{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyObqNCLpsWtMml3ZpfO539Z",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Hafsah2020/geospatial_analysis/blob/main/geospatial_tutorial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install geopandas\n",
        "\n",
        "# install geopandas"
      ],
      "metadata": {
        "id": "d_hSpXedRHEH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_rrLe778Q68r"
      },
      "outputs": [],
      "source": [
        "import geopandas\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "#impor the libraries I need"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = geopandas.read_file('/content/drive/MyDrive/geospatial training/toxic_release_pennsylvania.shp')\n",
        "\n",
        "#read in data to variable 'data'"
      ],
      "metadata": {
        "id": "7Xzo8XOeWoQX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()\n",
        "\n",
        "# View data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "cVAm13oDXL5D",
        "outputId": "4dcc9fa5-dc58-43aa-9646-06f5c5e9eeab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   YEAR          CITY        COUNTY  ST   LATITUDE  LONGITUDE  \\\n",
              "0  2016  PHILADELPHIA  PHILADELPHIA  PA  40.005901 -75.072103   \n",
              "1  2016  PHILADELPHIA  PHILADELPHIA  PA  39.920120 -75.146410   \n",
              "2  2016  PHILADELPHIA  PHILADELPHIA  PA  40.023880 -75.220450   \n",
              "3  2016  PHILADELPHIA  PHILADELPHIA  PA  39.913540 -75.198890   \n",
              "4  2016  PHILADELPHIA  PHILADELPHIA  PA  39.913540 -75.198890   \n",
              "\n",
              "                CHEMICAL UNIT_OF_ME  TOTAL_RELE  \\\n",
              "0            FORMIC ACID     Pounds       0.160   \n",
              "1        ETHYLENE GLYCOL     Pounds   13353.480   \n",
              "2  CERTAIN GLYCOL ETHERS     Pounds     104.135   \n",
              "3         LEAD COMPOUNDS     Pounds    1730.280   \n",
              "4                BENZENE     Pounds   39863.290   \n",
              "\n",
              "                         geometry  \n",
              "0  POINT (2718560.227 256380.179)  \n",
              "1  POINT (2698674.606 224522.905)  \n",
              "2  POINT (2676833.394 261701.856)  \n",
              "3  POINT (2684030.004 221697.388)  \n",
              "4  POINT (2684030.004 221697.388)  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-47823064-48eb-46ab-ac42-63b12191def1\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>YEAR</th>\n",
              "      <th>CITY</th>\n",
              "      <th>COUNTY</th>\n",
              "      <th>ST</th>\n",
              "      <th>LATITUDE</th>\n",
              "      <th>LONGITUDE</th>\n",
              "      <th>CHEMICAL</th>\n",
              "      <th>UNIT_OF_ME</th>\n",
              "      <th>TOTAL_RELE</th>\n",
              "      <th>geometry</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2016</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PA</td>\n",
              "      <td>40.005901</td>\n",
              "      <td>-75.072103</td>\n",
              "      <td>FORMIC ACID</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>0.160</td>\n",
              "      <td>POINT (2718560.227 256380.179)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2016</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PA</td>\n",
              "      <td>39.920120</td>\n",
              "      <td>-75.146410</td>\n",
              "      <td>ETHYLENE GLYCOL</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>13353.480</td>\n",
              "      <td>POINT (2698674.606 224522.905)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2016</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PA</td>\n",
              "      <td>40.023880</td>\n",
              "      <td>-75.220450</td>\n",
              "      <td>CERTAIN GLYCOL ETHERS</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>104.135</td>\n",
              "      <td>POINT (2676833.394 261701.856)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2016</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PA</td>\n",
              "      <td>39.913540</td>\n",
              "      <td>-75.198890</td>\n",
              "      <td>LEAD COMPOUNDS</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>1730.280</td>\n",
              "      <td>POINT (2684030.004 221697.388)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2016</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PHILADELPHIA</td>\n",
              "      <td>PA</td>\n",
              "      <td>39.913540</td>\n",
              "      <td>-75.198890</td>\n",
              "      <td>BENZENE</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>39863.290</td>\n",
              "      <td>POINT (2684030.004 221697.388)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-47823064-48eb-46ab-ac42-63b12191def1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-47823064-48eb-46ab-ac42-63b12191def1 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-47823064-48eb-46ab-ac42-63b12191def1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['CHEMICAL'].unique()\n",
        "\n",
        "# The types of chemicals available"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nhjoA8iCXN9B",
        "outputId": "297c6a24-aabe-414d-cc4c-c4cfeb790b42"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['FORMIC ACID', 'ETHYLENE GLYCOL', 'CERTAIN GLYCOL ETHERS',\n",
              "       'LEAD COMPOUNDS', 'BENZENE', 'ETHYLBENZENE',\n",
              "       '1,2,4-TRIMETHYLBENZENE',\n",
              "       'SULFURIC ACID (1994 AND AFTER ACID AEROSOLS\" ONLY)\"',\n",
              "       'ZINC COMPOUNDS', 'BARIUM COMPOUNDS', 'ANTIMONY COMPOUNDS',\n",
              "       'MERCURY COMPOUNDS', 'SILVER', 'PHTHALIC ANHYDRIDE',\n",
              "       'DICYCLOPENTADIENE', 'AMMONIA', 'STYRENE', 'NICKEL',\n",
              "       'TETRABROMOBISPHENOL A', 'TOLUENE', 'N-BUTYL ALCOHOL', 'COPPER',\n",
              "       'PHENOL', 'XYLENE (MIXED ISOMERS)', 'CUMENE', 'METHANOL',\n",
              "       'ETHYLENE', 'HYDROGEN SULFIDE', 'NICKEL COMPOUNDS', 'PROPYLENE',\n",
              "       'ACETOPHENONE', 'TRADE SECRET CHEMICAL', 'MANGANESE',\n",
              "       'CUMENE HYDROPEROXIDE', 'LEAD', 'METHYL METHACRYLATE', 'CHROMIUM',\n",
              "       'BENZO(G,H,I)PERYLENE', 'COPPER COMPOUNDS', 'N-HEXANE',\n",
              "       'ACETALDEHYDE', 'MALEIC ANHYDRIDE', 'FORMALDEHYDE',\n",
              "       '2,2-BIS(BROMOMETHYL)-1,3-PROPANEDIOL', 'MANGANESE COMPOUNDS',\n",
              "       'HYDROGEN CYANIDE', 'DICHLOROMETHANE', 'PROPIONALDEHYDE',\n",
              "       'COBALT COMPOUNDS', 'NAPHTHALENE', 'CYCLOHEXANE',\n",
              "       'HYDROGEN FLUORIDE', 'POLYCYCLIC AROMATIC COMPOUNDS',\n",
              "       'ZINC (FUME OR DUST)', 'TETRACHLOROETHYLENE', 'TRICHLOROETHYLENE',\n",
              "       'BENZOYL PEROXIDE', 'MERCURY', 'NITRIC ACID',\n",
              "       'N,N-DIMETHYLFORMAMIDE', 'N-METHYL-2-PYRROLIDONE', 'OXYFLUORFEN',\n",
              "       'POLYCHLORINATED BIPHENYLS', 'METHYL ISOBUTYL KETONE',\n",
              "       'ASBESTOS (FRIABLE)', 'NITRATE COMPOUNDS',\n",
              "       'DI(2-ETHYLHEXYL) PHTHALATE', 'DIETHANOLAMINE',\n",
              "       'METHYL TERT-BUTYL ETHER', 'CHLORODIFLUOROMETHANE',\n",
              "       'DIBUTYL PHTHALATE', 'DIOXIN AND DIOXIN-LIKE COMPOUNDS', 'MIXTURE',\n",
              "       'VANADIUM COMPOUNDS', '1,3-BUTADIENE', 'METHYL ETHYL KETONE',\n",
              "       'CYANIDE COMPOUNDS', 'DECABROMODIPHENYL OXIDE', 'SODIUM NITRITE',\n",
              "       '1,2-BUTYLENE OXIDE',\n",
              "       'CHROMIUM COMPOUNDS(EXCEPT CHROMITE ORE MINED IN THE TRANSVAAL REGION)',\n",
              "       'TERT-BUTYL ALCOHOL', '1,2-DICHLOROETHANE',\n",
              "       'TOLUENE DIISOCYANATE (MIXED ISOMERS)', 'CHLORENDIC ACID',\n",
              "       'BUTYL ACRYLATE', 'CHLORINE', 'SEC-BUTYL ALCOHOL',\n",
              "       'ALUMINUM (FUME OR DUST)', 'POLYCHLORINATED ALKANES',\n",
              "       'LITHIUM CARBONATE', 'PHOSPHORIC ACID', 'BERYLLIUM',\n",
              "       'HYDROCHLORIC ACID (1995 AND AFTER ACID AEROSOLS\" ONLY)\"',\n",
              "       'COBALT', 'CHLOROMETHANE', 'CADMIUM', '2-ETHOXYETHANOL',\n",
              "       'O-XYLENE', 'FREON 113', '1,1,1-TRICHLOROETHANE',\n",
              "       'ISOBUTYRALDEHYDE', 'ETHYLENE OXIDE', '1,2-DICHLOROPROPANE',\n",
              "       'M-XYLENE', 'BENZYL CHLORIDE', 'ARSENIC COMPOUNDS',\n",
              "       'PROPYLENE OXIDE', 'CARBON TETRACHLORIDE',\n",
              "       'DICHLORODIFLUOROMETHANE', 'P-XYLENE', 'ACETONE',\n",
              "       '1,4-DICHLOROBENZENE', 'CHLOROMETHYL METHYL ETHER', 'BROMOMETHANE',\n",
              "       'TOLUENE-2,4-DIISOCYANATE', 'AMMONIUM SULFATE (SOLUTION)',\n",
              "       'CHLOROPHENOLS', 'EPICHLOROHYDRIN', 'BIS(CHLOROMETHYL) ETHER',\n",
              "       'CHLOROFORM', 'BIPHENYL',\n",
              "       'ISOPROPYL ALCOHOL (MANUFACTURING,STRONG-ACID PROCESS ONLY,NO SUPPLIER)',\n",
              "       'CHLOROBENZENE', 'DIETHYL PHTHALATE', 'MOLYBDENUM TRIOXIDE',\n",
              "       '1,2,4-TRICHLOROBENZENE', 'ACRYLIC ACID', 'N-DIOCTYL PHTHALATE',\n",
              "       'ALUMINUM OXIDE (FIBROUS FORMS)', 'PHOSPHORUS (YELLOW OR WHITE)',\n",
              "       'SODIUM HYDROXIDE (SOLUTION)', 'ANTIMONY', 'BARIUM',\n",
              "       'TOLUENE-2,6-DIISOCYANATE', 'SODIUM SULFATE (SOLUTION)',\n",
              "       '1,2-DIBROMOETHANE', 'VINYL CHLORIDE'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "From assessment this data is only on Pennsylvania, I will drop non-relevant columns"
      ],
      "metadata": {
        "id": "3DgLlG9QYNDN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data = data.drop(['CITY','COUNTY','ST'], axis = 1)"
      ],
      "metadata": {
        "id": "NaaLg_k7X459"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data. head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "rFyQneOPYxc6",
        "outputId": "51d73635-8672-40f4-bc0c-e77f48ef0aa8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   YEAR   LATITUDE  LONGITUDE               CHEMICAL UNIT_OF_ME  TOTAL_RELE  \\\n",
              "0  2016  40.005901 -75.072103            FORMIC ACID     Pounds       0.160   \n",
              "1  2016  39.920120 -75.146410        ETHYLENE GLYCOL     Pounds   13353.480   \n",
              "2  2016  40.023880 -75.220450  CERTAIN GLYCOL ETHERS     Pounds     104.135   \n",
              "3  2016  39.913540 -75.198890         LEAD COMPOUNDS     Pounds    1730.280   \n",
              "4  2016  39.913540 -75.198890                BENZENE     Pounds   39863.290   \n",
              "\n",
              "                         geometry  \n",
              "0  POINT (2718560.227 256380.179)  \n",
              "1  POINT (2698674.606 224522.905)  \n",
              "2  POINT (2676833.394 261701.856)  \n",
              "3  POINT (2684030.004 221697.388)  \n",
              "4  POINT (2684030.004 221697.388)  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4dfcbd2b-2c06-4e90-a2f3-7fe6005d25de\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>YEAR</th>\n",
              "      <th>LATITUDE</th>\n",
              "      <th>LONGITUDE</th>\n",
              "      <th>CHEMICAL</th>\n",
              "      <th>UNIT_OF_ME</th>\n",
              "      <th>TOTAL_RELE</th>\n",
              "      <th>geometry</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2016</td>\n",
              "      <td>40.005901</td>\n",
              "      <td>-75.072103</td>\n",
              "      <td>FORMIC ACID</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>0.160</td>\n",
              "      <td>POINT (2718560.227 256380.179)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2016</td>\n",
              "      <td>39.920120</td>\n",
              "      <td>-75.146410</td>\n",
              "      <td>ETHYLENE GLYCOL</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>13353.480</td>\n",
              "      <td>POINT (2698674.606 224522.905)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2016</td>\n",
              "      <td>40.023880</td>\n",
              "      <td>-75.220450</td>\n",
              "      <td>CERTAIN GLYCOL ETHERS</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>104.135</td>\n",
              "      <td>POINT (2676833.394 261701.856)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2016</td>\n",
              "      <td>39.913540</td>\n",
              "      <td>-75.198890</td>\n",
              "      <td>LEAD COMPOUNDS</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>1730.280</td>\n",
              "      <td>POINT (2684030.004 221697.388)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2016</td>\n",
              "      <td>39.913540</td>\n",
              "      <td>-75.198890</td>\n",
              "      <td>BENZENE</td>\n",
              "      <td>Pounds</td>\n",
              "      <td>39863.290</td>\n",
              "      <td>POINT (2684030.004 221697.388)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4dfcbd2b-2c06-4e90-a2f3-7fe6005d25de')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4dfcbd2b-2c06-4e90-a2f3-7fe6005d25de button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4dfcbd2b-2c06-4e90-a2f3-7fe6005d25de');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['geometry'].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        },
        "id": "7RCBMd-FZAA4",
        "outputId": "b17a5f1f-7798-47d8-cb5f-9e7a45d52225"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "-lD9oxRZZFMJ"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}