Jupyter.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Jupyter.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "_kHS_aVnCAFW",
        "WK-zi4nZwNfa",
        "zKGjgo_MCHLt",
        "MYSVHrEFxwbR",
        "lXzuTYHW1IJ7",
        "KTJcziIwzymf",
        "Sqmf8vBS5w1C",
        "BAChLP2f00zS"
      ],
      "authorship_tag": "ABX9TyO5mJYMJ2+sZ3lL/mo5+2P3",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/amitkp57/Jupyter/blob/main/Jupyter.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_kHS_aVnCAFW"
      },
      "source": [
        "### Move to GPU mode if you are in Google Colab\r\n",
        "Go to `Runtime` -> `Change runtime type` to activate GPU."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WK-zi4nZwNfa"
      },
      "source": [
        "### Provide your credentials to the runtime\r\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2Gym1DvVvfzL",
        "outputId": "ad680bf6-8e68-473d-b083-b6ae32949090"
      },
      "source": [
        "from google.colab import auth\r\n",
        "auth.authenticate_user()\r\n",
        "print('Authenticated')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Authenticated\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zKGjgo_MCHLt"
      },
      "source": [
        "### Mount Google Drive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_0lGGQxtCBGm",
        "outputId": "445bd247-ea0b-4002-ee3c-d380abb483e0"
      },
      "source": [
        "import os\r\n",
        "from google.colab import drive\r\n",
        "drive.mount('/content/gdrive')\r\n",
        "WORKING_DIRECTORY = '/content/gdrive/MyDrive/Data/Jupyter'\r\n",
        "os.environ['WORKING_DIRECTORY'] = WORKING_DIRECTORY\r\n",
        "%cd $WORKING_DIRECTORY\r\n",
        "!ls -latr"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n",
            "/content/gdrive/MyDrive/Data/Jupyter\n",
            "total 789\n",
            "-rw------- 1 root root    530 Mar 12 12:15 requirements.txt\n",
            "-rw------- 1 root root     85 Mar 12 12:15 main.py\n",
            "-rw------- 1 root root   1069 Mar 12 12:15 LICENSE\n",
            "-rw------- 1 root root 780436 Mar 12 12:15 Jupyter-muhammad.ipynb\n",
            "-rw------- 1 root root   1193 Mar 12 12:18 README.md\n",
            "-rw------- 1 root root   3565 Mar 12 12:18 Jupyter.ipynb\n",
            "-rw------- 1 root root   1830 Mar 12 12:18 .gitignore\n",
            "drwx------ 3 root root   4096 Mar 12 12:21 data\n",
            "drwx------ 3 root root   4096 Mar 12 14:04 results\n",
            "drwx------ 3 root root   4096 Mar 12 14:26 scripts\n",
            "drwx------ 8 root root   4096 Mar 12 14:26 .git\n",
            "-rw------- 1 root root      0 Mar 12 14:27 app.log\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MYSVHrEFxwbR"
      },
      "source": [
        "### Clone git repo"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_A5TX_whyILW",
        "outputId": "c68f8c8e-83ef-4385-e6bc-6ac68d53033d"
      },
      "source": [
        "%cd $WORKING_DIRECTORY\r\n",
        "!git config --global user.email \"amitpradhanorissa@gmail.com\"\r\n",
        "!git config --global user.name \"Amit Pradhan\"\r\n",
        "# !git clone https://github.com/amitkp57/Jupyter\r\n",
        "!git pull origin pramit-dev\r\n",
        "# !pip install -r requirements.txt\r\n",
        "!pip install datasketch"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/gdrive/MyDrive/Data/Jupyter\n",
            "remote: Enumerating objects: 11, done.\u001b[K\n",
            "remote: Counting objects: 100% (11/11), done.\u001b[K\n",
            "remote: Compressing objects: 100% (4/4), done.\u001b[K\n",
            "remote: Total 7 (delta 4), reused 4 (delta 3), pack-reused 0\u001b[K\n",
            "Unpacking objects: 100% (7/7), done.\n",
            "From https://github.com/amitkp57/Jupyter\n",
            " * branch            pramit-dev -> FETCH_HEAD\n",
            "   9713a8a..c78f09a  pramit-dev -> origin/pramit-dev\n",
            "Updating 9713a8a..c78f09a\n",
            "Fast-forward\n",
            " Jupyter.ipynb             | 2612 \u001b[32m++++++++++++++++++++++++++++++++++++++++++++\u001b[m\u001b[31m-\u001b[m\n",
            " scripts/GraphicalViews.py |    7 \u001b[32m+\u001b[m\u001b[31m-\u001b[m\n",
            " 2 files changed, 2604 insertions(+), 15 deletions(-)\n",
            "Requirement already satisfied: datasketch in /usr/local/lib/python3.7/dist-packages (1.5.3)\n",
            "Requirement already satisfied: numpy>=1.11 in /usr/local/lib/python3.7/dist-packages (from datasketch) (1.19.5)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lXzuTYHW1IJ7"
      },
      "source": [
        "### Setup meta data\r\n",
        "\r\n",
        "Creates datasets.txt, tables.txt and columns.json in the /data folder. These files are used for querying Google Bigquery tables. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1_2rSY2c18EW",
        "outputId": "4a34b26b-6c79-4148-a815-0a20ac811cbc"
      },
      "source": [
        "from scripts.MetaData import save_locally\r\n",
        "DATA_PATH = f'{WORKING_DIRECTORY}/data'\r\n",
        "os.environ[\r\n",
        "        'GOOGLE_APPLICATION_CREDENTIALS'] = f'{DATA_PATH}/IntroDB-35dbe741f4c7.json'\r\n",
        "# save_locally(DATA_PATH)\r\n",
        "print('Completed!')"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Completed!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KTJcziIwzymf"
      },
      "source": [
        "### Jaccard similarity\r\n",
        "\r\n",
        "Jaccard similarity between columns based on minHash"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "odDDAXdCz9qb",
        "outputId": "ed883eb0-6683-4d7a-c3c1-db75f29342cf"
      },
      "source": [
        "import scripts.ClusterColumns as clusterColumns\r\n",
        "\r\n",
        "jaccard = clusterColumns.calculate_jaccard_similarity(override=False)\r\n",
        "jaccard"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    .dataframe thead th {\n",
              "        text-align: right;\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>bigquery-public-data.covid19_aha.hospital_beds.county_fips_code</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.county_name</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.state_name</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.county_fips_code</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.county_name</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.state_name</th>\n",
              "      <th>bigquery-public-data.covid19_ecdc.covid_19_geographic_distribution_worldwide.countries_and_territories</th>\n",
              "      <th>bigquery-public-data.covid19_ecdc.covid_19_geographic_distribution_worldwide.geo_id</th>\n",
              "      <th>bigquery-public-data.covid19_ecdc.covid_19_geographic_distribution_worldwide.country_territory_code</th>\n",
              "      <th>bigquery-public-data.covid19_ecdc_eu.covid_19_geographic_distribution_worldwide.countries_and_territories</th>\n",
              "      <th>bigquery-public-data.covid19_ecdc_eu.covid_19_geographic_distribution_worldwide.geo_id</th>\n",
              "      <th>bigquery-public-data.covid19_ecdc_eu.covid_19_geographic_distribution_worldwide.country_territory_code</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.airport_traffic.aggregation_method</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.airport_traffic.version</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.airport_traffic.airport_name</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.airport_traffic.city</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.airport_traffic.state_region</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.airport_traffic.country_iso_code_2</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.airport_traffic.country_name</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.city_congestion.city_name</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.commercial_traffic.alpha_code_3</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.commercial_traffic.country_iso_code_2</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.commercial_traffic.region</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.commercial_traffic.version</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.commercial_traffic_by_industry.alpha_code_3</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.commercial_traffic_by_industry.region</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.commercial_traffic_by_industry.industry</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.commercial_traffic_by_industry.version</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.fuel_station_daily_fillups.vehicle_class</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.fuel_station_daily_fillups.version</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.fuel_station_weekly_fillups.state_province</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.fuel_station_weekly_fillups.country_iso_code_2</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.fuel_station_weekly_fillups.version</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.lookup_region.country_iso_code_2</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.lookup_region.region_id</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.lookup_region.region_description</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.lookup_region.states</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.port_traffic.country_iso_code_2</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.port_traffic.port_id</th>\n",
              "      <th>bigquery-public-data.covid19_geotab_mobility_impact.port_traffic.port</th>\n",
              "      <th>...</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.nta</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.nta_name</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.location_1</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.state</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.address</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.curb_loc</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.status</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.health</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.spc_latin</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.spc_common</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.steward</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.guards</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.sidewalk</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.user_type</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.problems</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.root_stone</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.root_grate</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.root_other</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.trunk_wire</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.trnk_light</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.trnk_other</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.brch_light</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.brch_shoe</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.brch_other</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.address</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.zip_city</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.boroname</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.nta</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.nta_name</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.state</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.species_scientific_name</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.species_common_name</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.form</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.growth_rate</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.fall_color</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.environmental_tolerances</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.location_tolerances</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.notes_suggested_cultivars</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.tree_size</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.comments</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.county_name</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.007812</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.03125</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.state_name</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.031250</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.03125</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.492188</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.county_fips_code</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.county_name</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.03125</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</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",
              "      <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",
              "      <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",
              "      <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>bigquery-public-data.new_york_trees.tree_species.environmental_tolerances</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.046875</td>\n",
              "      <td>0.039062</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.054688</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.location_tolerances</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.046875</td>\n",
              "      <td>0.039062</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.039062</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.054688</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.078125</td>\n",
              "      <td>0.023438</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.notes_suggested_cultivars</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.054688</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.039062</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.tree_size</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.078125</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.078125</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_species.comments</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.085938</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.023438</td>\n",
              "      <td>0.007812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1688 rows × 1688 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    bigquery-public-data.covid19_aha.hospital_beds.county_fips_code  ...  bigquery-public-data.new_york_trees.tree_species.comments\n",
              "bigquery-public-data.covid19_aha.hospital_beds....                                                1.0                ...                                           0.000000        \n",
              "bigquery-public-data.covid19_aha.hospital_beds....                                                0.0                ...                                           0.000000        \n",
              "bigquery-public-data.covid19_aha.hospital_beds....                                                0.0                ...                                           0.000000        \n",
              "bigquery-public-data.covid19_aha.staffing.count...                                                1.0                ...                                           0.000000        \n",
              "bigquery-public-data.covid19_aha.staffing.count...                                                0.0                ...                                           0.000000        \n",
              "...                                                                                               ...                ...                                                ...        \n",
              "bigquery-public-data.new_york_trees.tree_specie...                                                0.0                ...                                           0.007812        \n",
              "bigquery-public-data.new_york_trees.tree_specie...                                                0.0                ...                                           0.023438        \n",
              "bigquery-public-data.new_york_trees.tree_specie...                                                0.0                ...                                           0.007812        \n",
              "bigquery-public-data.new_york_trees.tree_specie...                                                0.0                ...                                           0.000000        \n",
              "bigquery-public-data.new_york_trees.tree_specie...                                                0.0                ...                                           1.000000        \n",
              "\n",
              "[1688 rows x 1688 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Sqmf8vBS5w1C"
      },
      "source": [
        "### Find columns with Jaccard similarity greater than a threshold value\r\n",
        "\r\n",
        "We use MinHash based LSH t find columns with Jaccard similarity greater than a given threshold value."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j1W6x6_O6Zud",
        "outputId": "e4766060-7178-4c9c-cdc5-57a9fbe474ed"
      },
      "source": [
        "import scripts.QueryDatabase as queryDatabase\r\n",
        "import scripts.ClusterColumns as clusterColumns\r\n",
        "\r\n",
        "RESULTS_PATH = f'{WORKING_DIRECTORY}/results'\r\n",
        "string_columns = queryDatabase.get_columns('STRING')\r\n",
        "# np.savez(f'{RESULTS_PATH}/string_columns.npz', string_columns=string_columns)\r\n",
        "lsh = clusterColumns.build_minhash_lsh(string_columns, threshold=0.7)\r\n",
        "print(clusterColumns.get_all_similar_columns(lsh, string_columns[0]))\r\n",
        "print('Completed!')"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['bigquery-public-data.covid19_weathersource_com.county_day_history.county_fips_code', 'bigquery-public-data.covid19_public_forecasts.county_28d.county_fips_code', 'bigquery-public-data.covid19_public_forecasts.county_14d_historical_.county_fips_code', 'bigquery-public-data.covid19_usafacts.summary.county_fips_code', 'bigquery-public-data.covid19_public_forecasts.county_28d_historical.county_fips_code', 'bigquery-public-data.covid19_public_forecasts_asia_ne1.county_14d.county_fips_code', 'bigquery-public-data.covid19_google_mobility_eu.mobility_report.census_fips_code', 'bigquery-public-data.covid19_symptom_search.symptom_search_sub_region_2_daily.sub_region_2_code', 'bigquery-public-data.covid19_public_forecasts.county_14d.county_fips_code', 'bigquery-public-data.covid19_public_forecasts.county_28d_historical_.county_fips_code', 'bigquery-public-data.covid19_aha.staffing.county_fips_code', 'bigquery-public-data.covid19_public_forecasts_asia_ne1.county_14d_historical.county_fips_code', 'bigquery-public-data.covid19_public_forecasts_asia_ne1.county_14d_historical_.county_fips_code', 'bigquery-public-data.covid19_symptom_search.symptom_search_sub_region_2_weekly.sub_region_2_code', 'bigquery-public-data.covid19_nyt.us_counties.county_fips_code', 'bigquery-public-data.covid19_aha.hospital_beds.county_fips_code', 'bigquery-public-data.covid19_jhu_csse.summary.fips', 'bigquery-public-data.covid19_public_forecasts_asia_ne1.county_28d_historical_.county_fips_code', 'bigquery-public-data.covid19_usafacts.deaths.county_fips_code', 'bigquery-public-data.covid19_public_forecasts_asia_ne1.county_28d_historical.county_fips_code', 'bigquery-public-data.covid19_jhu_csse_eu.summary.fips', 'bigquery-public-data.covid19_nyt.mask_use_by_county.county_fips_code', 'bigquery-public-data.covid19_public_forecasts_asia_ne1.county_28d.county_fips_code', 'bigquery-public-data.covid19_public_forecasts.county_14d_historical.county_fips_code', 'bigquery-public-data.covid19_usafacts.confirmed_cases.county_fips_code', 'bigquery-public-data.covid19_google_mobility.mobility_report.census_fips_code']\n",
            "Completed!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BAChLP2f00zS"
      },
      "source": [
        "### Top-k similar columns based on Jaccard similarity\r\n",
        "\r\n",
        "We use minhash LSH based forest to query top k columns based on Jaccard similarity"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w60j5aUM1gMS",
        "outputId": "de552695-feec-4b67-fd63-a8eecba9b654"
      },
      "source": [
        "import scripts.QueryDatabase as queryDatabase\r\n",
        "import scripts.ClusterColumns as clusterColumns\r\n",
        "\r\n",
        "string_columns = queryDatabase.get_columns('STRING')\r\n",
        "forest = clusterColumns.build_lsh_forest(string_columns)\r\n",
        "print(clusterColumns.get_top_k(forest, string_columns[0], 10))\r\n",
        "print('Completed!')"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['bigquery-public-data.covid19_nyt.mask_use_by_county.county_fips_code', 'bigquery-public-data.covid19_symptom_search.symptom_search_sub_region_2_daily.sub_region_2_code', 'bigquery-public-data.covid19_nyt.us_counties.county_fips_code', 'bigquery-public-data.covid19_jhu_csse_eu.summary.fips', 'bigquery-public-data.covid19_google_mobility_eu.mobility_report.census_fips_code', 'bigquery-public-data.covid19_aha.hospital_beds.county_fips_code', 'bigquery-public-data.covid19_public_forecasts.county_14d.county_fips_code', 'bigquery-public-data.covid19_google_mobility.mobility_report.census_fips_code', 'bigquery-public-data.covid19_aha.staffing.county_fips_code', 'bigquery-public-data.covid19_jhu_csse.summary.fips']\n",
            "Completed!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qCyOe3jcnT_o"
      },
      "source": [
        "### Simple Random Sampling on tables\r\n",
        "\r\n",
        "Sample 100000 values for each table and store the table data locally"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KIL7o-h6nktz"
      },
      "source": [
        "from scripts.QueryDatabase import save_all_table_data\r\n",
        "save_all_table_data(override=False, sample_size=10000)"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gsQ6XaIOYoF0"
      },
      "source": [
        "### Calculate Pearson correlation matrix\r\n",
        "\r\n",
        "Calculates Pearson correlation matric for each column combination"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 462
        },
        "id": "w7D5HmCbY26p",
        "outputId": "0e2d7b77-088f-4e39-82e6-9d5f5786347e"
      },
      "source": [
        "import scripts.PearsonCorrelation as pearsonCorrelation\r\n",
        "\r\n",
        "# columns, table_names = pearsonCorrelation.get_table_values(sample_size=1000)\r\n",
        "pearson = pearsonCorrelation.get_pandas_correlation(override=False)\r\n",
        "pearson"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>bigquery-public-data.covid19_aha.hospital_beds.cbsa_code</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.total_hospital_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.acute_long_term_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.alcohol_drug_abuse_dependency_inpatient_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.burn_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.cardiac_intensive_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.gen_medical_surgical_adult_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.gen_medical_surgical_pediatric_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.intermediate_nursing_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.medical_surgical_intensive_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.neonatal_intensive_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.neonatal_intermediate_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.obstetric_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.other_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.other_intensive_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.other_long_term_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.other_special_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.pediatric_intensive_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.physical_rehabilitation_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.psychiatric_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.skilled_nursing_care_beds</th>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.num_airborne_infection_isolation_rooms</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.cbsa_code</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.total_personnel_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.total_hospital_unit_personnel_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.physicians_and_dentists_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.registered_nurses_pt</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.all_other_personnel_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.full_time_nursing_home_rns</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.laboratory_technicians_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.licensed_practical_vocational_nurses_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.medical_dental_residents_interns_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.nursing_assistive_personnel_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.other_trainees_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.pharmacists_licensed_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.pharmacy_technicians_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.radiology_technicians_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.registered_nurses_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.respiratory_therapists_ft</th>\n",
              "      <th>bigquery-public-data.covid19_aha.staffing.total_nursing_home_personnel_ft</th>\n",
              "      <th>...</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.wire_2nd</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.wire_other</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.inf_canopy</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.inf_guard</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.inf_wires</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.inf_paving</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.inf_outlet</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.inf_shoes</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.inf_lights</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.inf_other</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.cb_num</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.borocode</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.cncldist</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.st_assem</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.st_senate</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.boro_ct</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.x_sp</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.y_sp</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.objectid_1</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.latitude</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.longitude</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.census_tract</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.bin</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2005.bbl</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.tree_id</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.block_id</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.created_at</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.tree_dbh</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.stump_diam</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.zipcode</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.cb_num</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.borocode</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.cncldist</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.st_assem</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.st_senate</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.boro_ct</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.latitude</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.longitude</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.x_sp</th>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.y_sp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.cbsa_code</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.211892</td>\n",
              "      <td>0.092799</td>\n",
              "      <td>0.118284</td>\n",
              "      <td>0.110501</td>\n",
              "      <td>0.167656</td>\n",
              "      <td>0.199185</td>\n",
              "      <td>0.167363</td>\n",
              "      <td>0.045935</td>\n",
              "      <td>0.189978</td>\n",
              "      <td>0.148726</td>\n",
              "      <td>0.145951</td>\n",
              "      <td>0.201588</td>\n",
              "      <td>0.106937</td>\n",
              "      <td>0.141830</td>\n",
              "      <td>0.006389</td>\n",
              "      <td>0.139853</td>\n",
              "      <td>0.134230</td>\n",
              "      <td>0.169769</td>\n",
              "      <td>0.194325</td>\n",
              "      <td>0.097507</td>\n",
              "      <td>0.186238</td>\n",
              "      <td>0.086177</td>\n",
              "      <td>0.053818</td>\n",
              "      <td>0.054051</td>\n",
              "      <td>0.024092</td>\n",
              "      <td>0.061993</td>\n",
              "      <td>0.053311</td>\n",
              "      <td>-0.018425</td>\n",
              "      <td>0.052035</td>\n",
              "      <td>0.042480</td>\n",
              "      <td>0.014867</td>\n",
              "      <td>0.060715</td>\n",
              "      <td>0.009029</td>\n",
              "      <td>0.052637</td>\n",
              "      <td>0.054137</td>\n",
              "      <td>0.056300</td>\n",
              "      <td>0.058850</td>\n",
              "      <td>0.065627</td>\n",
              "      <td>-0.004650</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000044</td>\n",
              "      <td>0.021033</td>\n",
              "      <td>0.030255</td>\n",
              "      <td>0.015868</td>\n",
              "      <td>0.017417</td>\n",
              "      <td>-0.029861</td>\n",
              "      <td>-0.012587</td>\n",
              "      <td>0.002225</td>\n",
              "      <td>0.000322</td>\n",
              "      <td>0.025362</td>\n",
              "      <td>0.141102</td>\n",
              "      <td>-0.068884</td>\n",
              "      <td>0.107938</td>\n",
              "      <td>0.171319</td>\n",
              "      <td>0.084330</td>\n",
              "      <td>0.148525</td>\n",
              "      <td>0.149972</td>\n",
              "      <td>0.174854</td>\n",
              "      <td>-0.045919</td>\n",
              "      <td>0.098938</td>\n",
              "      <td>-0.098298</td>\n",
              "      <td>0.007763</td>\n",
              "      <td>0.120166</td>\n",
              "      <td>0.120349</td>\n",
              "      <td>0.069404</td>\n",
              "      <td>0.030926</td>\n",
              "      <td>0.036189</td>\n",
              "      <td>-0.055985</td>\n",
              "      <td>-0.019572</td>\n",
              "      <td>-0.090153</td>\n",
              "      <td>-0.117850</td>\n",
              "      <td>-0.066153</td>\n",
              "      <td>-0.132047</td>\n",
              "      <td>0.187572</td>\n",
              "      <td>-0.044129</td>\n",
              "      <td>0.024363</td>\n",
              "      <td>0.212267</td>\n",
              "      <td>0.272126</td>\n",
              "      <td>0.271971</td>\n",
              "      <td>0.212376</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.total_hospital_beds</th>\n",
              "      <td>0.211892</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.602761</td>\n",
              "      <td>0.471926</td>\n",
              "      <td>0.677023</td>\n",
              "      <td>0.875744</td>\n",
              "      <td>0.974264</td>\n",
              "      <td>0.917565</td>\n",
              "      <td>0.115844</td>\n",
              "      <td>0.964642</td>\n",
              "      <td>0.923179</td>\n",
              "      <td>0.661903</td>\n",
              "      <td>0.940317</td>\n",
              "      <td>0.371784</td>\n",
              "      <td>0.641703</td>\n",
              "      <td>0.175615</td>\n",
              "      <td>0.655934</td>\n",
              "      <td>0.877529</td>\n",
              "      <td>0.860722</td>\n",
              "      <td>0.820230</td>\n",
              "      <td>0.474525</td>\n",
              "      <td>0.948594</td>\n",
              "      <td>0.037917</td>\n",
              "      <td>0.099596</td>\n",
              "      <td>0.098752</td>\n",
              "      <td>0.095071</td>\n",
              "      <td>0.113863</td>\n",
              "      <td>0.098528</td>\n",
              "      <td>0.097803</td>\n",
              "      <td>0.086319</td>\n",
              "      <td>0.097198</td>\n",
              "      <td>0.076125</td>\n",
              "      <td>0.099481</td>\n",
              "      <td>0.018042</td>\n",
              "      <td>0.087745</td>\n",
              "      <td>0.093192</td>\n",
              "      <td>0.108593</td>\n",
              "      <td>0.098776</td>\n",
              "      <td>0.101506</td>\n",
              "      <td>0.160770</td>\n",
              "      <td>...</td>\n",
              "      <td>0.010083</td>\n",
              "      <td>-0.019891</td>\n",
              "      <td>0.028111</td>\n",
              "      <td>-0.008095</td>\n",
              "      <td>0.069742</td>\n",
              "      <td>-0.035155</td>\n",
              "      <td>-0.007450</td>\n",
              "      <td>0.002937</td>\n",
              "      <td>-0.011658</td>\n",
              "      <td>0.019074</td>\n",
              "      <td>0.106880</td>\n",
              "      <td>-0.051967</td>\n",
              "      <td>0.080914</td>\n",
              "      <td>0.136308</td>\n",
              "      <td>0.034100</td>\n",
              "      <td>0.116134</td>\n",
              "      <td>0.116233</td>\n",
              "      <td>0.141715</td>\n",
              "      <td>-0.054690</td>\n",
              "      <td>0.069515</td>\n",
              "      <td>-0.068943</td>\n",
              "      <td>-0.013336</td>\n",
              "      <td>0.089983</td>\n",
              "      <td>0.092549</td>\n",
              "      <td>0.059573</td>\n",
              "      <td>0.373951</td>\n",
              "      <td>0.032516</td>\n",
              "      <td>-0.015438</td>\n",
              "      <td>-0.018730</td>\n",
              "      <td>-0.437065</td>\n",
              "      <td>-0.309811</td>\n",
              "      <td>-0.416402</td>\n",
              "      <td>-0.153334</td>\n",
              "      <td>0.245964</td>\n",
              "      <td>0.037551</td>\n",
              "      <td>-0.308656</td>\n",
              "      <td>0.217231</td>\n",
              "      <td>0.179270</td>\n",
              "      <td>0.179013</td>\n",
              "      <td>0.217292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.acute_long_term_care_beds</th>\n",
              "      <td>0.092799</td>\n",
              "      <td>0.602761</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.272630</td>\n",
              "      <td>0.361489</td>\n",
              "      <td>0.528757</td>\n",
              "      <td>0.615385</td>\n",
              "      <td>0.603491</td>\n",
              "      <td>0.054686</td>\n",
              "      <td>0.647469</td>\n",
              "      <td>0.617204</td>\n",
              "      <td>0.505410</td>\n",
              "      <td>0.628324</td>\n",
              "      <td>0.211673</td>\n",
              "      <td>0.411570</td>\n",
              "      <td>0.103237</td>\n",
              "      <td>0.408381</td>\n",
              "      <td>0.592411</td>\n",
              "      <td>0.616587</td>\n",
              "      <td>0.528974</td>\n",
              "      <td>0.166911</td>\n",
              "      <td>0.631892</td>\n",
              "      <td>0.047124</td>\n",
              "      <td>0.108805</td>\n",
              "      <td>0.108532</td>\n",
              "      <td>0.125646</td>\n",
              "      <td>0.110266</td>\n",
              "      <td>0.107111</td>\n",
              "      <td>0.051667</td>\n",
              "      <td>0.091611</td>\n",
              "      <td>0.080211</td>\n",
              "      <td>0.114745</td>\n",
              "      <td>0.099261</td>\n",
              "      <td>0.028745</td>\n",
              "      <td>0.096977</td>\n",
              "      <td>0.096932</td>\n",
              "      <td>0.108342</td>\n",
              "      <td>0.105844</td>\n",
              "      <td>0.105819</td>\n",
              "      <td>0.089472</td>\n",
              "      <td>...</td>\n",
              "      <td>0.037252</td>\n",
              "      <td>-0.005444</td>\n",
              "      <td>0.001131</td>\n",
              "      <td>-0.000862</td>\n",
              "      <td>0.015204</td>\n",
              "      <td>-0.020176</td>\n",
              "      <td>-0.004496</td>\n",
              "      <td>-0.005508</td>\n",
              "      <td>-0.009551</td>\n",
              "      <td>0.050091</td>\n",
              "      <td>0.065285</td>\n",
              "      <td>-0.029797</td>\n",
              "      <td>0.055083</td>\n",
              "      <td>0.083524</td>\n",
              "      <td>0.026198</td>\n",
              "      <td>0.069781</td>\n",
              "      <td>0.070098</td>\n",
              "      <td>0.081631</td>\n",
              "      <td>-0.023197</td>\n",
              "      <td>0.042206</td>\n",
              "      <td>-0.041941</td>\n",
              "      <td>0.012551</td>\n",
              "      <td>0.054452</td>\n",
              "      <td>0.056889</td>\n",
              "      <td>0.033180</td>\n",
              "      <td>0.205375</td>\n",
              "      <td>0.013798</td>\n",
              "      <td>-0.034337</td>\n",
              "      <td>0.009323</td>\n",
              "      <td>-0.244005</td>\n",
              "      <td>-0.174545</td>\n",
              "      <td>-0.229634</td>\n",
              "      <td>-0.093864</td>\n",
              "      <td>0.150235</td>\n",
              "      <td>0.028619</td>\n",
              "      <td>-0.165602</td>\n",
              "      <td>0.130878</td>\n",
              "      <td>0.104477</td>\n",
              "      <td>0.104328</td>\n",
              "      <td>0.130912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.alcohol_drug_abuse_dependency_inpatient_care_beds</th>\n",
              "      <td>0.118284</td>\n",
              "      <td>0.471926</td>\n",
              "      <td>0.272630</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.321795</td>\n",
              "      <td>0.430273</td>\n",
              "      <td>0.464936</td>\n",
              "      <td>0.418470</td>\n",
              "      <td>0.019516</td>\n",
              "      <td>0.432890</td>\n",
              "      <td>0.381771</td>\n",
              "      <td>0.310907</td>\n",
              "      <td>0.415904</td>\n",
              "      <td>0.284187</td>\n",
              "      <td>0.303182</td>\n",
              "      <td>0.078488</td>\n",
              "      <td>0.264215</td>\n",
              "      <td>0.400599</td>\n",
              "      <td>0.386856</td>\n",
              "      <td>0.429437</td>\n",
              "      <td>0.348111</td>\n",
              "      <td>0.423760</td>\n",
              "      <td>0.012093</td>\n",
              "      <td>0.025360</td>\n",
              "      <td>0.024930</td>\n",
              "      <td>0.024844</td>\n",
              "      <td>0.034505</td>\n",
              "      <td>0.024774</td>\n",
              "      <td>0.042056</td>\n",
              "      <td>0.019412</td>\n",
              "      <td>0.031285</td>\n",
              "      <td>0.022428</td>\n",
              "      <td>0.023567</td>\n",
              "      <td>-0.006283</td>\n",
              "      <td>0.019842</td>\n",
              "      <td>0.023184</td>\n",
              "      <td>0.028574</td>\n",
              "      <td>0.025730</td>\n",
              "      <td>0.024863</td>\n",
              "      <td>0.069520</td>\n",
              "      <td>...</td>\n",
              "      <td>0.011472</td>\n",
              "      <td>-0.016656</td>\n",
              "      <td>0.011398</td>\n",
              "      <td>-0.003139</td>\n",
              "      <td>0.049071</td>\n",
              "      <td>-0.017305</td>\n",
              "      <td>-0.005242</td>\n",
              "      <td>-0.006421</td>\n",
              "      <td>-0.011135</td>\n",
              "      <td>0.026438</td>\n",
              "      <td>0.075987</td>\n",
              "      <td>-0.034738</td>\n",
              "      <td>0.062367</td>\n",
              "      <td>0.091860</td>\n",
              "      <td>0.037119</td>\n",
              "      <td>0.082701</td>\n",
              "      <td>0.082652</td>\n",
              "      <td>0.094832</td>\n",
              "      <td>-0.035771</td>\n",
              "      <td>0.049198</td>\n",
              "      <td>-0.048829</td>\n",
              "      <td>0.003317</td>\n",
              "      <td>0.061591</td>\n",
              "      <td>0.062465</td>\n",
              "      <td>0.034845</td>\n",
              "      <td>0.128713</td>\n",
              "      <td>0.030628</td>\n",
              "      <td>-0.017470</td>\n",
              "      <td>-0.000031</td>\n",
              "      <td>-0.143168</td>\n",
              "      <td>-0.101475</td>\n",
              "      <td>-0.127927</td>\n",
              "      <td>-0.080973</td>\n",
              "      <td>0.083952</td>\n",
              "      <td>-0.003286</td>\n",
              "      <td>-0.084545</td>\n",
              "      <td>0.122593</td>\n",
              "      <td>0.073816</td>\n",
              "      <td>0.073704</td>\n",
              "      <td>0.122607</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.covid19_aha.hospital_beds.burn_care_beds</th>\n",
              "      <td>0.110501</td>\n",
              "      <td>0.677023</td>\n",
              "      <td>0.361489</td>\n",
              "      <td>0.321795</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.670632</td>\n",
              "      <td>0.661263</td>\n",
              "      <td>0.683314</td>\n",
              "      <td>0.052016</td>\n",
              "      <td>0.650530</td>\n",
              "      <td>0.667429</td>\n",
              "      <td>0.443088</td>\n",
              "      <td>0.615725</td>\n",
              "      <td>0.227673</td>\n",
              "      <td>0.503821</td>\n",
              "      <td>0.199585</td>\n",
              "      <td>0.458694</td>\n",
              "      <td>0.692182</td>\n",
              "      <td>0.575876</td>\n",
              "      <td>0.530607</td>\n",
              "      <td>0.264445</td>\n",
              "      <td>0.685883</td>\n",
              "      <td>0.014164</td>\n",
              "      <td>0.077820</td>\n",
              "      <td>0.077316</td>\n",
              "      <td>0.084990</td>\n",
              "      <td>0.097864</td>\n",
              "      <td>0.076752</td>\n",
              "      <td>0.077026</td>\n",
              "      <td>0.069537</td>\n",
              "      <td>0.081617</td>\n",
              "      <td>0.074161</td>\n",
              "      <td>0.074145</td>\n",
              "      <td>0.017533</td>\n",
              "      <td>0.071208</td>\n",
              "      <td>0.072949</td>\n",
              "      <td>0.087411</td>\n",
              "      <td>0.074153</td>\n",
              "      <td>0.071993</td>\n",
              "      <td>0.104920</td>\n",
              "      <td>...</td>\n",
              "      <td>0.001107</td>\n",
              "      <td>-0.017909</td>\n",
              "      <td>0.025237</td>\n",
              "      <td>0.035312</td>\n",
              "      <td>0.017509</td>\n",
              "      <td>-0.020889</td>\n",
              "      <td>-0.004659</td>\n",
              "      <td>-0.005707</td>\n",
              "      <td>-0.009895</td>\n",
              "      <td>0.007221</td>\n",
              "      <td>0.066790</td>\n",
              "      <td>-0.030873</td>\n",
              "      <td>0.056180</td>\n",
              "      <td>0.080178</td>\n",
              "      <td>0.010594</td>\n",
              "      <td>0.072400</td>\n",
              "      <td>0.072051</td>\n",
              "      <td>0.084496</td>\n",
              "      <td>-0.037464</td>\n",
              "      <td>0.043727</td>\n",
              "      <td>-0.043496</td>\n",
              "      <td>-0.018026</td>\n",
              "      <td>0.053431</td>\n",
              "      <td>0.052552</td>\n",
              "      <td>0.029421</td>\n",
              "      <td>0.217620</td>\n",
              "      <td>0.014942</td>\n",
              "      <td>0.000750</td>\n",
              "      <td>-0.017342</td>\n",
              "      <td>-0.233897</td>\n",
              "      <td>-0.135488</td>\n",
              "      <td>-0.219121</td>\n",
              "      <td>-0.054879</td>\n",
              "      <td>0.125348</td>\n",
              "      <td>0.017477</td>\n",
              "      <td>-0.152015</td>\n",
              "      <td>0.105929</td>\n",
              "      <td>0.099110</td>\n",
              "      <td>0.098992</td>\n",
              "      <td>0.105957</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",
              "      <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",
              "      <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",
              "      <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>bigquery-public-data.new_york_trees.tree_census_2015.boro_ct</th>\n",
              "      <td>0.024363</td>\n",
              "      <td>-0.308656</td>\n",
              "      <td>-0.165602</td>\n",
              "      <td>-0.084545</td>\n",
              "      <td>-0.152015</td>\n",
              "      <td>-0.278127</td>\n",
              "      <td>-0.297251</td>\n",
              "      <td>-0.287966</td>\n",
              "      <td>-0.010999</td>\n",
              "      <td>-0.279259</td>\n",
              "      <td>-0.270469</td>\n",
              "      <td>-0.157898</td>\n",
              "      <td>-0.263352</td>\n",
              "      <td>-0.152124</td>\n",
              "      <td>-0.216074</td>\n",
              "      <td>0.004235</td>\n",
              "      <td>-0.354030</td>\n",
              "      <td>-0.254849</td>\n",
              "      <td>-0.245601</td>\n",
              "      <td>-0.202789</td>\n",
              "      <td>-0.225443</td>\n",
              "      <td>-0.326207</td>\n",
              "      <td>0.055342</td>\n",
              "      <td>0.082974</td>\n",
              "      <td>0.083588</td>\n",
              "      <td>0.065082</td>\n",
              "      <td>0.088998</td>\n",
              "      <td>0.082161</td>\n",
              "      <td>-0.052575</td>\n",
              "      <td>0.082997</td>\n",
              "      <td>0.062653</td>\n",
              "      <td>0.058302</td>\n",
              "      <td>0.083790</td>\n",
              "      <td>0.044390</td>\n",
              "      <td>0.085700</td>\n",
              "      <td>0.088324</td>\n",
              "      <td>0.075613</td>\n",
              "      <td>0.084561</td>\n",
              "      <td>0.084817</td>\n",
              "      <td>-0.041122</td>\n",
              "      <td>...</td>\n",
              "      <td>0.123515</td>\n",
              "      <td>0.081482</td>\n",
              "      <td>-0.049996</td>\n",
              "      <td>-0.027837</td>\n",
              "      <td>-0.015884</td>\n",
              "      <td>0.021753</td>\n",
              "      <td>-0.055954</td>\n",
              "      <td>-0.009907</td>\n",
              "      <td>-0.037389</td>\n",
              "      <td>-0.016241</td>\n",
              "      <td>0.731027</td>\n",
              "      <td>0.815897</td>\n",
              "      <td>0.545437</td>\n",
              "      <td>-0.271706</td>\n",
              "      <td>-0.300624</td>\n",
              "      <td>0.046470</td>\n",
              "      <td>0.001523</td>\n",
              "      <td>-0.271507</td>\n",
              "      <td>0.773493</td>\n",
              "      <td>0.026399</td>\n",
              "      <td>-0.038632</td>\n",
              "      <td>0.188457</td>\n",
              "      <td>0.600056</td>\n",
              "      <td>0.609291</td>\n",
              "      <td>0.227054</td>\n",
              "      <td>0.348391</td>\n",
              "      <td>0.214570</td>\n",
              "      <td>0.092759</td>\n",
              "      <td>0.017404</td>\n",
              "      <td>0.315133</td>\n",
              "      <td>0.999153</td>\n",
              "      <td>0.999245</td>\n",
              "      <td>0.690447</td>\n",
              "      <td>-0.539010</td>\n",
              "      <td>-0.590300</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.635516</td>\n",
              "      <td>-0.200235</td>\n",
              "      <td>-0.200356</td>\n",
              "      <td>-0.635068</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.latitude</th>\n",
              "      <td>0.212267</td>\n",
              "      <td>0.217231</td>\n",
              "      <td>0.130878</td>\n",
              "      <td>0.122593</td>\n",
              "      <td>0.105929</td>\n",
              "      <td>0.191962</td>\n",
              "      <td>0.232977</td>\n",
              "      <td>0.191352</td>\n",
              "      <td>0.064995</td>\n",
              "      <td>0.219737</td>\n",
              "      <td>0.171142</td>\n",
              "      <td>0.123705</td>\n",
              "      <td>0.221708</td>\n",
              "      <td>0.098602</td>\n",
              "      <td>0.148096</td>\n",
              "      <td>0.033139</td>\n",
              "      <td>0.196327</td>\n",
              "      <td>0.142658</td>\n",
              "      <td>0.185704</td>\n",
              "      <td>0.179605</td>\n",
              "      <td>0.171030</td>\n",
              "      <td>0.228515</td>\n",
              "      <td>0.119860</td>\n",
              "      <td>-0.092975</td>\n",
              "      <td>-0.092520</td>\n",
              "      <td>-0.089353</td>\n",
              "      <td>-0.064546</td>\n",
              "      <td>-0.093932</td>\n",
              "      <td>-0.140178</td>\n",
              "      <td>-0.078651</td>\n",
              "      <td>-0.071591</td>\n",
              "      <td>-0.091504</td>\n",
              "      <td>-0.085911</td>\n",
              "      <td>-0.088680</td>\n",
              "      <td>-0.094991</td>\n",
              "      <td>-0.088373</td>\n",
              "      <td>-0.082228</td>\n",
              "      <td>-0.089364</td>\n",
              "      <td>-0.074030</td>\n",
              "      <td>-0.105984</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.045979</td>\n",
              "      <td>-0.027582</td>\n",
              "      <td>0.012617</td>\n",
              "      <td>0.011654</td>\n",
              "      <td>0.027845</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>0.038400</td>\n",
              "      <td>-0.004833</td>\n",
              "      <td>0.016934</td>\n",
              "      <td>0.003196</td>\n",
              "      <td>-0.380161</td>\n",
              "      <td>-0.585397</td>\n",
              "      <td>-0.594936</td>\n",
              "      <td>0.220571</td>\n",
              "      <td>0.251271</td>\n",
              "      <td>0.215448</td>\n",
              "      <td>0.307946</td>\n",
              "      <td>0.628806</td>\n",
              "      <td>-0.517675</td>\n",
              "      <td>0.158160</td>\n",
              "      <td>-0.138863</td>\n",
              "      <td>-0.020266</td>\n",
              "      <td>-0.331884</td>\n",
              "      <td>-0.337821</td>\n",
              "      <td>-0.141376</td>\n",
              "      <td>0.140602</td>\n",
              "      <td>-0.103129</td>\n",
              "      <td>-0.033406</td>\n",
              "      <td>-0.002973</td>\n",
              "      <td>-0.101480</td>\n",
              "      <td>-0.644775</td>\n",
              "      <td>-0.641788</td>\n",
              "      <td>-0.885940</td>\n",
              "      <td>0.235369</td>\n",
              "      <td>0.290130</td>\n",
              "      <td>-0.635516</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.585874</td>\n",
              "      <td>0.585412</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.longitude</th>\n",
              "      <td>0.272126</td>\n",
              "      <td>0.179270</td>\n",
              "      <td>0.104477</td>\n",
              "      <td>0.073816</td>\n",
              "      <td>0.099110</td>\n",
              "      <td>0.161332</td>\n",
              "      <td>0.187824</td>\n",
              "      <td>0.149972</td>\n",
              "      <td>0.046184</td>\n",
              "      <td>0.183819</td>\n",
              "      <td>0.136306</td>\n",
              "      <td>0.131662</td>\n",
              "      <td>0.193219</td>\n",
              "      <td>0.071825</td>\n",
              "      <td>0.118033</td>\n",
              "      <td>0.053649</td>\n",
              "      <td>0.117181</td>\n",
              "      <td>0.114138</td>\n",
              "      <td>0.156990</td>\n",
              "      <td>0.159996</td>\n",
              "      <td>0.100844</td>\n",
              "      <td>0.185315</td>\n",
              "      <td>0.223014</td>\n",
              "      <td>0.226214</td>\n",
              "      <td>0.226899</td>\n",
              "      <td>0.163734</td>\n",
              "      <td>0.251584</td>\n",
              "      <td>0.225596</td>\n",
              "      <td>0.019931</td>\n",
              "      <td>0.220202</td>\n",
              "      <td>0.224564</td>\n",
              "      <td>0.132221</td>\n",
              "      <td>0.236197</td>\n",
              "      <td>0.101467</td>\n",
              "      <td>0.226848</td>\n",
              "      <td>0.233478</td>\n",
              "      <td>0.227121</td>\n",
              "      <td>0.228637</td>\n",
              "      <td>0.234932</td>\n",
              "      <td>0.019445</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.058481</td>\n",
              "      <td>-0.042011</td>\n",
              "      <td>0.006342</td>\n",
              "      <td>-0.025012</td>\n",
              "      <td>0.027029</td>\n",
              "      <td>0.010280</td>\n",
              "      <td>-0.005590</td>\n",
              "      <td>-0.003488</td>\n",
              "      <td>-0.011206</td>\n",
              "      <td>0.033887</td>\n",
              "      <td>-0.137044</td>\n",
              "      <td>-0.228242</td>\n",
              "      <td>-0.481566</td>\n",
              "      <td>-0.368780</td>\n",
              "      <td>-0.298571</td>\n",
              "      <td>0.600341</td>\n",
              "      <td>0.222364</td>\n",
              "      <td>0.441648</td>\n",
              "      <td>-0.259102</td>\n",
              "      <td>0.063920</td>\n",
              "      <td>-0.044089</td>\n",
              "      <td>0.176076</td>\n",
              "      <td>-0.115548</td>\n",
              "      <td>-0.129334</td>\n",
              "      <td>0.119291</td>\n",
              "      <td>-0.021412</td>\n",
              "      <td>0.223189</td>\n",
              "      <td>0.103346</td>\n",
              "      <td>0.042044</td>\n",
              "      <td>0.490261</td>\n",
              "      <td>-0.202291</td>\n",
              "      <td>-0.221384</td>\n",
              "      <td>-0.562161</td>\n",
              "      <td>-0.469124</td>\n",
              "      <td>-0.418245</td>\n",
              "      <td>-0.200235</td>\n",
              "      <td>0.585874</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999999</td>\n",
              "      <td>0.586305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.x_sp</th>\n",
              "      <td>0.271971</td>\n",
              "      <td>0.179013</td>\n",
              "      <td>0.104328</td>\n",
              "      <td>0.073704</td>\n",
              "      <td>0.098992</td>\n",
              "      <td>0.161106</td>\n",
              "      <td>0.187563</td>\n",
              "      <td>0.149747</td>\n",
              "      <td>0.046141</td>\n",
              "      <td>0.183571</td>\n",
              "      <td>0.136093</td>\n",
              "      <td>0.131525</td>\n",
              "      <td>0.192973</td>\n",
              "      <td>0.071708</td>\n",
              "      <td>0.117861</td>\n",
              "      <td>0.053633</td>\n",
              "      <td>0.116930</td>\n",
              "      <td>0.113961</td>\n",
              "      <td>0.156773</td>\n",
              "      <td>0.159805</td>\n",
              "      <td>0.100669</td>\n",
              "      <td>0.185048</td>\n",
              "      <td>0.222963</td>\n",
              "      <td>0.226320</td>\n",
              "      <td>0.227004</td>\n",
              "      <td>0.163835</td>\n",
              "      <td>0.251668</td>\n",
              "      <td>0.225702</td>\n",
              "      <td>0.020074</td>\n",
              "      <td>0.220296</td>\n",
              "      <td>0.224652</td>\n",
              "      <td>0.132316</td>\n",
              "      <td>0.236297</td>\n",
              "      <td>0.101565</td>\n",
              "      <td>0.226956</td>\n",
              "      <td>0.233581</td>\n",
              "      <td>0.227217</td>\n",
              "      <td>0.228739</td>\n",
              "      <td>0.235021</td>\n",
              "      <td>0.019553</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.058567</td>\n",
              "      <td>-0.042060</td>\n",
              "      <td>0.006380</td>\n",
              "      <td>-0.024997</td>\n",
              "      <td>0.027024</td>\n",
              "      <td>0.010338</td>\n",
              "      <td>-0.005603</td>\n",
              "      <td>-0.003467</td>\n",
              "      <td>-0.011216</td>\n",
              "      <td>0.033916</td>\n",
              "      <td>-0.137179</td>\n",
              "      <td>-0.228239</td>\n",
              "      <td>-0.481407</td>\n",
              "      <td>-0.369220</td>\n",
              "      <td>-0.298977</td>\n",
              "      <td>0.600508</td>\n",
              "      <td>0.222099</td>\n",
              "      <td>0.441188</td>\n",
              "      <td>-0.259186</td>\n",
              "      <td>0.063738</td>\n",
              "      <td>-0.043914</td>\n",
              "      <td>0.176045</td>\n",
              "      <td>-0.115616</td>\n",
              "      <td>-0.129415</td>\n",
              "      <td>0.119286</td>\n",
              "      <td>-0.022221</td>\n",
              "      <td>0.223256</td>\n",
              "      <td>0.103358</td>\n",
              "      <td>0.042055</td>\n",
              "      <td>0.490591</td>\n",
              "      <td>-0.202402</td>\n",
              "      <td>-0.221503</td>\n",
              "      <td>-0.561846</td>\n",
              "      <td>-0.469469</td>\n",
              "      <td>-0.418604</td>\n",
              "      <td>-0.200356</td>\n",
              "      <td>0.585412</td>\n",
              "      <td>0.999999</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.585843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bigquery-public-data.new_york_trees.tree_census_2015.y_sp</th>\n",
              "      <td>0.212376</td>\n",
              "      <td>0.217292</td>\n",
              "      <td>0.130912</td>\n",
              "      <td>0.122607</td>\n",
              "      <td>0.105957</td>\n",
              "      <td>0.192016</td>\n",
              "      <td>0.233037</td>\n",
              "      <td>0.191398</td>\n",
              "      <td>0.065008</td>\n",
              "      <td>0.219797</td>\n",
              "      <td>0.171186</td>\n",
              "      <td>0.123751</td>\n",
              "      <td>0.221773</td>\n",
              "      <td>0.098620</td>\n",
              "      <td>0.148130</td>\n",
              "      <td>0.033158</td>\n",
              "      <td>0.196359</td>\n",
              "      <td>0.142690</td>\n",
              "      <td>0.185757</td>\n",
              "      <td>0.179656</td>\n",
              "      <td>0.171050</td>\n",
              "      <td>0.228574</td>\n",
              "      <td>0.119951</td>\n",
              "      <td>-0.092853</td>\n",
              "      <td>-0.092397</td>\n",
              "      <td>-0.089265</td>\n",
              "      <td>-0.064409</td>\n",
              "      <td>-0.093810</td>\n",
              "      <td>-0.140175</td>\n",
              "      <td>-0.078532</td>\n",
              "      <td>-0.071473</td>\n",
              "      <td>-0.091431</td>\n",
              "      <td>-0.085784</td>\n",
              "      <td>-0.088624</td>\n",
              "      <td>-0.094867</td>\n",
              "      <td>-0.088246</td>\n",
              "      <td>-0.082107</td>\n",
              "      <td>-0.089240</td>\n",
              "      <td>-0.073903</td>\n",
              "      <td>-0.105980</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.045899</td>\n",
              "      <td>-0.027524</td>\n",
              "      <td>0.012584</td>\n",
              "      <td>0.011620</td>\n",
              "      <td>0.027840</td>\n",
              "      <td>-0.026918</td>\n",
              "      <td>0.038379</td>\n",
              "      <td>-0.004847</td>\n",
              "      <td>0.016919</td>\n",
              "      <td>0.003198</td>\n",
              "      <td>-0.379752</td>\n",
              "      <td>-0.585049</td>\n",
              "      <td>-0.594980</td>\n",
              "      <td>0.220338</td>\n",
              "      <td>0.251052</td>\n",
              "      <td>0.215732</td>\n",
              "      <td>0.308188</td>\n",
              "      <td>0.629068</td>\n",
              "      <td>-0.517324</td>\n",
              "      <td>0.158288</td>\n",
              "      <td>-0.138985</td>\n",
              "      <td>-0.020003</td>\n",
              "      <td>-0.331563</td>\n",
              "      <td>-0.337497</td>\n",
              "      <td>-0.141172</td>\n",
              "      <td>0.140955</td>\n",
              "      <td>-0.102902</td>\n",
              "      <td>-0.033333</td>\n",
              "      <td>-0.002946</td>\n",
              "      <td>-0.101251</td>\n",
              "      <td>-0.644328</td>\n",
              "      <td>-0.641353</td>\n",
              "      <td>-0.886004</td>\n",
              "      <td>0.234941</td>\n",
              "      <td>0.289698</td>\n",
              "      <td>-0.635068</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.586305</td>\n",
              "      <td>0.585843</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8574 rows × 8574 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    bigquery-public-data.covid19_aha.hospital_beds.cbsa_code  ...  bigquery-public-data.new_york_trees.tree_census_2015.y_sp\n",
              "bigquery-public-data.covid19_aha.hospital_beds....                                           1.000000         ...                                           0.212376        \n",
              "bigquery-public-data.covid19_aha.hospital_beds....                                           0.211892         ...                                           0.217292        \n",
              "bigquery-public-data.covid19_aha.hospital_beds....                                           0.092799         ...                                           0.130912        \n",
              "bigquery-public-data.covid19_aha.hospital_beds....                                           0.118284         ...                                           0.122607        \n",
              "bigquery-public-data.covid19_aha.hospital_beds....                                           0.110501         ...                                           0.105957        \n",
              "...                                                                                               ...         ...                                                ...        \n",
              "bigquery-public-data.new_york_trees.tree_census...                                           0.024363         ...                                          -0.635068        \n",
              "bigquery-public-data.new_york_trees.tree_census...                                           0.212267         ...                                           1.000000        \n",
              "bigquery-public-data.new_york_trees.tree_census...                                           0.272126         ...                                           0.586305        \n",
              "bigquery-public-data.new_york_trees.tree_census...                                           0.271971         ...                                           0.585843        \n",
              "bigquery-public-data.new_york_trees.tree_census...                                           0.212376         ...                                           1.000000        \n",
              "\n",
              "[8574 rows x 8574 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "euUtGQww1rnI"
      },
      "source": [
        "### Query correlation between two columns"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C36gUjpT1Mdy",
        "outputId": "a783e1f1-32c8-4dfa-b730-e21f57bf4022"
      },
      "source": [
        "import scripts.Index as index\r\n",
        "\r\n",
        "print(index.get_correlation('bigquery-public-data.covid19_aha.hospital_beds.county_fips_code', 'bigquery-public-data.covid19_aha.hospital_beds.county_name'))\r\n",
        "print(index.get_correlation('bigquery-public-data.covid19_aha.hospital_beds.cbsa_code', 'bigquery-public-data.covid19_aha.hospital_beds.total_hospital_beds'))"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.0\n",
            "0.21189153808476402\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mx1cZC0Q2lmy"
      },
      "source": [
        "### Top-k correlated columns"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sd06MvSY2qFN",
        "outputId": "b9b1d226-e9df-4de4-81e2-0d69b81e7362"
      },
      "source": [
        "import scripts.Index as index\r\n",
        "\r\n",
        "print(index.get_top_k('bigquery-public-data.covid19_aha.hospital_beds.county_fips_code'))\r\n",
        "print(index.get_top_k('bigquery-public-data.covid19_aha.hospital_beds.cbsa_code'))"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['bigquery-public-data.covid19_aha.hospital_beds.county_fips_code'\n",
            " 'bigquery-public-data.covid19_aha.staffing.county_fips_code'\n",
            " 'bigquery-public-data.covid19_google_mobility.mobility_report.census_fips_code'\n",
            " 'bigquery-public-data.covid19_google_mobility_eu.mobility_report.census_fips_code'\n",
            " 'bigquery-public-data.covid19_public_forecasts.county_14d.county_fips_code'\n",
            " 'bigquery-public-data.covid19_public_forecasts.county_28d.county_fips_code'\n",
            " 'bigquery-public-data.covid19_public_forecasts.county_28d_historical.county_fips_code'\n",
            " 'bigquery-public-data.covid19_public_forecasts.county_28d_historical_.county_fips_code'\n",
            " 'bigquery-public-data.covid19_public_forecasts_asia_ne1.county_14d.county_fips_code'\n",
            " 'bigquery-public-data.covid19_public_forecasts_asia_ne1.county_28d.county_fips_code']\n",
            "['bigquery-public-data.covid19_aha.hospital_beds.cbsa_code'\n",
            " 'bigquery-public-data.covid19_nyt.excess_deaths.week'\n",
            " 'bigquery-public-data.covid19_italy.data_by_region.region_code'\n",
            " 'bigquery-public-data.covid19_italy_eu.data_by_region.region_code'\n",
            " 'bigquery-public-data.covid19_italy_eu.data_by_province.longitude'\n",
            " 'bigquery-public-data.covid19_weathersource_com.county_day_forecast.min_humidity_relative_2m_pct'\n",
            " 'bigquery-public-data.covid19_italy.data_by_province.longitude'\n",
            " 'bigquery-public-data.new_york_trees.tree_census_1995.cb_new'\n",
            " 'bigquery-public-data.new_york_trees.tree_census_1995.recordid'\n",
            " 'bigquery-public-data.new_york_trees.tree_census_1995.cb_original']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DH7vyWIP27Wq"
      },
      "source": [
        "### Top similar columns with correlation greater than the threshold"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E-dz299n3L5V",
        "outputId": "b86ba01c-4233-48f5-c30a-abf1c2bc7944"
      },
      "source": [
        "import scripts.Index as index\r\n",
        "\r\n",
        "print(index.get_greater_than_threshold('bigquery-public-data.covid19_aha.hospital_beds.county_fips_code', threshold=0.9))\r\n",
        "print(index.get_greater_than_threshold('bigquery-public-data.covid19_aha.hospital_beds.cbsa_code', threshold=0.9))"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['bigquery-public-data.covid19_aha.hospital_beds.county_fips_code', 'bigquery-public-data.covid19_aha.staffing.county_fips_code']\n",
            "['bigquery-public-data.covid19_aha.hospital_beds.cbsa_code']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7uViI_8K_dNZ"
      },
      "source": [
        "### Plot correlation values "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "V4wfjwZn_mJX",
        "outputId": "94036e90-a439-493c-bdd1-40f97ab6b716"
      },
      "source": [
        "import scripts.GraphicalViews as graphicalViews\r\n",
        "\r\n",
        "# graphicalViews.plot('jaccard', jaccard, corr_th=0.9)\r\n",
        "\r\n",
        "# graphicalViews.plot('pearson', pearson, corr_th=0.9)\r\n"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-17-62b7b03133fd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# graphicalViews.plot('jaccard', jaccard, corr_th=0.9)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mgraphicalViews\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'pearson'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpearson\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcorr_th\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.9\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/content/gdrive/MyDrive/Data/Jupyter/scripts/GraphicalViews.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(plot_name, corr_2d, corr_th)\u001b[0m\n\u001b[1;32m     71\u001b[0m     \u001b[0mcbar\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolorbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'% .2f'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     72\u001b[0m     \u001b[0;31m# plt.show()\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msavefig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf'{os.environ[\"WORKING_DIRECTORY\"]}/results/{plot_name}.png'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     74\u001b[0m     \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     75\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36msavefig\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    721\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0msavefig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    722\u001b[0m     \u001b[0mfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgcf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 723\u001b[0;31m     \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msavefig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    724\u001b[0m     \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw_idle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m   \u001b[0;31m# need this if 'transparent=True' to reset colors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    725\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/figure.py\u001b[0m in \u001b[0;36msavefig\u001b[0;34m(self, fname, transparent, **kwargs)\u001b[0m\n\u001b[1;32m   2201\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_visible\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframeon\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2202\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2203\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2204\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2205\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mframeon\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36mprint_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, **kwargs)\u001b[0m\n\u001b[1;32m   2124\u001b[0m                     \u001b[0morientation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morientation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2125\u001b[0m                     \u001b[0mbbox_inches_restore\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_bbox_inches_restore\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2126\u001b[0;31m                     **kwargs)\n\u001b[0m\u001b[1;32m   2127\u001b[0m             \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2128\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mbbox_inches\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mrestore_bbox\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mprint_png\u001b[0;34m(self, filename_or_obj, metadata, pil_kwargs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    512\u001b[0m         }\n\u001b[1;32m    513\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 514\u001b[0;31m         \u001b[0mFigureCanvasAgg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    515\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mpil_kwargs\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    516\u001b[0m             \u001b[0;32mfrom\u001b[0m \u001b[0mPIL\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mImage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    386\u001b[0m         \u001b[0mDraw\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mfigure\u001b[0m \u001b[0musing\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    387\u001b[0m         \"\"\"\n\u001b[0;32m--> 388\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_renderer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcleared\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    389\u001b[0m         \u001b[0;31m# Acquire a lock on the shared font cache.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    390\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlock\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mget_renderer\u001b[0;34m(self, cleared)\u001b[0m\n\u001b[1;32m    402\u001b[0m                           and getattr(self, \"_lastKey\", None) == key)\n\u001b[1;32m    403\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mreuse_renderer\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 404\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    405\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lastKey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    406\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mcleared\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, width, height, dpi)\u001b[0m\n\u001b[1;32m     90\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwidth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     91\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 92\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_renderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_RendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     93\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_filter_renderers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     94\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: Image size of 91896x100944 pixels is too large. It must be less than 2^16 in each direction."
          ]
        },
        {
          "output_type": "stream",
          "text": [
            "Error in callback <function install_repl_displayhook.<locals>.post_execute at 0x7f1d2f763950> (for post_execute):\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mpost_execute\u001b[0;34m()\u001b[0m\n\u001b[1;32m    107\u001b[0m             \u001b[0;32mdef\u001b[0m \u001b[0mpost_execute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_interactive\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 109\u001b[0;31m                     \u001b[0mdraw_all\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    110\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    111\u001b[0m             \u001b[0;31m# IPython >= 2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/_pylab_helpers.py\u001b[0m in \u001b[0;36mdraw_all\u001b[0;34m(cls, force)\u001b[0m\n\u001b[1;32m    125\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mf_mgr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_all_fig_managers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    126\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mforce\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mf_mgr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstale\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 127\u001b[0;31m                 \u001b[0mf_mgr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw_idle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    129\u001b[0m \u001b[0matexit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mregister\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGcf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdestroy_all\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36mdraw_idle\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1945\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_is_idle_drawing\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1946\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_idle_draw_cntx\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1947\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1948\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1949\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdeprecated\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"3.2\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    386\u001b[0m         \u001b[0mDraw\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mfigure\u001b[0m \u001b[0musing\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    387\u001b[0m         \"\"\"\n\u001b[0;32m--> 388\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_renderer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcleared\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    389\u001b[0m         \u001b[0;31m# Acquire a lock on the shared font cache.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    390\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlock\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mget_renderer\u001b[0;34m(self, cleared)\u001b[0m\n\u001b[1;32m    402\u001b[0m                           and getattr(self, \"_lastKey\", None) == key)\n\u001b[1;32m    403\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mreuse_renderer\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 404\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    405\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lastKey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    406\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mcleared\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, width, height, dpi)\u001b[0m\n\u001b[1;32m     90\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwidth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     91\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 92\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_renderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_RendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     93\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_filter_renderers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     94\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: Image size of 91896x100944 pixels is too large. It must be less than 2^16 in each direction."
          ]
        },
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    332\u001b[0m                 \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    333\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 334\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mprinter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    335\u001b[0m             \u001b[0;31m# Finally look for special method names\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    336\u001b[0m             \u001b[0mmethod\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_real_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_method\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/IPython/core/pylabtools.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(fig)\u001b[0m\n\u001b[1;32m    239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    240\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m'png'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mformats\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 241\u001b[0;31m         \u001b[0mpng_formatter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfor_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFigure\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mprint_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'png'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    242\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m'retina'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mformats\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;34m'png2x'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mformats\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    243\u001b[0m         \u001b[0mpng_formatter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfor_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFigure\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mretina_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/IPython/core/pylabtools.py\u001b[0m in \u001b[0;36mprint_figure\u001b[0;34m(fig, fmt, bbox_inches, **kwargs)\u001b[0m\n\u001b[1;32m    123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    124\u001b[0m     \u001b[0mbytes_io\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 125\u001b[0;31m     \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbytes_io\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    126\u001b[0m     \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbytes_io\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    127\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mfmt\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'svg'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36mprint_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, **kwargs)\u001b[0m\n\u001b[1;32m   2092\u001b[0m                         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2093\u001b[0m                         functools.partial(\n\u001b[0;32m-> 2094\u001b[0;31m                             print_method, dpi=dpi, orientation=orientation)\n\u001b[0m\u001b[1;32m   2095\u001b[0m                         )\n\u001b[1;32m   2096\u001b[0m                     ctx = (renderer._draw_disabled()\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36m_get_renderer\u001b[0;34m(figure, print_method)\u001b[0m\n\u001b[1;32m   1558\u001b[0m     \u001b[0;32mwith\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setattr_cm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_draw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1559\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1560\u001b[0;31m             \u001b[0mprint_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1561\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mDone\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1562\u001b[0m             \u001b[0mrenderer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_cachedRenderer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mprint_png\u001b[0;34m(self, filename_or_obj, metadata, pil_kwargs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    512\u001b[0m         }\n\u001b[1;32m    513\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 514\u001b[0;31m         \u001b[0mFigureCanvasAgg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    515\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mpil_kwargs\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    516\u001b[0m             \u001b[0;32mfrom\u001b[0m \u001b[0mPIL\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mImage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    386\u001b[0m         \u001b[0mDraw\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mfigure\u001b[0m \u001b[0musing\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    387\u001b[0m         \"\"\"\n\u001b[0;32m--> 388\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_renderer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcleared\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    389\u001b[0m         \u001b[0;31m# Acquire a lock on the shared font cache.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    390\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlock\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mget_renderer\u001b[0;34m(self, cleared)\u001b[0m\n\u001b[1;32m    402\u001b[0m                           and getattr(self, \"_lastKey\", None) == key)\n\u001b[1;32m    403\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mreuse_renderer\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 404\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    405\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lastKey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    406\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mcleared\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, width, height, dpi)\u001b[0m\n\u001b[1;32m     90\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwidth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     91\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 92\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_renderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_RendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     93\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_filter_renderers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     94\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: Image size of 91896x100944 pixels is too large. It must be less than 2^16 in each direction."
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 91896x100944 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wVllabCDRBK6"
      },
      "source": [
        "### ScratchPad\r\n",
        "Try anything here!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AQXOn8N-RcBu"
      },
      "source": [
        "pass"
      ],
      "execution_count": 14,
      "outputs": []
    }
  ]
}