Pump_It_Up_Outlier_Analysis.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Pump It Up - Outlier Analysis ",
      "provenance": [],
      "mount_file_id": "1kq6KkQUd7eVPAc5kWVpuxhz1KauSFrz5",
      "authorship_tag": "ABX9TyOrEQxxqmf7nVkNT8BehvN2",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Yoshani/Pump-It-Up/blob/master/Pump_It_Up_Outlier_Analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_qODBWTca5ov"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn.ensemble import IsolationForest\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import precision_score\n",
        "\n",
        "# plotting\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import pyplot\n",
        "import seaborn as sns"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5Ln0sWYLbNX6"
      },
      "source": [
        "# Get datasets"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MbzvhR2VbLP4"
      },
      "source": [
        "features_df = pd.read_csv(\n",
        "    \"/content/drive/MyDrive/PumpItUp/TrainingSet.csv\", \n",
        "    index_col=\"id\",\n",
        "    low_memory=False\n",
        ")\n",
        "labels_df = pd.read_csv(\n",
        "    \"/content/drive/MyDrive/PumpItUp/TrainingLabels.csv\", \n",
        "    index_col=\"id\"\n",
        ")\n",
        "test_df = pd.read_csv(\n",
        "    \"/content/drive/MyDrive/PumpItUp/TestSet.csv\", \n",
        "    index_col=\"id\",\n",
        "    low_memory=False\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-6pB2ZGIbSTE"
      },
      "source": [
        "X = features_df.copy()\n",
        "y = labels_df.copy()\n",
        "X_test = test_df.copy()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eqT_SDMfbVYO"
      },
      "source": [
        "# Outlier Analysis"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "id": "Kl7iup0qbXq2",
        "outputId": "5172116c-190b-4948-f21a-da9998f2f27b"
      },
      "source": [
        "plt.subplots(figsize=(15, 5))\n",
        "sns.boxplot(data=features_df)\n",
        "plt.title(\"Overall Boxplot\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Overall Boxplot')"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CG4UtRYbbdnk"
      },
      "source": [
        "Viewing altogether does not reveal much due to differences in scale"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hYeZyeC7bbyO"
      },
      "source": [
        "# numeric columns\n",
        "cols = ['gps_height','longitude','latitude','region_code', 'district_code','construction_year']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "E4GxmeYpbfid",
        "outputId": "72c37d02-6dd8-4655-9788-aa324e73a324"
      },
      "source": [
        "features_df['longitude'].plot.box()\n",
        "plt.title(\"Boxplot of Longitude\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Boxplot of Longitude')"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pOQZ9W0EbkBO"
      },
      "source": [
        "Zero in longitude seems to be an outlier"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "5ZEEpJRdbiQl",
        "outputId": "c5fabece-e79e-4d88-d9b7-0663f09cc0a8"
      },
      "source": [
        "features_df['gps_height'].plot.box()\n",
        "plt.title(\"Boxplot of GPS height\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Boxplot of GPS height')"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "Obo0erqfbvrg",
        "outputId": "bb88a5a6-0643-445a-9807-7885c59a3d02"
      },
      "source": [
        "features_df['latitude'].plot.box()\n",
        "plt.title(\"Boxplot of Latitude\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Boxplot of Latitude')"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 335
        },
        "id": "41o70Wn6byAz",
        "outputId": "5bf2ec7c-7695-489f-89a9-1030fbffcd1f"
      },
      "source": [
        "plt.subplots(figsize=(30, 5))\n",
        "sns.boxplot(x='population',data=features_df)\n",
        "plt.xticks(rotation=90)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([-5000.,     0.,  5000., 10000., 15000., 20000., 25000., 30000.,\n",
              "        35000.]), <a list of 9 Text major ticklabel objects>)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 2160x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "OtJ8kHjNbz3b",
        "outputId": "dc29d95a-d5f7-41f7-bb26-0614a904605c"
      },
      "source": [
        "features_df['region_code'].plot.box()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb454ebb850>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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U1X3AFmAP8EVgX1Xt7pb/OfBZZv8ATc95ndcCk92bsncBvz/ALNJjeG4ZNefHx6uTPAn4NLC5qm4d9VzScvKYu1q0PcnZwPHATsOuY5F77tJhJLkMeN1Biz9TVZfPt750NDDuktQg31CVpAYZd0lqkHGXpAYZd0lq0P8DiC+4ECLE/ocAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "9Nst4vwdb1Y-",
        "outputId": "87c3e0f1-3b4f-4d5c-c058-4fd91df6c329"
      },
      "source": [
        "features_df['district_code'].plot.box()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb454e14490>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "eFfmapZMb3AK",
        "outputId": "6593f596-1da0-41e2-9242-16df24f6b3b2"
      },
      "source": [
        "plt.subplots(figsize=(15, 5))\n",
        "sns.boxplot(x='construction_year',data=features_df)\n",
        "plt.xticks(rotation=90)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([-250.,    0.,  250.,  500.,  750., 1000., 1250., 1500., 1750.,\n",
              "        2000., 2250.]), <a list of 11 Text major ticklabel objects>)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1YAAAFNCAYAAAAD0v4aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAV4ElEQVR4nO3dfbRldX3f8c93wAcSBUUiRUQnOlKIVSlimrQm1bQqWtMka5mosSHaB7MaM6Fp0oSktokryxbNikZpsZJUUWtCiEnUWmto1ahLl8qDPIkoE1doMy0UhVARsAjf/nH26J3rzDjjb+7suee8Xmux1r37nHvme39sOPM+Z5+9q7sDAADAt27L3AMAAABsdsIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGDQkQdy5+OOO663bt26QaMAAAAc3i6//PIvdPd3rN9+QGG1devWXHbZZQdvKgAAgE2kqm7c03aHAgIAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADDoyLkHGHXeeedlx44dc48BAADsw86dO5MkJ5544h5v37ZtW7Zv334oRzqoNn1Y7dixI1de+5nc+23Hzj0KAACwF0fceXuS5KavfGOCHHHnrYd6nINu04dVktz7bcfmrlOeM/cYAADAXhx1/XuTZI9/b99122bmM1YAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADDoyLkHGLVz585sufvOuccAAAAOkvPOOy9Jsn379pkn2X+bPqzuuuuu1H33zD0GAABwkOzYsWPuEQ6YQwEBAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABgkrAACAQcIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABgkrAACAQcIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABgkrAACAQcIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABgkrAACAQcIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYdOfcAAADAatty9//Njh1fytlnn50k2bFjR4466qiZpzow3/Qdq6p6aVVdVlWX3XLLLYdiJgAAgE3lm75j1d0XJLkgSc4444ze8IkAAICVct8Dj862xxyf173udUnytXeuNhOfsQIAABgkrAAAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABgkrAACAQcIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABgkrAACAQcIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABgkrAACAQcIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABgkrAACAQcIKAABgkLACAAAYJKwAAAAGCSsAAIBBwgoAAGCQsAIAABgkrAAAAAYJKwAAgEHCCgAAYNCRcw8w6qijjsqX/l/PPQYAAHCQbNu2be4RDtimD6sTTzwxN33l5rnHAAAADpLt27fPPcIBcyggAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMOnLuAQ6GI+68NUdd/965xwAAAPbiiDu/mCR7/Hv7EXfemuT4QzzRwbXpw2rbtm1zjwAAAHwTO3d+NUly4ol7CqjjN/3f6zd9WG3fvn3uEQAAgBXnM1YAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMAgYQUAADBIWAEAAAwSVgAAAIOEFQAAwCBhBQAAMEhYAQAADBJWAAAAg4QVAADAIGEFAAAwSFgBAAAMElYAAACDhBUAAMCg6u79v3PVLUlu3LhxvmXHJfnC3EOsIOs+H2s/D+s+H2s/D+s+H2s/D+s+n8209o/u7u9Yv/GAwupwVVWXdfcZc8+xaqz7fKz9PKz7fKz9PKz7fKz9PKz7fJZh7R0KCAAAMEhYAQAADFqWsLpg7gFWlHWfj7Wfh3Wfj7Wfh3Wfj7Wfh3Wfz6Zf+6X4jBUAAMCcluUdKwAAgNkIKwAAgEFHzj3AgaqqU5L8UJITp007k7y7uz8z31QAAMAq21SfsaqqX0rywiQXJfmLafMjk7wgyUXdfe5cs62Cqqok353do/aTvZl2ok2sqo7PmrXv7pvnnGcV2OcB4OCrqmOSnJndn1//pLv/cr6pxm22sPpcksd39z3rtt8/yae7+3HzTLb8quqZSc5PckMWO3+yiNptSX66uy+Za7ZlV1WnJfkPSY7J7mv/l1ms/RVzzbbM7PPzWtYn3cNdVT0ryQ9n93V/V3e/b76pVoMjcuZhnz/0quqsJL+a5JLs/vz6jCSv6O63zjXbqM0WVtcneVZ337hu+6OTXNLdf3WeyZZfVX0mybO7+8/Xbf/OJO/t7lNnGWwFVNWVSX6quz+xbvv3JHljdz9pnsmWm31+Psv8pHs4q6rfSnJykrdm96NCzkpyQ3efPddsy84ROfOwz8+jqj6b5G+sf6Gsqh6a5BPdffI8k43bbGF1ZpJ/l8UryP9z2vyoLF5B/hmvLmycqrohyand/dV12++f5Lru3jbPZMuvqm7Y27uxVbXD2m8M+/x8lvlJ93BWVZ/b09pOh8R+zlEhG8cROfOwz89j2t+f0t23r9t+TJLLNvO6b6qTV3T3+6rq5HzjZx4u7e5755tsJbwpyaVVdVG+HrUnZfFq2n+cbarV8F+r6r9k8Yra2rU/K4kXEzaOfX4+lWRPr/rdN93Gxri7qp7S3Zeu2/6UJHfPMdAKuS/JI5LcuG77CdNtbAz7/DxemeSKqroku79R8owkvz7bVAfBpnrHinlV1anZ8/Hf18031Wqoqmdnz2v/3vmmWn72+XlU1U8m+ddZHAr4DU+63X3hTKMttao6Pckbkjw4Xz8s6qQktyd5WXdfPtdsy84ROfOwz89nOgLhWfnGz9HeNt9U44QVAIedZX3S3Qyq6q9k9zOQ3jTnPKuiqrbEETmzsM/PYxnPdrypDgVkPlV15q5XzKZjYH8ziyeAa5P83DL8x3C4mtb7l7N45+T4LA6R+j9J3pXkXGdJ2xj2+Xl1921V9cHs/qQrqg6B6S+VN1XVg5KcXFV3+//MIdFr/tn1vcMADwH7/KG17mzHf5HFId6PrKpNf7bjLXMPwKbxb9Z8/ZtJbkryg0kuTfLGWSZaHRcnuS3J07v72O5+WJKnZ3G69YtnnWy52ednUlWnVdXHk/xpklcleXWSD1XVx6dDd9gAVXX+mq+fmuS6LPb9a6rqObMNtgKmyzvckOTXkjxn+ucVSW6YbmMD2Odnc2GSs7v71O5+Rnf/3e4+Jck/S/LmeUcb41BA9ktVXdHdp09fX9ndp625bbfvObiq6rN7u5TAvm5jjH1+Pi4xMI91+/wHk/x8d19RVY9JcnF3nzHvhMvL5R3mYZ+fxzKf7dihgOyvh1fVP8/i7dqjq6r661Xunc+NdWNV/WKSt+w6/Gw6LvnF+fqHnDn47PPz+fb1UZUk3f3xqvr2OQZaQUfvOhynuz8/ff6HjXNkvn7yhLV2JrnfIZ5lVdnnD52lPduxsGJ//XYWZ81JkrckOS7JLdMHPq+cbarV8Pwk52RxKNSuz1jdnOTdSX5szsGWnH1+Pkv7pHuYO6Wqrs7ixYStVfXQ6bNuW5Lcf+bZlp3LO8zDPj+D7v7ZvZzt+N9v9rMdOxSQ/VZVp2TxH8AnuvuONdu/9iF/Nl5VfV8WJ1G4prsvmXueZVVVP5vkj7vbu4IzcImBQ6+qHr1u0//q7nuq6rgk39/dfzTHXKvC5R0OPfs8B5uwYr9U1fYkP5PkM0lOy+JDh++abvvaMcocfFX1ye7+7unrf5zkZUnemeSZSf5zd58753zLqqpuT/LlJH+W5PeS/EF33zLvVACwuS3z2Y4dP8r+emmSJ3f3Dyd5WpJ/VVVnT7fVbFOthrXH1/9Ukmd29yuyCKsXzTPSSvh8kkdmcRX4Jye5rqreV1U/WVUP3vePMqKqjqmqc6vqM1V1a1V9cfr63Kp6yNzzLauqOrqq/m1Vva2qfnzdbefv7ecYN10geNfXx1TV71TV1VX1u9Mh4GyAqrqiql5eVY+de5YVs7RnOxZW7K8tuw7/m85a9LQkz66q10RYbbQtVfXQqnpYFu8y35Ik3f3lJF+dd7Sl1t19X3df0t3/KMkjkpyf5MwsoouNs7RPuoe5N2fx//M/TPKCqvrDqnrAdNv3zDfWSnB5h3k8NMlDknywqj5ZVT9XVY+Ye6gVsLW7X7X2QszdfdN0BM76wzM3FWHF/rp5uqBbkmSKrOdm8YH+J8w21Wo4JsnlSS5LcmxVnZAk04UMRe3G2W1tu/ue7n53d78wm/x//JvA0j7pHuYe293ndPc7u/vvJ7kiyQemF3U4dM7o7pd3943d/dokW+ceaInd1t2/0N2PSvLzSR6X5Iqq+mBVvXTm2ZbZjVX1i2vfja2q46vql7LJz3bsrIDsr7Oy7t2R7v5qkrOqyqtpG6i7t+7lpvuS/MghHGXVPH9vN3T3nYdykBXkEgPzeEBVbenu+5Kku19ZVTuTfDjJg+Ydbem5vMPMuvsjST4yfab8GVk8B1ww71RLa2nPduzkFQAcVqrqoVk86f5QkodPm3c96Z7b3bfNNdsyq6pXJ7mku//7uu1nJjlvbxf0ZFxV/eq6Ted3967LO7y6u8+aY65lV1UXdfcL5p5jFU1nmn5kko8v05mmhRUAm0ZVvaS73zz3HKvGus/H2s/Dum+c6XImL8sSnmlaWAGwaVTV/5g+D8EhZN3nY+3nYd03TlVdk+R7u/uOqtqa5B1J3tbdr6uqT3X3X591wAE+YwXAYaWqrt7bTVlc84QNYN3nY+3nYd1ns9uZpqvqaUneMV2weVOflEtYAXC4OT7Js7I45fpaleRjh36clWHd52Pt52Hd53FzVZ3W3VcmizNNV9Vzk7wpm/xM08IKgMPNe5I8aNeT7lpV9aeHfpyVYd3nY+3nYd3nsbRnmvYZKwAAgEGujQAAADBIWAEAAAwSVgAAAIOEFQAboqp+5SA+1kOq6qfXfP+IqnrHwXp8ABjl5BUAbIiquqO7H7SH7ZXF8899B/BYW5O8p7v/2sGbcONV1RHdfe/ccwCw8bxjBbDiquqsqrq6qq6qqrdV1daq+sC07f1V9ajpfhdW1eur6mNV9fmqet60/YSq+nBVXVlV11bV91XVuUmOmra9fXrMz1bVW5Ncm+SkqrpjzQzPq6oLp6+Pr6o/nua5qqr+ZpJzkzx2erzfmB7v2un+D6yqN1fVNVX1qap6+rT9xVX1R1X1vqq6oapevY81+IdV9Vtrvv8nVfXa6et/UFWfnP7sN1bVEdP2N1TVZVX16ap6xZqf/fOqelVVXZHkRw/KvyQADnvCCmCFVdXjk7w8yQ9095OSnJ3kvCRv6e4nJnl7ktev+ZETkjw1yXOziJ0k+fEkf9LdpyV5UpIru/ucJHd192nd/aLpfo9Lcn53P767b9zHWK9P8qFpntOTfDrJOUn+bHq8f7Hu/i9L0t39hCQvTPKWqnrgdNtpSZ6fxUUnn19VJ+3lz7w4yQ9W1f2m71+S5E1Vder0839r+v3uTbLr9/mX3X1Gkicm+dtV9cQ1j/fF7j69uy/ax+8JwBIRVgCr7QeS/EF3fyFJuvvWJN+b5Hen29+WRUjt8s7uvq+7r0ty/LTt0iQvqapfS/KE7v7SXv6sG7v74/s50xumee7t7tu/yf2fmuQ/Tfe/PsmNSU6ebnt/d9/e3XcnuS7Jo/f0AN19R5IPJHluVZ2S5H7dfU2Sv5PkyUkuraorp+8fM/3Yj03vSn0qyeOTfNeah/z9/fg9AVgiR849AACbylfWfF1J0t0frqrvT/L3klxYVa/p7rfu4We/vO77tR/yfWA2xtp5782+n/d+J8mvJLk+yZunbZXFu3e/vPaOVfWdSX4hyVO6+7bpMMa1v8P63xWAJecdK4DV9oEkP1pVD0uSqjo2yceSvGC6/UVJPrKvB6iqRye5ubt/O4s4OX266Z41h9btyc1VdWpVbUnyI2u2vz/JP50e+4iqOibJl5I8eC+P85FpzlTVyUkeleSz+5p5T7r7E0lOyuLQxt9bM8vzqurh0+MfO/2+R2cRT7dX1fFJnn2gfx4Ay0VYAayw7v50klcm+VBVXZXkNUm2Z3Fo39VJfiKLz13ty9OSXFVVn8ri80ivm7ZfkOTqqnr7Xn7unCTvySLk/vea7WcneXpVXZPk8iTf1d1fTPLR6eQYv7Hucc5PsmW6/+8neXF3fyXfmouTfLS7b0uS6ZDHlye5ZFqP/5bkhO6+KotDAK/P4rDJj36Lfx4AS8Lp1gFgUlXvSfLa7n7/3LMAsLl4xwqAlTddgPhzWZzJUFQBcMCcvAKAlVJVn0jygHWbf6K7T97T/QFgfzgUEAAAYJBDAQEAAAYJKwAAgEHCCgAAYJCwAgAAGCSsAAAABv1/YZRq1Kuei1MAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N1RgXaaJG7pZ"
      },
      "source": [
        "combined_df = features_df.copy()\n",
        "combined_df['status_group'] = labels_df['status_group']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0d58YjpZG_Uq"
      },
      "source": [
        "# label encode y for visualizing\n",
        "label_map = {\n",
        "    \"functional\": 0,\n",
        "    \"functional needs repair\": 1,\n",
        "    \"non functional\": 2\n",
        "  }\n",
        "\n",
        "combined_df['status_group'] = combined_df['status_group'].map(label_map)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "pyRCBvp7Gur2",
        "outputId": "8600a3d0-d618-4fa2-82be-9e1c5ca790d6"
      },
      "source": [
        "combined_df.groupby('status_group').boxplot(fontsize=10,rot=90,figsize=(30,30),patch_artist=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0         AxesSubplot(0.1,0.559091;0.363636x0.340909)\n",
              "1    AxesSubplot(0.536364,0.559091;0.363636x0.340909)\n",
              "2             AxesSubplot(0.1,0.15;0.363636x0.340909)\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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FPkmSJEmSJEmSJKmnLPZJkiRJkiRJkiRJPWWxT5IkSZIkSZIkSeopi32SJEmSJEmSJElST1nskyRJkiRJkiRJknrKYp8kSZIkSZIkSZLUUxb7JEmSJEmSJEmSpJ6y2CdJkiRJkiRJkiT1lMU+SZIkSZIkSZIkqacs9kmSJEmSJEmSJEk9ZbFPkiRJkiRJkiRJ6imLfZIkSZIkSZIkSVJPWeyTJEmSJEmSJEmSespinyRJkiRJkiRJktRTFvskSZIkSZIkSZKknrLYJ0mSJEmSJEmSJPWUxT5JkiRJkiRJkiSpp1JVrTNMqiT/A9zWOsc6PAr4aesQPeXaTYzrNnGu3cS4bhPn2k2M6zZxrt3EuXYTM8zrtlNVPbp1CEmSJEmSJmLGFfuGWZIlVbVf6xx95NpNjOs2ca7dxLhuE+faTYzrNnGu3cS5dhPjukmSJEmSNDVs4ylJkiRJkiRJkiT1lMU+SZIkSZIkSZIkqacs9k2vv28doMdcu4lx3SbOtZsY123iXLuJcd0mzrWbONduYlw3SZIkSZKmgGf2SZIkSZIkSZIkST3lzj5JkiRJkiRJkiSppyz2SZIkSZIkSZIkST1lsU+SJEmSJEmSJEnqKYt9kiRJkiRJkiRJUk9Z7NPQSnLGhsxpTUm2SvK2JOd34yckeW7rXNo0JNmqdYY+ct02XpKHJdm1dY4+SjI7yWOS/NbIV+tMwy7JrCQvaZ2jr5LMTbJt6xySJEmSJM1UFvumWJIjkvzfJMuT3JlkRZI7W+fqiWeOMfesaU/RPxcCK4GndeP/At7VLk5/JNklyZeTfLcb75nkz1vn6oMkBya5Cfj3brxXkrMbxxp6rtvEJDkcuBb4Yjd+cpJL2qbqhyQnAj8BvgR8rvv6bNNQPVBVDwBvaZ2jb5Lsn+QG4Hrgu0muS7Jv61ySJEmSJM00qarWGWa0JN8DDq+qZa2z9EWS44ETgJ2B74+6tC1wZVW9vEmwnkiypKr2S3JNVe3dzV1XVXu1zjbsknwVeDNw3qi1+25V7dE22fBL8m/Ai4FLXLsN57pNTJKlwMHA4lHrdkNVPaltsuHXvS55SlX9rHWWvknybuCnwMeAu0bmq+qOZqGGXJLrgddV1de78dOBs6tqz7bJJEmSJEmaWTZrHWAT8BMLfRvtn4EvAKcDbx01v8I31DbIvUkeBhRAkt9msNNP49uqqq5KMnru/lZh+qaq/nOttVvVKkufuG4Tcl9VLV9r3fz00ob5T2B56xA99dLu9nWj5orBh5M0tlUjhT6AqvpGEp9XJUmSJEmaZBb7pkiSI7q7S5J8DPg0owouVXVxk2A9UFXLGbwReVSS2cAODB6r2yTZpqp+2DTg8Hs7g9Z2j03yUeB3gD9qmqg/ftoVR0cKpS8Gftw2Um/8Z5IDgUqyOXAS4Acdxue6TcyNSY4GZid5AvB64JuNM/XFLcDiJJ9jzdclZ7WL1A9V9fjWGXroq0nOAxYxeG59KYPH3z4AVXV1y3CSJEmSJM0UtvGcIkkuXM/lqqpXTVuYnkryJ8BfMjhb6IFuumz9NL4kjwSeCgT4dlX9tHGkXkiyM/D3wIHAz4EfAC+vqltb5uqDJI8CPgD8vwwed5cDr3c37vqtY91OssXi+iXZCjgNOJTBul0GvLOq7mkarAeSvH2s+ar6q+nO0kdJ9gDmAXNG5qrqQ+0SDbckV6znclXVwdMWRpIkSZKkGcxin4aW5wptnJFPya+Ln57fcEm2BmZV1YrWWfoiye9U1ZXjzUkaDkm2AaiqX7TO0hddofQgBsW+zwPPAr5RVS9umUuSJEmSJMli3xRL8h7gXcAvGbRW3BN4Y1V9pGmwHug+Df7MqvJslw0w6tPzc4D9gOsY7HjZE1hSVU9rlW3YJTl5fddtbze+JFdX1T7jzWkgyULWc8ZcVb1+GuP0RpJLWf+6PW8a4/RStzPtw8AjuqmfAn9YVTe2S9UPSW4A9gKuqaq9kuwAfKSqntk42tBK8hdjzVfVO6Y7iyRJkiRJM5ln9k29Q6vqLUleCNwKHAF8DbDYtw6jCi+eK7QRqmo+QJKLgX2q6oZuvAeDdqhat227212B/YFLuvHhwFVNEvVEkqcxaHv66LWKpnOB2W1S9cKS7vZ3GOwS+lg3PhK4qUmifnhvd3sE8Ousfi49ikHLZ43v74GTq+oKgCQHAecz+DvW+v2yqh5Icn+SucDtwGNbhxpyd426Pwd4Lp5LKkmSJEnSpLPYN/U2726fA3y8qpYnaZmnD0YKLz/svrbovrRhdh0p9AFU1XeT7N4y0LAbOasqydcYFEpXdOO/BD7XMFofbAFsw+D5ZNtR83cCtrZbh6r6IECS44Gnj+xgTnIu8PWW2YZZVX0VIMn7qmq/UZcuTbJkHT+mNW09UugDqKrFXetijW9JkoczKI4uBX4BfKttpOFWVe8bPU7yXgZnbEqSJEmSpElksW/qXZrk3xm08Tw+yaOBexpnGmojhRdN2PVJ/oHVO15eBlzfME+f7ADcO2p8bzendeiKL19N8k9VdVvrPD20PYNdkHd04226Oa3f1kl2rqpbAJI8HrBgtWFuSfI2Bq08AV7OYCe9xlFVJ3R3z03yRWBuVfn8unG2AnZsHUKSJEmSpJnGYt/UezvwHmB5Va1KcjfgmUIbYB1nMy1n0P7uvKqyaDq2VwLHAyd1468B57SL0ysfAq5K8qlu/ALggw3z9MndSc4EnsigVRsAVXVwu0i98G7gmu7MzQDPwLa7G+KNDNo838Jg3XYC/rhtpN54FfBXwMXd+OvdnMaRQWuGlwE7V9U7kvxWkgOqynbP69CdczjyWm428GjA8/okSZIkSZpkqVq7lqLJlOTqqtpnvDk9WJIPMHhTaFE39VIGrQGLwafpj2mVTTNXkn2A3+2GX6uqa1rm6YsklzM4d+5NwHHAK4D/qapTmgbrgSS/DjyFwb9tV1XVfzeO1AtJtgR264b/XlUr1/f90kOV5BzgAeDgqto9yfbA5VW1f+NoQyvJTqOG9wM/GWlbLEmSJEmSJo87+6ZI9+btbwIPS7I3g50HMGjXtlWzYP1y4FpvoF2a5DtVtX+SG5ulGnJJfsCDd0RSVTs3iNMrSX4L+CnwqdFzVfXDdql645FVdUGSk0a19vxO61A9cQCrC8wFXNowSy8k2Rx4LYOdkDDY5XdeVd3XMNZQS/L+qnrDOnbNU1V2HRjfU6pqnyTXAFTVz5N4pvB6VNVtSfZi1IdosLW4JEmSJEmTzmLf1DkM+CMG55K8j9XFvjuBP2uUqW+2GV1o6Qox23TX7l33j23y9ht1fw5wJPCIRln65nOsfhP8YcDjgZsZtKbU+o0UWX6c5DnAj/BxN64k7wb2Bz7aTb0+ydOqyueJ9TsH2Bw4uxsf0829ulmi4TdyRt97m6bot/uSzKZ7nujOYX6gbaThluQk4DWsbhv70SR/X1ULG8aSJEmSJGnGsY3nFEvyoqr65Hquv6KqPBNsDEmeDZwLfJ9BsfTxwAnAYuA1VfX+dun6JcnSqtq3dY6+6Vp6nlBVFhDGkeS5DM7+eiywkMEu5r+qqkuaBhtySa4HnlxVD3Tj2cA1VbVn22TDLcl1VbXXeHN6sG737QfGm9ODJXkZg5bi+zA4z/XFwJ9X1cebBhti3b9xT6uqu7rx1sC3/DdOkiRJkqTJZbGvMc/vW7+1zmS6uaruaZmnD7oC1YhZDHb6He+b4BOT5IaqelLrHMMuyaOr6n9a5+ib7o3wg6rqjm78CGCxb4SvX5KrgSOr6vvdeGfgEz6fjm8dZwlfU1V7t8rUJ0l2Aw5h8CGkL1fVssaRhlqSG4D9R16/JZkDfMfnVUmSJEmSJpdtPNvL+N+yaUlycFV9JckRa1367SRU1cVj/qBGvG/U/fuBHwAvaZSlV5KcPGo4i8HujR81itM3Vya5FfgYcHFV/bxxnr44HbgmyRUMng+eAby1baReeDNwRZJbGKzbTsAr20YabkmOAo4GHp9k9I7bbYE72qTqlyTvAy6oqr9rnaVHLgT+LcnIWbgvAC5omEeSJEmSpBnJYl97bq18sN8DvgIcPsa1YvW5LxrbsVV1y+iJJI9vFaZnth11/34GZ/itsw2vVquqXZIcAPwBcFqSm4CLquojjaMNtapalGQxg3P7AE6pqv9uGKkXqurLSZ4A7NpN3VxVK1tm6oFvAj8GHsWaHwpZAVzfJFH/LAPOT7IZgyLWoqpa3jjT0EoyC/g2g/brT++mX1lV1zQLJUmSJEnSDGUbz8ZsnaXJto4WbZ7ZtwGSHLn22UtjzWn9kjwKOAt4WVXNbp1nmCV5IfCVkYJBkoczaOv56bbJhluS1wEfrar/7cbbA0dV1dltk2lTkGRXBjtJjwKuBM6vqivaphpOvs6VJEmSJGl6zGodYKYba0fVWnNXTmOcXkmyQ5ILknyhG89LcmzrXMMqyW5JXgRsl+SIUV9/BMxpHK8vTt3AOa0lydwkr+j+Xkd2EB3QOFYfvH30zqCuePX2hnn64jUjhT6Arm3saxrm6Y0kT03ynSS/SHJvklVJ7mydqy+SzGZwlvBuwE+B64CTk1zUNNjw+nKSFyWxbb0kSZIkSVPINp5T75MMzv0a7RPAvgBV9SfTnqg//olBm6zTuvF/MDgPzLNexrYr8Fzg4azZAnUFvgm+XkmeBTwb+M0kfzPq0lwG7Tw1vuuATwPvqKpvtQ7TI2N96Mbn5vHNTpLq2hN0BZgtGmfqi79l0G7348B+wB8CuzRN1BNJ/prB8+xXgP9TVVd1l85IcnO7ZEPttcDJwP1J7mFwxmZV1dy2sSRJkiRJmll8Q3GKJNkNeCLdLqtRl+biLqsN9aiq+pckpwJU1f1JVrUONayq6jPAZ5I8zWLLRvsRsAR4HrB01PwK4I1NEvXPzmVf6IlYkuQs4O+68etY8zGosX0R+FiS87rxa7s5bYCq+l6S2VW1CrgwyTW4i3lDXA/8eVXdNca1A5I8sapunO5Qw6yqth3/uyRJkiRJ0kNlsW/quMvqobsrySOBkZ0bTwWWr/9HNl1J3lJV7wGOTnLU2ter6vUNYvVCVV0HXJfko1XlTr6NkOT9VfUG4JIkDyr2VdXzGsTqkxOBtzHYtVzAlxgU/LR+pwB/DBzfjb8E/EO7OL1yd5ItgGuTvIdBy13bum+AqrpwPdeWJ7mCB3dz2KQlGWs9lgO3+XwrSZIkSdLkiRsxppa7rCaue4NoIbAH8F3g0cCLq+r6psGGVJLDq+rSJK8Y63pVfXC6M/VFkn+pqpckuYGuuDxaVe3ZIFYvJNm3qpYm+b2xrlfVV6c700ySZGFVndg6R98k+WRVvah1jmGUZCfgdmBzBjuXtwPOrqrvNQ02AyS5pqr2bp1jmCT5NoMC6A3d1JMYvKbbDji+qi5vlU2SJEmSpJnEYt8US/JoBjv5HseonZRV9apWmfokyWYMdkkGuLmq7mscSTNQkt+oqh93b4I/SFXdNt2Z+qQ7L+1DVfWy1llmmiRXV5U7hTaSRRe14N/rgyW5GHjbSHvTJPOAdwBvAS6uqie3zCdJkiRJ0kxhG8+p9xng68C/Ap43t/EOYHWhdJ8kVNWH2kYabkku5cG705YzOJPuvKq6Z/pTDbeq+nF394SqOmX0tSRnMGgZqHWoqlVJdkqyRVXd2zqPxBg7dDd169q5PMIdzJoiu4w+x7CqbkqyW1XdkqRlLkmSJEmSZhSLfVNvq7WLB9owST4M/DZwLasLpQVY7Fu/Wxi0PF3UjV/K4KzIXYDzgWMa5eqDZ/Lgwt6zxpjTg90CXJnkEuCukcmqOqtdJEmbUZvaAAATRElEQVSjPLd1gE2AH3Z4sBuTnANc1I1fCtyUZEvAbg2SJEmSJE0Si31T77NJnl1Vn28dpIf2A+aVvWY31oFVtf+o8aVJvlNV+ye5cZ0/tQlLcjxwArBzktFnQm4LXNkmVe98v/uaxWDdNDnc+jIxrttabEc8OZL8JrATa7Zm/1p3+9RWuYbYHzF4fn1DN74SeBODQt/8RpkkSZIkSZpxPLNviiVZAWwNrGTwxkaAqqq5TYP1QJKPA68f1WJRGyDJMuCwqvphN/4t4LKq2t1zrMaWZDtge+B04K2jLq2oqjvapOqnJHMZ/Bu3onWWmSDJH1XVP7XOMWySnFRVH1jXXJJDq+ryNumGW/e6ZOTF3xbA5sBdvi4ZX9fW+aXATYzqOFBVz2uXqt+SfLKqXtQ6hyRJkiRJfWexT0Nn1Jlz2wJPBq5iUCwFwDfV1i/Js4FzGeyyCvB4Bp+qXwy8pqre3y5dPyT5NWDOyHikcKp1S7IfcCGrd/UtB15VVUvbpRp+SXYB3syDdwod3CxUDyS5uqr2WWvODzNspAwOTXs+8NSqeut437+pS3IzsGdVrRz3m7VB/LuVJEmSJGlyWOybYkmeMdb8SMsnPViS31vf9ar66nRl6avuLJzduuHNVXVPyzx9keRw4CzgMcDtDAowy6rqiU2D9UDX/vR1VfX1bvx04Oyq2rNtsuGW5DoGxfmlrN4phEXSsSU5CjgaeDrw9VGXtgUeqKpDmgTrOQsuGybJF4Ajq+oXrbPMFGMV7iVJkiRJ0sbzzL6p9+ZR9+cABzB4U9ddG+uwocW8JN+qqqdNdZ6e2hd4HIO/8b2SUFUfahupF94FPBX416raO8l84OWNM/XFqpFCH0BVfSPJ/S0D9cT9VXVO6xA98k3gx8CjgPeNml8BXD/mT2gNSY4YNZzF4HxcPxCyYe4Grk3yZdbsOPD6dpEkSZIkSZIs9k25qjp89DjJYwHbKE6OOeN/y6YnyYeB3wauZdSZQoDFvvHdV1U/SzIryayquiKJf68b5qtJzgMWMXi8vRRYnGQfgKq6umW4IXZpkhOAT7Fm8cCzIsdQVbcBtyV5GfCjkV3LSR4G7Ajc2jBeX4x+XXI/gzV7fpsovXNJ96XJk9YBJEmSJEmaCWzjOc2683FurKp5rbP0na2fxpZkGTCv/OPeaEn+FXgBcDqDnUO3A/tX1YFNg/VAkivWc7k8g25sSX4wxnRV1c7THqZHkiwBDqyqe7vxFsCVVbV/22Sa6brH2i7d8Oaquq9lnj5Jsj3w2Kq6ftTcoVV1ecNYkiRJkiTNCO7sm2JJFjLY5QKDdllPBtzhoqn0XeDXGbS608Z5PoN2dm8EXgZsB7yjaaKeqKr567ue5BVV9cHpytMXVfX41hl6arORQh9AVd3bFWE0jiQ7Ax9g0LK4gG8Bb6yqW5oG64EkBwEfZLAbMsBju3/bPId5HZIsBp7H4P85lgK3J7myqk4GsNAnSZIkSdLksNg39ZaMun8/sKiqrmwVZoax9dPYHgXclOQq1mwL+Lx2kfqhqu4aNbQwNblOwjV9kCSbA8cDz+imFgPnuVtoXP+T5HlVdQlAkucDP22cqS/+Gfg74IXd+A8YtN99SrNE/fE+4NCquhkgyS4M1m7fpqmG23ZVdWeSVwMfqqq3J/F8TUmSJEmSJpnFvilWVR9cu+VTyzx9kmRr4JdV9UD3htpuwBdGvQl+TLt0Q+0vWwfomyQrWL0Dd41LDFoqzp3mSDORxfmxnQNsDpzdjY/p5l7dLFE/HAd8NMnfMnhs/Sfwh20j9cZWVfXhUeOPJHlzszT9svlIoQ+gqv6jK9hr3TZL8hvAS4DTWoeRJEmSJGmm8sy+KTZWyyfAlk8bIMlS4HeB7YErge8A91bVy5oG64EkOwAjZ1ddVVW3t8wjecbm2JJcV1V7jTensSXZBqCqftE6S18kOQP4OXARgw85vJTB8+yZAFV1R7t0wy3JPwIPAB/ppl4GzK6qV7VLNdySHAm8DfhGVZ3QtZE9s6pe1DiaJEmSJEkzisW+KdYVrI5eu+VTVdnyaRwjxYEkJwIPq6r3JLm2qp7cOtswS/ISBm/aLmZQYP5d4M1V9YmWubRpS3JNVe3dOsewSXI1cGRVfb8b7wx8wsLo2JK8vKo+kuTksa5X1VnTnalvkvxgPZerqnaetjA9k2RL4HXA07uprwNnV9XKdf+UJEmSJEnS1LON59Sz5dPEJcnTGHxy/thubnbDPH1xGrD/yG6+JI8G/hWw2KeWPKt0bG8GrkhyC4Pi/E7AK9tGGmpbd7fbNk3RY1X1+NYZ+qor6p3VfWkDJLmQMdpkuxtSkiRJkqTJZbFv6i1J8g+s2fJpScM8ffIG4FTgU1V1Y7fj5YrGmfpg1lptO38GzGoVRpuGJA9ncGba4xj13FJVr+9u/6RNsuFWVV9O8gRg127qZncJrVtVnZdkNnBnVf116zx91H3g6HjgGd3UYuC8Uefhai1J/qWqXpLkBsYuXO3ZIFZffHbU/TnAC4EfNcoiSZIkSdKMZRvPKWbLp4cuyVwGrcVWtM7SB0nOBPYEFnVTLwWur6pT2qXSTJfkm8C3gRsYnGkFQFV9sFmoIZbk4Kr6SpIjxrpeVRdPd6Y+SXJVVR3QOkcfdR9A2pzBecIAxwCrqurV7VINtyS/UVU/TrLTWNer6rbpztRXSWYxOL/vwNZZJEmSJEmaSSz2aWgl2Q+4kEG7tgD/C7yqqpY2DdYDSV4E/E43/HpVfaplHs18I2dsts7RF0n+qqre3rW4W1vZ4m79kvw1g4LVx4C7Ruar6upmoXoiyXVVtdd4c3qwJGes/cGZsea0bkl2BT5XVf9P6yySJEmSJM0kFvumWJLnAu9kcA7TZgyKVlVVc5sG64Ek1wOvq6qvd+OnM9gVabssacgkeSPwCwYt2361c7mq7mgWSjNWkrFaOldVHTztYXomydXAkVX1/W68M/AJi/XjG+tDDUmu93XJuiVZwZqtT/8bOLWqPtkokiRJkiRJM5Jn9k299wNHADeUldWNtWqk0AdQVd9Icn/LQMNsjDfUfnUJC8yaevcCZwKnsfpxWMDOzRL1QJKTx5heDiytqmunO0+PHFtVt4ye6IpWGt+bgSuSjKzf44BXtosz/JIcD5wA/Hb3QaQR2wLfbJOqH6pq29YZJEmSJEnaFLizb4p1uw8OqaoHxv1mrSHJ+4GHMTh7rhicPXcP8BGwXZs0TLrCwQFV9dPWWfokyT8D+wGXdlPPBa5nUID5eFW9p1G0obaOHVZLq2rfVpn6Iskc4E+BQxi0x/4O8NdVdU/TYEMsyXbA9sDpwFtHXVrh7uX1S/LlqjpkvDlJkiRJkvTQuLNv6r0F+HySr7Jma7uz2kXqjZHzg/6iu013uzeD4p/t2qTh8T3g7tYhemhHYJ+q+gVAkrcDnwOeASwFLPaNkmQ34InAdkmOGHVpLjCnTare+RBwJ4MW4wBHAx8GjmyWaMhV1XJgeZIPAHdU1QqAJHOTPKWq/q1twuHTFZW3Ah6VZHtWv4abC/xms2CSJEmSJM1QFvum3gIG51jNAbZonKVvPsugqDfyBlFheztpWN0FXNvtZh79wYbXt4vUC7/GqPUC7gN2qKpfJlm5jp/ZlO3KYPfjw4HDR82vAF7TJFH/7FFV80aNr0hyU7M0/XIOMHpH6S/GmNPAa4E3AI9h8MGFkddydwJ/2yqUJEmSJEkzlcW+qfeYqtqjdYie2pdBe7tLGLxJNNLe7rVJPmF7O2mofLr70sb5KPBvST7TjQ8H/jnJ1oAFmLVU1WeAzyR5WlV9q3Wenro6yVOr6tsASZ4CLGmcqS8y+vzlqnogia+lx1BVHwA+kOTEqlrYOo8kSZIkSTOdZ/ZNsSTvAf61qi5vnaVvknwNePao9nbbMGhv9/sMdvfNW9/PS1IfJNkP+J1ueGVVWXgZR/fc+i7gl8AXgT2BN1bVR5oG64EkyxjskPxhN/VbwM3A/UBV1Z6tsg27JBcDixns5gM4AZhfVS9oFqoHkuwBzGNUq92q+lC7RJIkSZIkzTwW+6ZYkhXA1gzatN3HYIdaVdXcpsF6IMm/A0+qqvu68ZbAdVW1W5JrqmrvtgkljUjyAwatdtdQVTs3iNMrSZ4OPKGqLkzyaGCbqvpB61zDLMm1VfXkJC9ksOv7ZOBrVbXXOD+6yUuy0/quV9Vt05Wlb5L8GvA3DM4MLuDLwBuq6vamwYZYdw7pQQyKfZ8HngV8o6pe3DKXJEmSJEkzja2HplhVbZvkEcATGPWJZm0Q29tJ/bHfqPtzgCOBRzTK0hvdG+H7MdhpdSGwOfARVu/009g2726fA3y8qpYnWd/3q2Mxb+K6ot4ftM7RMy8G9gKuqapXJtmBwb9xkiRJkiRpErmzb4oleTVwErAjcC3wVOCbVXVI02A9YXs7qb+SLK2qfVvnGGZJrgX2Bq4e2a2c5HpbKa5fkncDL2DQxvMA4OHAZ6vqKU2DaUZLciFj72B+VYM4vZDkqqo6IMlSYD6wAlhWVbs1jiZJkiRJ0ozizr6pdxKwP/DtqpqfZDfg/zTO1Btdcc8CnzTkkuwzajiLwW41n2PGd29VVZIC6HYuaxxV9dbu3L7lVbUqyV3A81vn0oz32VH35wAvBH7UKEtfLEnycOB8YCnwC+BbbSNJkiRJkjTz+Ebs1Lunqu5JQpItq+rfk+zaOpQkTbL3sXrHy/3ArQxaeWodMug7+dkk5wEPT/Ia4FUM3hTXGJIcXFVfSXLEqLnR33Lx9KfSpqKqPjl6nGQR8I1GcXqhqk7o7p6b5IvA3Kq6vmUmSZIkSZJmIot9U+//6z7R/GngS0l+DnhejqSZ5lnAi4DHsfq55Q+Ad7QKNOy6HX1HAicDdzI4t+8vqupLbZMNtWcAX2FwhmsBWevWYp+m0xOAX2sdYpgl+fJI6/qqunXtOUmSJEmSNDks9k2xqnphd/cvk1wBbAd8sWEkSZoKnwb+F7gauKdxlj65Gvjfqnpz6yA9sSLJycB3WV3kgzHOUZMmW5IVrPlY+2/glEZxhlqSOcBWwKOSbM/qv9W5wG82CyZJkiRJ0gxlsW8aVdVXW2eQpCmyY1X9fusQPfQU4GVJbgPuGpmsqj3bRRpq23S3uzI4D/czDIoIhwNXtQqlma9ru/vEqvph6yw98VrgDcBjGJzVN7L7dgWwsGEuSZIkSZJmpFT5YXhJ0kOT5O+BhVV1Q+ssfZJkp7Hmq8p2z+uR5GvAc6pqRTfeFvhcVT2jbTLNZEluqKontc7RJ0n+Anh/Vd2Z5G3APsA7q+rqxtEkSZIkSZpRZrUOIEmaEZ4OLE1yc5Lrk9yQ5PrWoYZdVd021lfrXD2wA3DvqPG93Zw0la5Osn/rED3z4q7Q93TgYOAfgHMaZ5IkSZIkacaxjackaTI8q3UAbVI+BFyV5FPd+AXAP7WLo03E2m13A5Rtd9drVXf7HOD8qvpckne1DCRJkiRJ0kxkG09JktQ7SfYBfrcbfq2qrmmZRzOfbXc3XpLPAv8FPJNBC89fAldV1V5Ng0mSJEmSNMNY7JMkSZLGkeTDVXXMeHNaLclWwO8DN1TV/03yG8CTquryxtEkSZIkSZpRLPZJkiRJ40hydVXtM2o8m0ERa17DWJIkSZIkScxqHUCSJEkaVklOTbIC2DPJnd3XCuB24DON40mSJEmSJLmzT5IkSRpPktOr6tTWOSRJkiRJktbmzj5JkiRpfJ9NsjVAkpcnOSvJTq1DSZIkSZIkWeyTJEmSxncOcHeSvYA/Bb4PfKhtJEmSJEmSJIt9kiRJ0oa4vwb9758P/G1V/R2wbeNMkiRJkiRJbNY6gCRJktQDK5KcCrwceEaSWcDmjTNJkiRJkiS5s0+SJEnaAC8FVgLHVtV/AzsCZ7aNJEmSJEmSBBl0I5IkSZIkSZIkSZLUN+7skyRJksaR5Igk/zfJ8iR3JlmR5M7WuSRJkiRJktzZJ0mSJI0jyfeAw6tqWesskiRJkiRJo7mzT5IkSRrfTyz0SZIkSZKkYeTOPkmSJGkcST4A/DrwaWDlyHxVXdwslCRJkiRJErBZ6wCSJElSD8wF7gYOHTVXgMU+SZIkSZLUlDv7JEmSJEmSJEmSpJ7yzD5JkiRpHEl2TPKpJLd3X59MsmPrXJIkSZIkSRb7JEmSpPFdCFwCPKb7urSbkyRJkiRJaso2npIkSdI4klxbVU8eb06SJEmSJGm6ubNPkiRJGt/Pkrw8yezu6+XAz1qHkiRJkiRJcmefJEmSNI4kOwELgacBBXwTOLGq/rNpMEmSJEmStMmz2CdJkiSNI8kHgTdU1c+78SOA91bVq9omkyRJkiRJmzrbeEqSJEnj23Ok0AdQVXcAezfMI0mSJEmSBFjskyRJkjbErCTbjwy6nX2bNcwjSZIkSZIE+AaFJEmStCHeB3wryce78ZHAgoZ5JEmSJEmSAM/skyRJkjZIknnAwd3wK1V1U8s8kiRJkiRJYLFPkiRJkiRJkiRJ6i3P7JMkSZIkSZIkSZJ6ymKfJEmSJEmSJEmS1FMW+yRJkiRJkiRJkqSestgnSZIkSZIkSZIk9dT/D0L0JrY0F+F6AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 2160x2160 with 4 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}