ax2.set_title(\"Lowest Rated Dog Breeds\")\n",
    "ax2.set_xlabel(\"Dog Breed\")\n",
    "ax2.set_ylabel(\"Average Rating\")\n",
    "\n",
    "# Show the plot\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the right-hand chart, Clumber has the highest rating there with a 2.7. While the Pomeranian was ranked as the 10th best breed with 1.3 points. The chart on the left, however, displays the dog breeds with the lowest ratings. The Japanese Spaniel had the lowest rating of any dog breed with 0.5."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What is the relationship between the numerical columns especially (favourite count and retweet count)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>display_text_length</th>\n",
       "      <th>dog_conf</th>\n",
       "      <th>hour</th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>tweet_id</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.024922</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.611185</td>\n",
       "      <td>0.385310</td>\n",
       "      <td>-0.113147</td>\n",
       "      <td>0.100346</td>\n",
       "      <td>0.139947</td>\n",
       "      <td>0.024922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rating_numerator</th>\n",
       "      <td>0.024922</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.016789</td>\n",
       "      <td>0.019118</td>\n",
       "      <td>-0.076104</td>\n",
       "      <td>0.038629</td>\n",
       "      <td>0.012584</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rating_denominator</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>favorite_count</th>\n",
       "      <td>0.611185</td>\n",
       "      <td>0.016789</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.929253</td>\n",
       "      <td>-0.090585</td>\n",
       "      <td>0.047275</td>\n",
       "      <td>0.048546</td>\n",
       "      <td>0.016789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>retweet_count</th>\n",
       "      <td>0.385310</td>\n",
       "      <td>0.019118</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.929253</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.112744</td>\n",
       "      <td>0.018371</td>\n",
       "      <td>0.046524</td>\n",
       "      <td>0.019118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>display_text_length</th>\n",
       "      <td>-0.113147</td>\n",
       "      <td>-0.076104</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.090585</td>\n",
       "      <td>-0.112744</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.004997</td>\n",
       "      <td>0.035226</td>\n",
       "      <td>-0.076104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dog_conf</th>\n",
       "      <td>0.100346</td>\n",
       "      <td>0.038629</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.047275</td>\n",
       "      <td>0.018371</td>\n",
       "      <td>-0.004997</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.019003</td>\n",
       "      <td>0.038629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hour</th>\n",
       "      <td>0.139947</td>\n",
       "      <td>0.012584</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.048546</td>\n",
       "      <td>0.046524</td>\n",
       "      <td>0.035226</td>\n",
       "      <td>0.019003</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rating</th>\n",
       "      <td>0.024922</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.016789</td>\n",
       "      <td>0.019118</td>\n",
       "      <td>-0.076104</td>\n",
       "      <td>0.038629</td>\n",
       "      <td>0.012584</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     tweet_id  rating_numerator  rating_denominator  \\\n",
       "tweet_id             1.000000          0.024922                 NaN   \n",
       "rating_numerator     0.024922          1.000000                 NaN   \n",
       "rating_denominator        NaN               NaN                 NaN   \n",
       "favorite_count       0.611185          0.016789                 NaN   \n",
       "retweet_count        0.385310          0.019118                 NaN   \n",
       "display_text_length -0.113147         -0.076104                 NaN   \n",
       "dog_conf             0.100346          0.038629                 NaN   \n",
       "hour                 0.139947          0.012584                 NaN   \n",
       "rating               0.024922          1.000000                 NaN   \n",
       "\n",
       "                     favorite_count  retweet_count  display_text_length  \\\n",
       "tweet_id                   0.611185       0.385310            -0.113147   \n",
       "rating_numerator           0.016789       0.019118            -0.076104   \n",
       "rating_denominator              NaN            NaN                  NaN   \n",
       "favorite_count             1.000000       0.929253            -0.090585   \n",
       "retweet_count              0.929253       1.000000            -0.112744   \n",
       "display_text_length       -0.090585      -0.112744             1.000000   \n",
       "dog_conf                   0.047275       0.018371            -0.004997   \n",
       "hour                       0.048546       0.046524             0.035226   \n",
       "rating                     0.016789       0.019118            -0.076104   \n",
       "\n",
       "                     dog_conf      hour    rating  \n",
       "tweet_id             0.100346  0.139947  0.024922  \n",
       "rating_numerator     0.038629  0.012584  1.000000  \n",
       "rating_denominator        NaN       NaN       NaN  \n",
       "favorite_count       0.047275  0.048546  0.016789  \n",
       "retweet_count        0.018371  0.046524  0.019118  \n",
       "display_text_length -0.004997  0.035226 -0.076104  \n",
       "dog_conf             1.000000  0.019003  0.038629  \n",
       "hour                 0.019003  1.000000  0.012584  \n",
       "rating               0.038629  0.012584  1.000000  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the correlation matrix of the dataset\n",
    "corr = df.corr()\n",
    "corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop rating_denominator\n",
    "corr.drop(\"rating_denominator\", axis = 1, inplace = True)\n",
    "corr.drop(\"rating_denominator\", axis = 0, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f397f093668>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the heatmap for correlation matrix\n",
    "plt.figure(figsize = (12,8))\n",
    "sns.heatmap(corr, annot=True)\n",
    "plt.title(\"Correlation Matrix of Numerical Variables\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f397dee5fd0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Scatter plot of favorite_count and retweet_count\n",
    "plt.figure(figsize = (10, 8))\n",
    "plt.scatter(x = df[\"retweet_count\"], \n",
    "           y = df[\"favorite_count\"])\n",
    "\n",
    "plt.title(\"Correlation Between Retweet Count and Favorite Count\")\n",
    "plt.xlabel(\"Retweet Counts\")\n",
    "plt.ylabel(\"Favorite Counts\")\n",
    "\n",
    "#Show figure\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The heatmap demonstrates that most numerical variables have weak correlations with one another. Focusing on the correlation between the favourite count and the retweet count. The scatter plot indicates there is a strong positive correlation between these variables as they have correlation of 0.93 also shown in the heatmap."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What is the distribution and relationship between dog stages and retweet count as well as favourite count?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dog_stage</th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>display_text_length</th>\n",
       "      <th>dog_conf</th>\n",
       "      <th>hour</th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>doggo</td>\n",
       "      <td>7.970939e+17</td>\n",
       "      <td>11.870968</td>\n",
       "      <td>10.0</td>\n",
       "      <td>17094.838710</td>\n",
       "      <td>5836.919355</td>\n",
       "      <td>104.048387</td>\n",
       "      <td>0.508401</td>\n",
       "      <td>11.225806</td>\n",
       "      <td>1.187097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>doggo, floofer</td>\n",
       "      <td>8.540102e+17</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14345.000000</td>\n",
       "      <td>2741.000000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>0.354733</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>1.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>doggo, pupper</td>\n",
       "      <td>7.747741e+17</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12349.000000</td>\n",
       "      <td>3649.125000</td>\n",
       "      <td>108.625000</td>\n",
       "      <td>0.803757</td>\n",
       "      <td>6.375000</td>\n",
       "      <td>1.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>doggo, puppo</td>\n",
       "      <td>8.558515e+17</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>40240.000000</td>\n",
       "      <td>15580.000000</td>\n",
       "      <td>134.000000</td>\n",
       "      <td>0.321676</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>floofer</td>\n",
       "      <td>7.665514e+17</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10904.857143</td>\n",
       "      <td>3892.857143</td>\n",
       "      <td>112.000000</td>\n",
       "      <td>0.609204</td>\n",
       "      <td>7.857143</td>\n",
       "      <td>1.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>pupper</td>\n",
       "      <td>7.187022e+17</td>\n",
       "      <td>10.716418</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6070.805970</td>\n",
       "      <td>1880.144279</td>\n",
       "      <td>110.791045</td>\n",
       "      <td>0.586449</td>\n",
       "      <td>9.487562</td>\n",
       "      <td>1.071642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>puppo</td>\n",
       "      <td>8.089964e+17</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>18958.818182</td>\n",
       "      <td>5196.409091</td>\n",
       "      <td>111.363636</td>\n",
       "      <td>0.652581</td>\n",
       "      <td>12.090909</td>\n",
       "      <td>1.200000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        dog_stage      tweet_id  rating_numerator  rating_denominator  \\\n",
       "0           doggo  7.970939e+17         11.870968                10.0   \n",
       "1  doggo, floofer  8.540102e+17         11.000000                10.0   \n",
       "2   doggo, pupper  7.747741e+17         11.000000                10.0   \n",
       "3    doggo, puppo  8.558515e+17         13.000000                10.0   \n",
       "4         floofer  7.665514e+17         12.000000                10.0   \n",
       "5          pupper  7.187022e+17         10.716418                10.0   \n",
       "6           puppo  8.089964e+17         12.000000                10.0   \n",
       "\n",
       "   favorite_count  retweet_count  display_text_length  dog_conf       hour  \\\n",
       "0    17094.838710    5836.919355           104.048387  0.508401  11.225806   \n",
       "1    14345.000000    2741.000000           140.000000  0.354733  16.000000   \n",
       "2    12349.000000    3649.125000           108.625000  0.803757   6.375000   \n",
       "3    40240.000000   15580.000000           134.000000  0.321676  18.000000   \n",
       "4    10904.857143    3892.857143           112.000000  0.609204   7.857143   \n",
       "5     6070.805970    1880.144279           110.791045  0.586449   9.487562   \n",
       "6    18958.818182    5196.409091           111.363636  0.652581  12.090909   \n",
       "\n",
       "     rating  \n",
       "0  1.187097  \n",
       "1  1.100000  \n",
       "2  1.100000  \n",
       "3  1.300000  \n",
       "4  1.200000  \n",
       "5  1.071642  \n",
       "6  1.200000  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Group the data by dog breed and calculate the mean for retweet count and favorite count\n",
    "df_grouped = df.groupby(\"dog_stage\").mean().reset_index()\n",
    "df_grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f397d6022b0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f397d5f8470>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f397d1f8cf8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the distribution of dog breeds\n",
    "plt.figure(figsize = (10,6))\n",
    "sns.countplot(x = \"dog_stage\", palette = \"cool\", data = df)\n",
    "plt.title(\"Distribution of Dog Stages in the Tweets\")\n",
    "plt.xlabel(\"Dog Breed\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.savefig(\"Distribution of Dog Stages.png\")\n",
    "plt.show()\n",
    "\n",
    "# Plot the relationship between dog breed and retweet count\n",
    "plt.figure(figsize = (10,6))\n",
    "sns.barplot(x = \"dog_stage\", y =\"retweet_count\", palette = \"cool\", data = df_grouped)\n",
    "plt.title(\"Relationship between Dog Stage and Retweet Count\")\n",
    "plt.xlabel(\"Dog Breed\")\n",
    "plt.ylabel(\"Retweet Count\")\n",
    "plt.savefig(\"Dog Stages Retweet.png\")\n",
    "plt.show()\n",
    "\n",
    "# Plot the relationship between dog breed and favorite count\n",
    "plt.figure(figsize = (10,6))\n",
    "sns.barplot(x = \"dog_stage\", y = \"favorite_count\", palette = \"cool\", data = df_grouped)\n",
    "plt.title(\"Relationship between Dog Stage and Favorite Count\")\n",
    "plt.xlabel(\"Dog Breed\")\n",
    "plt.ylabel(\"Favorite Count\")\n",
    "plt.savefig(\"Dog Stage Favorite.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Fig. 1__ shows the distribution of dog stages based on the above chart. This indicates that the most common dog stage is Pupper, Followed by Doggo. The chart's lowest distribution was recoded by Doggo, Pupper and Doggo, Floofer.\n",
    "\n",
    "\n",
    "The relationship between dog stage and retweet count is also illustrated in __Fig. 2__. This shows that with 16,000 counts, Doggo, Puppo has the most retweets, followed by Doggo with 6,000. With roughly 2000 retweets, Pupper has the lowest number.\n",
    "\n",
    "\n",
    "__Fig. 3__ also represents the relationship between the dog stage and favorite count. According to the graph, Doggo, Puppo had a 40,000 favorite count, while Pupper had a 6000 favorite count as the lowest recorded."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"conclusion\"></a>\n",
    "<h2> Conclusion </h2>\n",
    "\n",
    "The analysis of the WeRateDogs Twitter datasets found that there are specific patterns and trends in the dog-related content shared on the platform. It was discovered that the majority of tweets occur during the early hours of the day and in the evenings, with very little activity during working hours. This emphasizes how crucial it is to comprehend the habits and routines of the target audience when developing social media strategies.\n",
    "\n",
    "The analysis also determined which dog breeds had the highest and lowest ratings, with Clumber having the highest rating and Japanese Spaniel having the lowest. Favorite count and retweet count have a strong positive connection, indicating that they are closely related metrics and that increasing either one will probably raise the other.\n",
    "\n",
    "The analysis also looked at how dog phases are distributed and related to one another, as well as how they affect favorite and retweet counts. Pupper was found to be the most prevalent dog stage, followed by Doggo, with Doggo, Puppo and Doggo, Floofer having the lowest frequency, according to the findings. Doggo, Puppo received the most retweets and favorites.\n",
    "\n",
    "In conclusion, social media managers and dog owners may use this study to better understand the concerns and trends on the WeRateDogs Twitter platform and provide more relevant and interesting content for their followers.\n"
   ]
  }
 ],
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