TID_Innovation_Challenge.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ShiroDima/TID-TIC045/blob/main/TID_Innovation_Challenge.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qm-1NYePB3qz"
      },
      "source": [
        "# Importing Neccesary libraries                                                "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 125,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kqLNNf9JDmHD",
        "outputId": "14bb559e-e0cd-46e7-f959-b4e07c3a9c99"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: geopandas in /usr/local/lib/python3.10/dist-packages (0.13.0)\n",
            "Requirement already satisfied: folium in /usr/local/lib/python3.10/dist-packages (0.14.0)\n",
            "Requirement already satisfied: fiona>=1.8.19 in /usr/local/lib/python3.10/dist-packages (from geopandas) (1.9.3)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from geopandas) (23.1)\n",
            "Requirement already satisfied: pandas>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from geopandas) (1.5.3)\n",
            "Requirement already satisfied: pyproj>=3.0.1 in /usr/local/lib/python3.10/dist-packages (from geopandas) (3.5.0)\n",
            "Requirement already satisfied: shapely>=1.7.1 in /usr/local/lib/python3.10/dist-packages (from geopandas) (2.0.1)\n",
            "Requirement already satisfied: branca>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from folium) (0.6.0)\n",
            "Requirement already satisfied: jinja2>=2.9 in /usr/local/lib/python3.10/dist-packages (from folium) (3.1.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from folium) (1.22.4)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from folium) (2.27.1)\n",
            "Requirement already satisfied: attrs>=19.2.0 in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (23.1.0)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (2022.12.7)\n",
            "Requirement already satisfied: click~=8.0 in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (8.1.3)\n",
            "Requirement already satisfied: click-plugins>=1.0 in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (1.1.1)\n",
            "Requirement already satisfied: cligj>=0.5 in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (0.7.2)\n",
            "Requirement already satisfied: munch>=2.3.2 in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (2.5.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2>=2.9->folium) (2.1.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.0->geopandas) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.0->geopandas) (2022.7.1)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->folium) (1.26.15)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->folium) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->folium) (3.4)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from munch>=2.3.2->fiona>=1.8.19->geopandas) (1.16.0)\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: rasterio in /usr/local/lib/python3.10/dist-packages (1.3.6)\n",
            "Requirement already satisfied: affine in /usr/local/lib/python3.10/dist-packages (from rasterio) (2.4.0)\n",
            "Requirement already satisfied: attrs in /usr/local/lib/python3.10/dist-packages (from rasterio) (23.1.0)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from rasterio) (2022.12.7)\n",
            "Requirement already satisfied: click>=4.0 in /usr/local/lib/python3.10/dist-packages (from rasterio) (8.1.3)\n",
            "Requirement already satisfied: cligj>=0.5 in /usr/local/lib/python3.10/dist-packages (from rasterio) (0.7.2)\n",
            "Requirement already satisfied: numpy>=1.18 in /usr/local/lib/python3.10/dist-packages (from rasterio) (1.22.4)\n",
            "Requirement already satisfied: snuggs>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from rasterio) (1.4.7)\n",
            "Requirement already satisfied: click-plugins in /usr/local/lib/python3.10/dist-packages (from rasterio) (1.1.1)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from rasterio) (67.7.2)\n",
            "Requirement already satisfied: pyparsing>=2.1.6 in /usr/local/lib/python3.10/dist-packages (from snuggs>=1.4.1->rasterio) (3.0.9)\n"
          ]
        }
      ],
      "source": [
        "! pip install geopandas folium                                              \n",
        "! pip install rasterio"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 126,
      "metadata": {
        "id": "rVNadBwHEHHN"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import geopandas as gpd\n",
        "from shapely.geometry import Point\n",
        "import folium\n",
        "import matplotlib.pyplot as plt                                            \n",
        "import rasterio\n",
        "from datetime import datetime                                               "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hWkywFjiCFLq"
      },
      "source": [
        "# Loading and Previewing Data                                               "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 127,
      "metadata": {
        "id": "A-TtmnAIGIBo"
      },
      "outputs": [],
      "source": [
        "transmission_substations_csv=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/all_transmission_substations.csv')\n",
        "power_plants_csv=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/power_plants.csv')\n",
        "transmission_lines_csv=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/transmission_lines.csv')\n",
        "cluster_offgrid_csv=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/cluster_offgrid.csv')\n",
        "minigrids_csv=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/minigrids (2).csv')\n",
        "state_boundaries_csv=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/nigeria_state_boundaries.csv')\n",
        "electrical_grid=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/electrical_grid_nigeria_15.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 128,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
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        "id": "31W8PO9cGZjY",
        "outputId": "66bcbe2a-a7ba-451b-8c5a-0b6d6bf6f765"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                    FID     osm_id power_substation tags  \\\n",
              "0  all_transmission_substations.3114602  564813837       substation   {}   \n",
              "1  all_transmission_substations.3114625  564466620       substation   {}   \n",
              "2  all_transmission_substations.3117563  564468439       substation   {}   \n",
              "3  all_transmission_substations.3128584  564469422       substation   {}   \n",
              "4  all_transmission_substations.3130639  574213499       substation   {}   \n",
              "\n",
              "                                           geom  \n",
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          "metadata": {},
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      "source": [
        "transmission_substations_csv.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 129,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
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        "id": "4CXXG687F6P6",
        "outputId": "29bf44f8-b9b4-46f2-eb4b-738656b2907c"
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                FID                                        description  \\\n",
              "0    power_plants.7                   Jebba Hydroelectric Power Plant    \n",
              "1    power_plants.1                     AES Nigeria BARGE IPP Limited    \n",
              "2    power_plants.2                       Egbin Thermal Power Station    \n",
              "3    power_plants.3                  Olorunsogo II Power Plant - NIPP    \n",
              "4    power_plants.4                            Olorunsogo Power Plant    \n",
              "5    power_plants.5                        Omotosho Power Plant - NIPP   \n",
              "6    power_plants.6                     Omotosho I & II Power Station    \n",
              "7    power_plants.8                Kainji Hydroelectric Power Station    \n",
              "8    power_plants.9               Shiroro Hydroelectric Power Station    \n",
              "9   power_plants.10  Delta Power Station (Transcorp Ughelli Power S...   \n",
              "10  power_plants.11                       Gerugu II Power Plant - NIPP   \n",
              "11  power_plants.12                            Gerugu I Power Station    \n",
              "12  power_plants.13                         Ihovbor Power Plant - NIPP   \n",
              "13  power_plants.14                          Sapele Power Plant - NIPP   \n",
              "14  power_plants.15                              Sapele Power Station    \n",
              "15  power_plants.16                                 Okpai Power Plant    \n",
              "16  power_plants.17                             Afam IV-V Power Plant    \n",
              "17  power_plants.18                               Afam VI Power Plant    \n",
              "18  power_plants.19                         Alaoiji Power Plant - NIPP   \n",
              "19  power_plants.20                           Ibom Power Station (IPP)   \n",
              "20  power_plants.21                   Odukpani  (Calabar) Power Plant    \n",
              "21  power_plants.22                           Omoku Power Plant - NIPP   \n",
              "22  power_plants.23                      Trans-Amadi Power Plant (IPP)   \n",
              "23  power_plants.24                           Rivers Power Plant (IPP)   \n",
              "24  power_plants.25                  ASCO (Ajaokuta Steel Company) IPP   \n",
              "25  power_plants.26                  Azura Thermal Power Station (IPP)   \n",
              "26  power_plants.27              Paras Energy & Natural Res. Dev. Ltd.   \n",
              "27  power_plants.28                         Gbarain Power Plant - NIPP   \n",
              "\n",
              "   types_of_plants       lat      long  installation_capacity_mw  \\\n",
              "0            Hydro  9.135556  4.787778                       570   \n",
              "1             Gas   6.559167  3.615000                       270   \n",
              "2           Steam   6.563056  3.615278                      1320   \n",
              "3     Gas; Steam    6.885556  3.315556                       720   \n",
              "4             Gas   6.881944  3.314444                       320   \n",
              "5             Gas   6.735833  4.710833                       480   \n",
              "6             Gas   6.735833  4.710833                       304   \n",
              "7            Hydro  9.862500  4.613333                       760   \n",
              "8            Hydro  9.975000  6.834444                       600   \n",
              "9             Gas   5.541111  5.915556                       860   \n",
              "10            Gas   7.563056  6.692778                       435   \n",
              "11            Gas   7.416111  6.919733                       405   \n",
              "12            Gas   6.405556  5.683333                       480   \n",
              "13            Gas   5.927778  5.644722                       480   \n",
              "14          Steam   5.925278  5.645556                       420   \n",
              "15            Gas   5.710300  6.575610                       470   \n",
              "16            Gas   4.851389  7.254722                       260   \n",
              "17     Gas; Steam   4.849444  7.256667                       725   \n",
              "18            Gas   5.066667  7.323333                       480   \n",
              "19            Gas   4.564722  7.568333                       174   \n",
              "20            Gas   5.189167  8.273611                       600   \n",
              "21            Gas   5.390000  6.663333                       120   \n",
              "22            Gas   4.815994  7.031416                        80   \n",
              "23            Gas        NaN       NaN                       160   \n",
              "24            Gas   7.514400  6.690590                       110   \n",
              "25            Gas   6.408889  5.683611                       460   \n",
              "26            Gas   6.720140  3.522200                        96   \n",
              "27            Gas   5.032230  6.301560                       250   \n",
              "\n",
              "                                             geom  \n",
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              "      <td>power_plants.7</td>\n",
              "      <td>Jebba Hydroelectric Power Plant</td>\n",
              "      <td>Hydro</td>\n",
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              "      <td>570</td>\n",
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              "      <td>power_plants.1</td>\n",
              "      <td>AES Nigeria BARGE IPP Limited</td>\n",
              "      <td>Gas</td>\n",
              "      <td>6.559167</td>\n",
              "      <td>3.615000</td>\n",
              "      <td>270</td>\n",
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              "      <th>2</th>\n",
              "      <td>power_plants.2</td>\n",
              "      <td>Egbin Thermal Power Station</td>\n",
              "      <td>Steam</td>\n",
              "      <td>6.563056</td>\n",
              "      <td>3.615278</td>\n",
              "      <td>1320</td>\n",
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              "      <th>3</th>\n",
              "      <td>power_plants.3</td>\n",
              "      <td>Olorunsogo II Power Plant - NIPP</td>\n",
              "      <td>Gas; Steam</td>\n",
              "      <td>6.885556</td>\n",
              "      <td>3.315556</td>\n",
              "      <td>720</td>\n",
              "      <td>POINT (369085.9610887856 768348.2126840537)</td>\n",
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              "      <th>4</th>\n",
              "      <td>power_plants.4</td>\n",
              "      <td>Olorunsogo Power Plant</td>\n",
              "      <td>Gas</td>\n",
              "      <td>6.881944</td>\n",
              "      <td>3.314444</td>\n",
              "      <td>320</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>power_plants.5</td>\n",
              "      <td>Omotosho Power Plant - NIPP</td>\n",
              "      <td>Gas</td>\n",
              "      <td>6.735833</td>\n",
              "      <td>4.710833</td>\n",
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              "      <th>6</th>\n",
              "      <td>power_plants.6</td>\n",
              "      <td>Omotosho I &amp; II Power Station</td>\n",
              "      <td>Gas</td>\n",
              "      <td>6.735833</td>\n",
              "      <td>4.710833</td>\n",
              "      <td>304</td>\n",
              "      <td>POINT (524407.5641679956 751562.7491455841)</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>power_plants.8</td>\n",
              "      <td>Kainji Hydroelectric Power Station</td>\n",
              "      <td>Hydro</td>\n",
              "      <td>9.862500</td>\n",
              "      <td>4.613333</td>\n",
              "      <td>760</td>\n",
              "      <td>POINT (513553.91381565353 1103350.6911312963)</td>\n",
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              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>power_plants.9</td>\n",
              "      <td>Shiroro Hydroelectric Power Station</td>\n",
              "      <td>Hydro</td>\n",
              "      <td>9.975000</td>\n",
              "      <td>6.834444</td>\n",
              "      <td>600</td>\n",
              "      <td>POINT (760806.8704629388 1116064.1641375)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>power_plants.10</td>\n",
              "      <td>Delta Power Station (Transcorp Ughelli Power S...</td>\n",
              "      <td>Gas</td>\n",
              "      <td>5.541111</td>\n",
              "      <td>5.915556</td>\n",
              "      <td>860</td>\n",
              "      <td>POINT (658516.6371512987 617797.4558860898)</td>\n",
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              "      <th>10</th>\n",
              "      <td>power_plants.11</td>\n",
              "      <td>Gerugu II Power Plant - NIPP</td>\n",
              "      <td>Gas</td>\n",
              "      <td>7.563056</td>\n",
              "      <td>6.692778</td>\n",
              "      <td>435</td>\n",
              "      <td>POINT (745036.6166885244 844371.1334096566)</td>\n",
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              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>power_plants.12</td>\n",
              "      <td>Gerugu I Power Station</td>\n",
              "      <td>Gas</td>\n",
              "      <td>7.416111</td>\n",
              "      <td>6.919733</td>\n",
              "      <td>405</td>\n",
              "      <td>POINT (770301.1873812595 827872.5868619345)</td>\n",
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              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>power_plants.13</td>\n",
              "      <td>Ihovbor Power Plant - NIPP</td>\n",
              "      <td>Gas</td>\n",
              "      <td>6.405556</td>\n",
              "      <td>5.683333</td>\n",
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              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>power_plants.14</td>\n",
              "      <td>Sapele Power Plant - NIPP</td>\n",
              "      <td>Gas</td>\n",
              "      <td>5.927778</td>\n",
              "      <td>5.644722</td>\n",
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              "      <th>14</th>\n",
              "      <td>power_plants.15</td>\n",
              "      <td>Sapele Power Station</td>\n",
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              "      <th>15</th>\n",
              "      <td>power_plants.16</td>\n",
              "      <td>Okpai Power Plant</td>\n",
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              "      <td>5.710300</td>\n",
              "      <td>6.575610</td>\n",
              "      <td>470</td>\n",
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              "      <th>16</th>\n",
              "      <td>power_plants.17</td>\n",
              "      <td>Afam IV-V Power Plant</td>\n",
              "      <td>Gas</td>\n",
              "      <td>4.851389</td>\n",
              "      <td>7.254722</td>\n",
              "      <td>260</td>\n",
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              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>power_plants.18</td>\n",
              "      <td>Afam VI Power Plant</td>\n",
              "      <td>Gas; Steam</td>\n",
              "      <td>4.849444</td>\n",
              "      <td>7.256667</td>\n",
              "      <td>725</td>\n",
              "      <td>POINT (807808.4419005037 540483.3791233592)</td>\n",
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              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>power_plants.19</td>\n",
              "      <td>Alaoiji Power Plant - NIPP</td>\n",
              "      <td>Gas</td>\n",
              "      <td>5.066667</td>\n",
              "      <td>7.323333</td>\n",
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              "      <th>19</th>\n",
              "      <td>power_plants.20</td>\n",
              "      <td>Ibom Power Station (IPP)</td>\n",
              "      <td>Gas</td>\n",
              "      <td>4.564722</td>\n",
              "      <td>7.568333</td>\n",
              "      <td>174</td>\n",
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              "      <th>20</th>\n",
              "      <td>power_plants.21</td>\n",
              "      <td>Odukpani  (Calabar) Power Plant</td>\n",
              "      <td>Gas</td>\n",
              "      <td>5.189167</td>\n",
              "      <td>8.273611</td>\n",
              "      <td>600</td>\n",
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              "      <th>21</th>\n",
              "      <td>power_plants.22</td>\n",
              "      <td>Omoku Power Plant - NIPP</td>\n",
              "      <td>Gas</td>\n",
              "      <td>5.390000</td>\n",
              "      <td>6.663333</td>\n",
              "      <td>120</td>\n",
              "      <td>POINT (741758.836546015 600899.0137811431)</td>\n",
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              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>power_plants.23</td>\n",
              "      <td>Trans-Amadi Power Plant (IPP)</td>\n",
              "      <td>Gas</td>\n",
              "      <td>4.815994</td>\n",
              "      <td>7.031416</td>\n",
              "      <td>80</td>\n",
              "      <td>POINT (782733.6486756761 536746.4123286618)</td>\n",
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              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>power_plants.24</td>\n",
              "      <td>Rivers Power Plant (IPP)</td>\n",
              "      <td>Gas</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>160</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>power_plants.25</td>\n",
              "      <td>ASCO (Ajaokuta Steel Company) IPP</td>\n",
              "      <td>Gas</td>\n",
              "      <td>7.514400</td>\n",
              "      <td>6.690590</td>\n",
              "      <td>110</td>\n",
              "      <td>POINT (744793.0719065692 838907.5920056782)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>power_plants.26</td>\n",
              "      <td>Azura Thermal Power Station (IPP)</td>\n",
              "      <td>Gas</td>\n",
              "      <td>6.408889</td>\n",
              "      <td>5.683611</td>\n",
              "      <td>460</td>\n",
              "      <td>POINT (632696.6823870491 714926.6565212721)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>power_plants.27</td>\n",
              "      <td>Paras Energy &amp; Natural Res. Dev. Ltd.</td>\n",
              "      <td>Gas</td>\n",
              "      <td>6.720140</td>\n",
              "      <td>3.522200</td>\n",
              "      <td>96</td>\n",
              "      <td>POINT (392089.5104720689 749803.6651171149)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>power_plants.28</td>\n",
              "      <td>Gbarain Power Plant - NIPP</td>\n",
              "      <td>Gas</td>\n",
              "      <td>5.032230</td>\n",
              "      <td>6.301560</td>\n",
              "      <td>250</td>\n",
              "      <td>POINT (701486.450403261 560906.8781957559)</td>\n",
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      ]
    },
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          "data": {
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              "                    FID  fid_1  \\\n",
              "0  transmission_lines.1      1   \n",
              "1  transmission_lines.2      2   \n",
              "2  transmission_lines.3      3   \n",
              "3  transmission_lines.4      4   \n",
              "4  transmission_lines.5      5   \n",
              "\n",
              "                                            geometry  fid  osm_power_line_id  \\\n",
              "0  LINESTRING (3.3854091 6.471850199423217, 3.387...    1              184.0   \n",
              "1  LINESTRING (6.8533431 6.140590799437865, 6.857...    2               87.0   \n",
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              "4  LINESTRING (6.8601059 6.146071299437604, 6.868...    5               83.0   \n",
              "\n",
              "        osm_id power_line                                       tags  offset  \n",
              "0  564441300.0       line  cables: 6, frequency: 50, voltage: 132000     6.0  \n",
              "1  575700596.0       line                            voltage: 330000     3.0  \n",
              "2  564402808.0       line                                        NaN     2.0  \n",
              "3  548722729.0       line                 cables: 3, voltage: 330000     6.0  \n",
              "4  575700594.0       line                            voltage: 330000     2.0  "
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              "      <th>offset</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>transmission_lines.1</td>\n",
              "      <td>1</td>\n",
              "      <td>LINESTRING (3.3854091 6.471850199423217, 3.387...</td>\n",
              "      <td>1</td>\n",
              "      <td>184.0</td>\n",
              "      <td>564441300.0</td>\n",
              "      <td>line</td>\n",
              "      <td>cables: 6, frequency: 50, voltage: 132000</td>\n",
              "      <td>6.0</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>transmission_lines.2</td>\n",
              "      <td>2</td>\n",
              "      <td>LINESTRING (6.8533431 6.140590799437865, 6.857...</td>\n",
              "      <td>2</td>\n",
              "      <td>87.0</td>\n",
              "      <td>575700596.0</td>\n",
              "      <td>line</td>\n",
              "      <td>voltage: 330000</td>\n",
              "      <td>3.0</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>transmission_lines.3</td>\n",
              "      <td>3</td>\n",
              "      <td>LINESTRING (6.0187912 9.147705199405225, 6.018...</td>\n",
              "      <td>3</td>\n",
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              "      <td>2.0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>transmission_lines.4</td>\n",
              "      <td>4</td>\n",
              "      <td>LINESTRING (7.5572314 6.402926199426054, 7.557...</td>\n",
              "      <td>4</td>\n",
              "      <td>550.0</td>\n",
              "      <td>548722729.0</td>\n",
              "      <td>line</td>\n",
              "      <td>cables: 3, voltage: 330000</td>\n",
              "      <td>6.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>transmission_lines.5</td>\n",
              "      <td>5</td>\n",
              "      <td>LINESTRING (6.8601059 6.146071299437604, 6.868...</td>\n",
              "      <td>5</td>\n",
              "      <td>83.0</td>\n",
              "      <td>575700594.0</td>\n",
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          "metadata": {},
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        "id": "K1zoxzlSF7Vu",
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              "                 FID  fid  area_km2  building_count  large_building_count  \\\n",
              "0  cluster_offgrid.1    1  0.372251             778                   480   \n",
              "1  cluster_offgrid.2    2  0.982818            1489                  1053   \n",
              "2  cluster_offgrid.3    3  0.436341             734                   440   \n",
              "3  cluster_offgrid.4    4  0.922544            1113                   819   \n",
              "4  cluster_offgrid.5    5  0.101582             110                    95   \n",
              "\n",
              "   percentage_large_building  building_area_km2  \\\n",
              "0                   0.616967           0.076766   \n",
              "1                   0.707186           0.188231   \n",
              "2                   0.599455           0.060379   \n",
              "3                   0.735849           0.144856   \n",
              "4                   0.863636           0.016632   \n",
              "\n",
              "   building_count_density_perkm2  percentage_building_area  grid_dist_km  \\\n",
              "0                    2089.987305                  0.206221     22.475574   \n",
              "1                    1515.031494                  0.191522     27.298412   \n",
              "2                    1682.171021                  0.138375     33.566612   \n",
              "3                    1206.446777                  0.157018     29.344755   \n",
              "4                    1082.867676                  0.163729     28.299776   \n",
              "\n",
              "                                                geom  \n",
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              "3  POLYGON ((694458.9513761475 480324.0167405627,...  \n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>cluster_offgrid.5</td>\n",
              "      <td>5</td>\n",
              "      <td>0.101582</td>\n",
              "      <td>110</td>\n",
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              "      <td>POLYGON ((697093.2256070838 480397.96057361393...</td>\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          "metadata": {},
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      "source": [
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      "execution_count": 132,
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        "id": "mOotU6KjF7a9",
        "outputId": "b850ad7d-b766-4c70-a42b-91b0d6ce8c7e"
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            FID  lga_name community        lat        lon  power_system  \\\n",
              "0  minigrids.26     Arewa      Kare  12.898667   4.062016  Solar Hybrid   \n",
              "1  minigrids.27     Kwali     Kigbe   8.681200   7.094500         Solar   \n",
              "2  minigrids.29   Balanga    Kolaku  10.039130  11.779307         Solar   \n",
              "3  minigrids.30  Kaltungo     Kolwa   9.704815  11.542259         Solar   \n",
              "4  minigrids.31   Shendan      Kuka   8.438683   9.695346  Solar Hybrid   \n",
              "\n",
              "   power_kw              status  number_of_connections      fund_type  \\\n",
              "0     100.0            Existing                  535.0  Equity; Grant   \n",
              "1      20.0            Existing                    NaN   Equity;Grant   \n",
              "2      47.0            Existing                  350.0   Equity;Grant   \n",
              "3      38.0            Existing                  200.0    Debt; Grant   \n",
              "4     150.0  Under Construction                 2782.0            NaN   \n",
              "\n",
              "             project                               owner        condition  \\\n",
              "0            REA;REF  Nayo Tropical Technologies Limited      Operational   \n",
              "1          Havenhill                           Havenhill      Operational   \n",
              "2       BoI;UNDP;GVE                                 GVE      Operational   \n",
              "3      BoI;UNDP;IEEE                                 GVE      Operational   \n",
              "4  All On; ElectriFI                                 GVE  Non Operational   \n",
              "\n",
              "  located                                          geom  \n",
              "0     Yes  POINT (452181.55271413096 1448157.525865247)  \n",
              "1     Yes    POINT (789756.1274328792 970105.676503249)  \n",
              "2     Yes  POINT (1311266.479401542 1123313.4044015515)  \n",
              "3     Yes  POINT (1284878.349956283 1085538.1687694453)  \n",
              "4     Yes  POINT (1079281.0020484996 942804.6383047344)  "
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              "      <th>condition</th>\n",
              "      <th>located</th>\n",
              "      <th>geom</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>minigrids.26</td>\n",
              "      <td>Arewa</td>\n",
              "      <td>Kare</td>\n",
              "      <td>12.898667</td>\n",
              "      <td>4.062016</td>\n",
              "      <td>Solar Hybrid</td>\n",
              "      <td>100.0</td>\n",
              "      <td>Existing</td>\n",
              "      <td>535.0</td>\n",
              "      <td>Equity; Grant</td>\n",
              "      <td>REA;REF</td>\n",
              "      <td>Nayo Tropical Technologies Limited</td>\n",
              "      <td>Operational</td>\n",
              "      <td>Yes</td>\n",
              "      <td>POINT (452181.55271413096 1448157.525865247)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>minigrids.27</td>\n",
              "      <td>Kwali</td>\n",
              "      <td>Kigbe</td>\n",
              "      <td>8.681200</td>\n",
              "      <td>7.094500</td>\n",
              "      <td>Solar</td>\n",
              "      <td>20.0</td>\n",
              "      <td>Existing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Equity;Grant</td>\n",
              "      <td>Havenhill</td>\n",
              "      <td>Havenhill</td>\n",
              "      <td>Operational</td>\n",
              "      <td>Yes</td>\n",
              "      <td>POINT (789756.1274328792 970105.676503249)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>minigrids.29</td>\n",
              "      <td>Balanga</td>\n",
              "      <td>Kolaku</td>\n",
              "      <td>10.039130</td>\n",
              "      <td>11.779307</td>\n",
              "      <td>Solar</td>\n",
              "      <td>47.0</td>\n",
              "      <td>Existing</td>\n",
              "      <td>350.0</td>\n",
              "      <td>Equity;Grant</td>\n",
              "      <td>BoI;UNDP;GVE</td>\n",
              "      <td>GVE</td>\n",
              "      <td>Operational</td>\n",
              "      <td>Yes</td>\n",
              "      <td>POINT (1311266.479401542 1123313.4044015515)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>minigrids.30</td>\n",
              "      <td>Kaltungo</td>\n",
              "      <td>Kolwa</td>\n",
              "      <td>9.704815</td>\n",
              "      <td>11.542259</td>\n",
              "      <td>Solar</td>\n",
              "      <td>38.0</td>\n",
              "      <td>Existing</td>\n",
              "      <td>200.0</td>\n",
              "      <td>Debt; Grant</td>\n",
              "      <td>BoI;UNDP;IEEE</td>\n",
              "      <td>GVE</td>\n",
              "      <td>Operational</td>\n",
              "      <td>Yes</td>\n",
              "      <td>POINT (1284878.349956283 1085538.1687694453)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>minigrids.31</td>\n",
              "      <td>Shendan</td>\n",
              "      <td>Kuka</td>\n",
              "      <td>8.438683</td>\n",
              "      <td>9.695346</td>\n",
              "      <td>Solar Hybrid</td>\n",
              "      <td>150.0</td>\n",
              "      <td>Under Construction</td>\n",
              "      <td>2782.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>All On; ElectriFI</td>\n",
              "      <td>GVE</td>\n",
              "      <td>Non Operational</td>\n",
              "      <td>Yes</td>\n",
              "      <td>POINT (1079281.0020484996 942804.6383047344)</td>\n",
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              "                              FID    adm1_en  \\\n",
              "0  nigeria_state_boundaries.NG001       Abia   \n",
              "1  nigeria_state_boundaries.NG002    Adamawa   \n",
              "2  nigeria_state_boundaries.NG003  Akwa Ibom   \n",
              "3  nigeria_state_boundaries.NG004    Anambra   \n",
              "4  nigeria_state_boundaries.NG005     Bauchi   \n",
              "\n",
              "                                                geom  \n",
              "0  MULTIPOLYGON (((822295.9619617525 673246.32529...  \n",
              "1  MULTIPOLYGON (((1516314.9825899764 1226236.927...  \n",
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              "      <td>MULTIPOLYGON (((1516314.9825899764 1226236.927...</td>\n",
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              "      <th>2</th>\n",
              "      <td>nigeria_state_boundaries.NG003</td>\n",
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              "        lat       lon  Electrical Distribution Grid\n",
              "0  7.520427  2.785034                             1\n",
              "1  6.397189  2.785034                             1\n",
              "2  6.724620  2.785034                             1\n",
              "3  6.691887  2.785034                             1\n",
              "4  6.429942  2.785034                             1"
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              "    }\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-c320aaa8-e176-407f-b3d5-d133d586eb0d 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-c320aaa8-e176-407f-b3d5-d133d586eb0d');\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": 134
        }
      ],
      "source": [
        "electrical_grid.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 135,
      "metadata": {
        "id": "zE7eDvYn0sIu"
      },
      "outputs": [],
      "source": [
        "electrical_grid['location']=electrical_grid.apply(lambda x: Point((x['lon'],x['lat'])),axis=1)                                                \n",
        "electrical_grid.to_csv('electrical_grid.csv')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F0brLTdEHJEQ"
      },
      "source": [
        "# Seperating Longitude and Latitude From String Paths                                           "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 136,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DI_E6XfZNm0T",
        "outputId": "43c9f199-1221-4bbf-96be-371462f3eb61"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "ERROR:fiona._env:Pointer 'hGeom' is NULL in 'OGR_G_GetGeometryType'.\n",
            "\n"
          ]
        }
      ],
      "source": [
        "transmission_lines=gpd.read_file('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/transmission_lines.csv',\n",
        "                                 GEOM_POSSIBLE_NAMES='geometry',\n",
        "                                 KEEP_GEOM_COLUMNS='NO')\n",
        "\n",
        "power_plants=gpd.read_file('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/power_plants.csv',\n",
        "                           GEOM_POSSIBLE_NAMES='geom',\n",
        "                           KEEP_GEOM_COLUMNS='NO')\n",
        "\n",
        "state_boundaries=gpd.read_file('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/nigeria_state_boundaries.csv',\n",
        "                               GEOM_POSSIBLE_NAMES='geom',\n",
        "                               KEEP_GEOM_COLUMNS='NO')\n",
        "                    \n",
        "\n",
        "transmission_substations=gpd.read_file('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/all_transmission_substations.csv',\n",
        "                                        GEOM_POSSIBLE_NAMES='geom',\n",
        "                                        KEEP_GEOM_COLUMNS='NO')\n",
        "\n",
        "data=gpd.read_file('/content/drive/MyDrive/TID_Innovation/Data/data.geojson')\n",
        "\n",
        "cluster_offgrid=gpd.read_file('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/cluster_offgrid.csv',\n",
        "                              GEOM_POSSIBLE_NAMES='geom',\n",
        "                              KEEP_GEOM_COLUMNS='NO')\n",
        "\n",
        "minigrids=gpd.read_file('/content/drive/MyDrive/TID_Innovation/Data/TID_Dataset/minigrids (2).csv',\n",
        "                        GEOM_POSSIBLE_NAMES='geom',\n",
        "                        KEEP_GEOM_COLUMNS='NO')\n",
        "\n",
        "electrical_grid=gpd.read_file('/content/electrical_grid.csv',\n",
        "                              GEOM_POSSIBLE_NAMES='location',\n",
        "                              KEEP_GEOM_COLUMNS='NO')\n",
        "\n",
        "grid=gpd.read_file('/content/drive/MyDrive/TID_Innovation/Data/modelled_grid_original.csv',\n",
        "                   GEOM_POSSIBLE_NAMES='geom',\n",
        "                        KEEP_GEOM_COLUMNS='NO')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 137,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "7sN2eCpV-JlR",
        "outputId": "cfd34509-46c5-4ac0-b059-00325280955c"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 137
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "data=data[data.iso=='nga']\n",
        "# print('Original CRS:', data.crs)                                                \n",
        "data.plot()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 138,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "Tl1kwaFtKdlk",
        "outputId": "41d629d0-83cf-44d5-ba09-0507fc55b540"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 138
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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SiRiG4am/iNFoVCUlJWppaVFxcbHbw4GHBKGWGO4I0u9OEBrkIH1WYiIBHb6QqKmG+WeMGQpSIRDCj6zERJLi4HlBqSWGu8x8DyCoLO+hb9iwQTNnzlRlZaUikYhefPHFHs8bhqGHHnpIFRUVGjBggKZOnaodO3bYNV6EUK5riY+fjOlXG/+ih17aql9t/IuOn4zZ8rphQI4D4B7LM/SjR4/q/PPP1+23367rr7++z/OPPfaYnnjiCT3zzDOqqqrSokWLdNVVV6mhoUH9+3u7NATelMta4mW1DarZ2KjucWhJ7UeaN6VKC2dUZ/36QRakfWrAjywH9KuvvlpXX3113OcMw9DPf/5z/ehHP9KsWbMkSb/5zW80dOhQvfjii7rpppuyGy1CKVe1xMtqG/T0hsY+j8cMdT1OUI+Pg0MA99lattbY2Kjm5mZNnTq167GSkhJ95StfUV1dXdzvaW9vVzQa7fEf0F0uaomPn4ypZmPfYN5dzcZGlt/j4OAQwBtsDejNzc2SpKFDh/Z4fOjQoV3P9bZs2TKVlJR0/Td8+HA7h4QAyEUt8aq6XUoVb2JG53XoKSj90gG/c72xzMKFC9XS0tL13+7du90ekqd1TzrauO1vqtkQjuQtp5tqNB1qtfW6MAlKv3TA72wtWysvL5ck7d+/XxUVp/7A7t+/XxMnToz7PUVFRSoqKrJzGIEVL+mou6AnbznZO35k6UBbrwuToPRLB/zO1hl6VVWVysvL9frrr3c9Fo1G9fbbb2vy5Ml2vlXomElHyZY2zeStZbUNORxZbjnVO37O5FFK9VJ5kc7r0JOZ45DKZ0fbczAaILwsB/TPP/9cW7Zs0ZYtWyR1JsJt2bJFn3zyiSKRiO6++2795Cc/0csvv6wPP/xQt956qyorK3XdddfZPPTwSJZ0FA/JW9YVFuRp3pSqpNfMm1KlwgLXd6k8Jz8vokXXpF4VevQPH5EYBzjI8pL7O++8oyuuuKLr63vvvVeSNHfuXP3Hf/yHfvCDH+jo0aP69re/rcOHD+vSSy/V2rVrqUHPQqqko97M5K1vTTnLwVEFj7lV0bsOPS+iQG9l2OH0QYUprzET4+jWBjjDckC//PLLlaz9eyQS0Y9//GP9+Mc/zmpgOCWTZCKStzKzcEa17vv6WK2q26WmQ60aWTpQcyaPYmaewr9v3JnWdSTGAc6hl7sPZJJMRPJW5goL8ljdsOD4yZjWf/y3tK4lMQ5wDtMOH0jVWKU3kreQS6vqdqWV31HcvyCr5j8AkiOg+0CyxirxkLwVHH447CTd7Z0LRpzOaXiAg1hy9wmzsUqyOnSSt4LFL4edpLu9c9mYMxweCRBuESNZhpsLrBzmHkYdMaOrsUrpgEJ9vP+Idn9G8lYq3e+bnQ1pnJLosBNzxHYddmLHfTl+Mqaxi15N2jo3LyJ9/OjV/H4CFlmJiczQfcZsrGKa8qUvujgaf/DLTNeU6rCTiDoPO5lWXZ7VhxK77otZwx/vpDoT20CA8/gXhkBL1GHPPNZz7dZ9Lo0ssVwcdmL3fVk4o1rfuayqT7e9SET6xnkV+sH0czMeK4D0ENARWH491tPpw06cui8LZ1Tr40ev1jcnDdPAfvmdr2dIr3ywT5cuX+/JD09AkBDQEVh+PdbT6cNOnLwv6z/er/9Tv0etJzp6PO7lFREgKAjoCCy/HuuZqu9ARJ173ZnWdDt1X/y6IgIEBQEdgeXXYz2T9R0wv354ZnXGCXFO3Re/rogAQUFAR2A5PdN1ktl3oLzXsaTlJf2zLllz6r681tCc1nVeWxEBgoKyNQSWOdO9c3W9IlKPpWA7ZrpOmz6+QtOqy22vn8/2vpi1680tx3To6HGVfqFIQ75QpOff25PW+3ttRQQIChrLIPD8VoeeK5ncl3jfY0XZoEJt+uFUz36IAryGxjJAN07NdP3O6n1J1L3OilkTKzO6737r9Ae4gYCOUOjdYQ+d0r0vyTLYrZhWXW75e1hhAdJDUhyAlFJlsKcjk0Q7P3b6A9xCQAeQUjaZ6ZG//2c1AZG69uDyw7HAfsSSO4CUsslML89wedxKXTvbKf7BFopzCOgAUjJr11Mtu0ckDS0u0r/eOFGfft6eVQKbXzv9IbFEiZXmFopdxwKHFUvugI2CupRo1q6nE5YfuXacLjn7DM2aOEyTR5d5rqMd3MEWivOYoQcYpT65FfSlRLN7XaI6dLt/VnNVoLmlLW4QiKhzOd+Lnf7QF1soziOgB1TtB/v0o5e26tDR412P+SW4+PGDSFiWErvXrnfvFFdebP//T37v9Iee2EJxHgE9gJbVNujpDY19Ht/ng+Dix1luqqXEiDqXEqdVl3cFn+MnY1pVt0tNh1o1snSg5kwepcICf+yA5bKmP9GqQKaJdnAPWyjOI6AHTO0He+MGc5OhvsHFK/w6y7W6lListkE1GxvVfavwJ7Uf6b9dWqUfXlPt/IB9hk5/wcAWivP8MSVAWjpihn700taU13nxCEs/J8xYWUo0V096/xiGIdVsbNS832x2YIT+Z64KZJtoB/c4fSwwCOiBsqnxkA4dPZHWtV7bp/LzWdrpLhGWDixUzcbEqyeStK7hgF7Zkt6pZYDfOHksMFhyDxQrQdpr+1R+TphJdynx4+Zon5l5PAtf/FBXn5fZISaA17GF4hxm6AGSbpAuG1TouX0qPyfMpLuUuPuzY2m93pG2Dk+uRAB2YQvFGQT0ADFniqk8Omu85/4BmWNPNKqIMjvcw0ndm8iUDCjUk/81+VJia/vJtF/biysR8I+gNjhCciy5B0j3ut1E/3y/c1mVZpznvX0qv9UcJyqvW3TNuTp9UFGfpcSOmKGNO/6W9ut7cSUC/uDH0k/Ygxl6wJhJJ71n6qWD+ul//NcLtHCGd8ui/JIwk+xIz+89+55ajh3vs5S4qfGQ9h85Hu/l+siLSP9l5Om2jxvBx3Gz4cYMPYD8nHTi9bFn0kRGsraEHjOkd5s+y2n7Sz9250NPmf5uIjgI6AGVy25edvPy2DPtR211CT2Xe+gs0QYDvdLBkjtgQabldekmLJpytYfOEm1w+Ln0E/YgoAMWZFpe1720LZl0svntymD2c3c+9OXn0k/YgyV3wIJs+lFPH1+hp26ZpAee/1CHW/t29Esnm9/O5XGWaIOFXulghg5YkG0/6unjK/Tuj6bpnqnn6LQB/Xo8lyqb3+7lcZZog4Ve6WCGDliU7ZGe+XkRzZ86Rt+/8uy0M8udyGBmiTZ4OG423AjoQAbsKK+zks3vxPI4S7TB5PXSTziHgA5kKJfldU4sj/utOx/S5+XSTziHPXTAB5xaHvdLdz4AqTFDB3zAyeVxlmiBYCCgAz7g9PI4S7SA/7HkDvgEy+MAkmGGDvgIy+MAEiGgAz7D8jiAeFhyBwAgAAjoAAAEAAEdAIAAIKADABAABHQAAAKAgA4AQAAQ0AEACAACOgAAAUBABwAgAAjoAAAEAAEdAIAAIKADABAABHQAAAKA09YCoiNmcKQmAIQYAT0A1m7dp8VrGrSvpa3rsYqS/np4ZrWmj69I6zX4QAAA/kZA97m1W/fpztX1Mno93tzSpjtX12vFLZNSBnU7PhAAANzFHrqPdcQMLV7T0CeYS+p6bPGaBnXE4l3RyfxA0D2YS6c+EKzdus++AQMAHENA97FNjYf6BOLuDEn7Wtq0qfFQ3Oft+EAAAPAGArqPHTiSOJinc122HwgAAN5BQPexIYP7Z3Vdth8IAADeQUD3sYuqSlVR0l+JctEj6kxuu6iqNO7z2X4gAAB4h+0BvaOjQ4sWLVJVVZUGDBig0aNH69FHH5Vh+HMftiNmqG7nQb20ZY/qdh701H5yfl5ED8+slqQ+Qd38+uGZ1QnLz7L9QAAA8A7by9aWL1+uFStW6JlnntG4ceP0zjvv6LbbblNJSYnuuusuu9/OUX4o55o+vkIrbpnUZ5zlaYzT/EBw5+p6RaQeyXHpfCAAAHhHxLB56vyNb3xDQ4cO1a9+9auux/7pn/5JAwYM0OrVq1N+fzQaVUlJiVpaWlRcXGzn0CxJVN9thrZ06rtzKZvGMH744AIAYWQlJto+Q7/44ou1cuVKbd++Xeecc47ef/99vfnmm3r88cfjXt/e3q729vaur6PRqN1DsixVOVdEneVc06rLPTN7zc+LaPLosoy+d/r4Ck2rLqdTHAD4mO0B/YEHHlA0GtXYsWOVn5+vjo4OLVmyRDfffHPc65ctW6bFixfbPYysWCnnyjSIek02HwgAAO6zPSnu97//vX7729/q2WefVX19vZ555hn9y7/8i5555pm41y9cuFAtLS1d/+3evdvuIVlGORcAwG9sn6Hff//9euCBB3TTTTdJkiZMmKCmpiYtW7ZMc+fO7XN9UVGRioqK7B5GVijnCjYOogEQRLYH9NbWVuXl9Zz45+fnKxaL2f1WjjHLuZpb2uLuo0fUmUXuVjkXASlzJAACCCrbA/rMmTO1ZMkSjRgxQuPGjdN7772nxx9/XLfffrvdb+UYL5dzEZAyZ8fJdADgVbaXrR05ckSLFi3SCy+8oAMHDqiyslKzZ8/WQw89pMLCwpTf75WyNcl7wdNvpXRe0hEzdOny9QmTHc1VlzcXXMlqBwDPsBITbQ/o2fJSQJe8s7xNQMpO3c6Dml3zVsrrnpv3VbL9AXiGq3XoQeOVcq4wltLZicoFAEHH4Sw+QUDKDpULAIKOgO4TBKTscBANgKAjoLsgkxPcCEiJpXM/sz2ZLsy8fOIggFPYQ8+xTDPnvVxK5yYr9zObk+nCymuVHgASI8s9h+woO+MP7CmZ3k+vVC54HWWSgPsoW/MgO8vOwh6QOmKG3tp5UN97tl6Hj52Ie0069zPs9zEZyiQBb6BszYPsLDvzSimdG+KtUMST6n6y0pEcZZKA/5AUlyPZlp2RmHRqCThVMO8u3v1M9DpmC9i1W/dlPVa/o0wS8B9m6DmSTdkZs8nODzSL1zTEPSwnmd73M9nrGOpcSl68pkHTqstDvZRMmSTgP8zQbZJqBp1p2RmzyU6ploB7S3Q/rSwlhxllkoD/MEO3QToz6EzKzphNnmJlaTdZGd+/b9xp+/sFEWWSgP8wQ8+SlRm0WQddXtJzmbK8pH/cEiBmk6dYWdpNdD+Pn4xp/cd/s/39gsrq7ysAdzFDz0ImM+jp4ys0rbo8rXIpEpNOMZeAm1vaEu6jnzagn568eZK+elZZ3Pu5qm5XWnvwxf0LWEr+Oyu/rwDcRUDPQqalPemWnZGYdEo6S8A//acJuuTsMxK+RtOh1rTe64IRpxOwuglzmSTgJyy5Z2FJbUNa12U6gyYxqadUS8DTqsuTJiaOLB2Y1vtcNibxhwIA8Cpm6Bk6drxDW/dE07o20xk0iUl9JVoCXtfQ3KezWe/ExDmTR2lJ7UdKVsKfF+m8DgD8hhl6hpamOTsfWJif1QyaxKS+zCXgWROHafLoMq1raE4rMbGwIE/zplQlfe15U6pUWMA/CwD+www9Q7sOprcfO7JsYNYzaBKTErOamLhwRucRqjUbG3vM1PMincHcfB4A/IaAnqFRZQO1cUfq6y4cebot70diUnyZJCYunFGt+74+VqvqdqnpUKtGlg7UnMmjmJkD8DUCeoYenFGtVW99ktZ1cE6mpX2FBXn61pSznBgSALiCKUmGBhTma1r1kKTXTKseogGF+TkaUThR2gcAnQjoWai59csJg/q06iGqufXLOR5R+FDaBwCdQrnk3hEztKnxkJpbjunQ0eMq/UKRyoszSzSrufXLOna8Q0trG7TrYKtGlQ3UgzOqmZnnCKV9ANApYhiGpw7WjkajKikpUUtLi4qLi21//XgHqZjCdiRpkHDELIAgshITQxXQzYNUkv3AESlQ9d3makQYyt3C9LMCCAcrMTE0S+7J6pV7C8qRpGGbtVLaByDMQpMUl6pe2RSUI0mtHOsKAPC/0AR0qwek+PlI0lTd06TOVYjeh5cAAPwrNAHdah2yn+uWrXRPAwAEQ2gCulmvnEoQ6pYz7Z4GAPCv0AR0s145nTQ3v9ct0z0NAMInNAFd6jy17InZF2hw//jJ/RUBOZKU7mkAED6hKVuTpGW1DX2OzZSkK750hr592dmBqVume5p3USsPwCmhCejLahv09IbGuM+9se1TnTN0cKBqmKePr9CKWyb1qUMvD3AduteFrS8AgNwKRae44ydjGrvo1T4z8+7yItLHj14duDOxmRF6Q6Iuheb/E0HY6gFgPysxMVjRK4FVdbuSBnNJihmd1wWN2T1t1sRhmjy6jGDuAvoCAMiFUAT0pkOtaV/XETNUt/OgXtqyR3U7D/JHFlmjLwCAXAjFHvrI0oFpXdfaflKX/HS9mqPd9pyL++uRa72/xxmWpXU//pz0BQCQC6EI6HMmj9KS2o+SLrtHJP3v+j19Hm+OtumO1fV6ysN7nGFJtvLrz0lfAAC5EIol98KCPM2bUpX0moL85LO8+/7X+/rPHZ96bik+LIew+PnnpC8AgFwIfEA398RPdCQPwKmeP9reoZt/9bbm/26LZte8pUuXr3c9iIQl2crvP6fZF0BSn6BOXwAAdgl0QF+7dZ8uXb5es2ve0v/8z122vrYXZoZhSbYKws9p9gUo73WeQHlAuhMCcF9g99AT1f3axVDn7GrxmgZNqy53ZXYVlmSroPyc08dXaFp1ue+S+gD4QyADerIlWjt1nxm60WUuLMlWQfo5zb4AAGC3QC65p1qitZtbM8OwJFuF5edMhR4JAJIJ5Aw91wHWrZlhWA5hCcvPmYxfS/YA5E4gZ+i5CrBemBmGJdkqLD9nPH4u2QOQO4GcoZtLtLlYdvfCzDAsyVZh+Tm7S1Wy53ZiJgDvCGRAN5do71hd7+j73D31HM/MDMOSbBXEnzNZO1srJXtBuy8ArAlkQJc6Z3O/nH2B/vtz7zn2HqPOSK9HPGDqHbw/O3pcj/4h8d54UEr2ADgvsAFdkmaeX6kP/vqZajbucuT1/VAm5bZjxzu0tLZBuw62alTZQD04o1oDCvPdHpYr4iW2xWPuja+4ZVKgSvYAOCvQAV2SfnjNOOVFIlq5odHWunS3k+H8YN5vNmtdw4GurzfukFa99YmmVQ9Rza1fdnFkuWel0VH3drZ/vP8KVZT0V3NLW9zvjagzMZDfRQCBzHLvbeGMav1g+pdsfU0vJMN5We9g3t26hgOa95vNOR6RezJtdLSvpU3vNn2WUR94ataB8An8DN00vqLEtte6x0PJcF507HhHwmBuWtdwQMeOd4Ri+T2bRkfN0Tb94wXDtOKWSX2W68sT1KFTsw6EU2gC+qFjx215nfLiIn3/yrNtea2gWlrbkPZ1j143weHRuC+bhLVDn7dLSr9kL9HSfvd9eYI6EEyhCeh2JA1FJD1y7TiW2lN44+Pks3PTroOtDo/EG7L53SsdVNj1v1OV7FGzDoRbKPbQpdT9wFOpCEFHMjssq23QXw+nNyMdVRbcsr/ue9ixmKHy4sx+98pLBqR9bRCOmQWQudDM0JP1A0/lnqlj9P0rxzCrSeH4yZhqNjamff2DM6odHE1uxGsKs66huc8e9mkD+3XNktP93bNaSUHNOhBuoQno0ql+4L3/2JYO6qeJZ5Zoc9NhHWk72fU4iUTWrKrbpXSTqadVD/F9Qly85LPTBvbT4dYTfa5t+ftjJQme7y0i65UU1KwD4RaqgC4lTy5K1oITqTUdSm9P/MzTBniiDj2b/78TJZ8lCtbm7Lx/QZ5++9++ok8/b/97p7h2PfqHj2zJSDe3lahZB8IpdAFdSpxcFMQ+4bk0sjS9PfHbLhnl7EDSkE1pV6Z15Yak5mi78iIRzZo4rOvxq8ZX2PJBkmNmgXALTVIcnDdn8iilihV5kc7r3JTsONI7VtfrF69tT9qQJZu6cqnvHrb5QXLWxGGaPLosq4Ab5mNmgbAL5QwdzigsyNO8KVV6ekPixLh5U6pUWODe58hUpV2S9LPXdnQ9Fm/Wnm1SmdN72GE8ZhYAAR02W/j3zPWajY09EuTyIp3BfKHLme1WZ9fxGrJkGpBzuYfN9hEQPgR02G7hjGrd9/WxWlW3S02HWjWydKDmTB7l6szcZHV2Ha8hS6rks3jYwwbgNAI6HFFYkKdvTTnL7WH0kcnsuntDFnOPO1nymaG+5WuJ+q4DgF0I6AiVTGbXpu6z+0Q9DczAzR42gFxzJKDv2bNHCxYs0KuvvqrW1ladffbZ+vWvf60LL7zQibcD0pZNx8Des/tUyWfsYQPIJdsD+meffaZLLrlEV1xxhV599VV98Ytf1I4dO3T66afb/VZARhLNrhNJlsxG8hkAr7A9oC9fvlzDhw/Xr3/9667Hqqqq7H4b+ICXO+/1nl3v+rRVP39tuyQasgDwJ9sD+ssvv6yrrrpKN9xwg/74xz9q2LBh+u53v6t58+bFvb69vV3t7e1dX0ejUbuHBBdk04ktV3rPrr9U/oWEe+JeGTMAJBIxDMNqblBS/ft37jPee++9uuGGG7R582bNnz9fTz31lObOndvn+kceeUSLFy/u83hLS4uKi4vtHBpyJFGfc3N+6+WOZV5eVQAQPtFoVCUlJWnFRNsDemFhoS688EL96U9/6nrsrrvu0ubNm1VXV9fn+ngz9OHDhxPQfaojZujS5esT7k2b+9FvLriSQAkAKVgJ6LZ3+qioqFB1dc9uYOeee64++eSTuNcXFRWpuLi4x3/wr1Sd2LrXdAMA7GP7Hvoll1yibdu29Xhs+/btGjlypN1vBQ9KtxNbtv3Q/YRlfAC5YHtAv+eee3TxxRdr6dKluvHGG7Vp0yatXLlSK1eutPut4EHpdmJz+oASr/BDciCAYLB9D12SXnnlFS1cuFA7duxQVVWV7r333oRZ7r1Z2S+A95h76Ik6sYVpDz1VcuAvb5qo/UfaPdfvHoB3uJoUly0Cuv+ZgUyKX9PtVpZ7Lpe+UyUHxuOVE+kAeIeVmEgvd9guVZ9zN4J5rpe+rR7TKkkxQ11nyRPUAVjFDB2O8UoymBt18S9t2aP5v9uS0ffmRaSPH72a5XcA7patASazE9usicO6jh3NtY6YocVrGuLu55uPLV7ToI6YvZ9rs0n6ixnSqrpd9g0GQCgQ0BFobtXFm8e0ZvoRpulQq63jARB8BHQEmlt18eYxrZIyCuojSwfaOh4AwUdAR851xAzV7Tyol7bsUd3Og7Yvd3eX7tL3GV8osn1MZnJgeYm15fe8iDRn8qis3x9AuJDljpyKl20+dHChpoz5ogYWFdhej20ufSeriz9tYD/d9/stao6eOlPArgz43se0DhncX+s/3q+ajY0Jv2felCoS4gBYRpY7ciZRtnlvdtdjJ6uLTzQWJzPgO2KG5v/uPf3hg3093p86dAC9UYcOz0mWbd6b3fXYyerij53o0OHWE32+x1BnUF+8pkHTqsv7ZOgfPxnTqrpdlru8xVuhGNgvXzMmlGvp9ecxMweQMWboyIm6nQc1u+YtS99jdz1277r4WMzQzb96O+X3PTfvq5o8uqzr62W1DarZ2Kju2+zpzK79fE48AHdQhw7PySSL3O567N518Z8ebU/9Teo59mW1DXp6Q89gbo716Q2NWlbbEPc13KqHBxAeBHTkRKaNVpysx7Z6Mtzxk7GkyWySVLOxUcdPxvo8zjnxAJxGQEdOZNpoxcl67InDT9Pg/onTSCLqzHa/qKpUUudqQaoJdKJVBc6JB+A0AjpyIpNGK07WYy+rbdC4h9fqSNvJuM+bY3x4ZnVXQly6qwXxruOceABOI6AjZ6w2WnGqHjvRPnh35SX9+ySppbtaEO+6VCsUvVcDAMAqAjpyavr4Cr254Eo9N++r+sVNE/WN8yrU+8yWvIj0ncucqcdOZx88Imn9fZf3yTifM3lUn7H2lmhVIdkKRbzVAACwijp05JyZbS5JsyYOy7imOxPp7IMbkp59u0nfmnJWj8cLC/I0b0pVV418PMlWFbx4TjyA4CCgw3WFBXl9gqdTstkHl041usmkDl2K3wrWrXPiAQQLAR2hks0+uGnhjGrd9/WxGa8qdF+hAAC7ENARKnMmj9KS2o+SLrunk12fy1UFAEgHSXEIFXMfPJmgn3aWy+NrAeQOM3SETrb74LnQu++8Xfvs8Q6HseuoWADu4nAWhFYus+utcCrocjgM4D9WYiIBHciBdGfcTgXdjpihS5evT9hPPqLO8rk3F1xJxj3gIZyHDnhIujPuVCeyJTufPRUrh8OQgQ/4k/vri0CArXl/r+5YXd8nmDa3tOnO1fVau3Vf12NOnsiW7qEv+w4fs/zaALyBgA5f83LG9pI//D/99+fei/tcvDPQnTyRLd1DX+77X+8nPNMdgLex5A7fWrt1nx55uUHN0W5tVIv765Fr3c/YXlbboJqNu5Je03uZ28kT2czDYZpb2uIu6Xcfk9na1gvZ/gDSxwwdvrR26z7dsbq+RzCXpOZom+5YXa/aD/a6NLL0DoDpzpxxO3kim9Xja2s2Nur4yZjl9wHgHgI6fKcjZuiB5z9Mes33nntPtR/sS3qNU9I5AKY7c8bt9Ils5uEwX+ifemEuZnT+HAD8g4AO33nrLwd1uPVE0msMQ/rusz2TznIl3QNgpL4z7kRnxsc7nz0T08dXaNbEyrSutfJzAHAfe+jwnbqdB9O+NtMyr96sdG4bfnp6B8BI8WfcTp/IVlU2KK3r0j3IBoA3ENDhQ+mvZ9tRW22lc9varfv07xt3pvW6v5x9QcIZt5Mnstl1QA0Ab2HJHb4z+awzLF2fSZmXyezcFq+O/I7V9frFa9u7SuZqP+i8dv+R4ylfd96UUZp5fnpL33bjgBogmJihw3e+OrpMpw3sl3If3ZRJmZeUunObJP3stR1dj+VFUq8deOUAGD8cUAPAGgI6fCc/L6KfXj9Bd6yuT3qd2Z88kzIvKXXntt7SyWw//8xizwTLhTOqdd/Xx3rygBoA1hHQ4UvTx1foqVsm6YH/84EOHzvZ53k7yryyWapP5L3dUR073qEBhfm2v3YmCgvy9K0pZ7k9DAA24KM4fGv6+Aq9u+jrumfqOTptQL8ez9lR5pXpUn0qS2mtCsABzNDha/l5Ec2fOkbfv/Js28u80m2XatWug9R3A7AfAR2B4ESZl9m57c7V9YrISrFccqPKqO8GYD+W3IEkEnVuy8aDHkmKAxAszNCBFHp3btu4/W/63/V7MnqtqecOsTUhzkoHOwDBRkAH0tB7ST+TgH7emcX697lftm1MVjrYAQg+ltwBi6xmvxfmSU/ceL5e/v4U28aQrIPdnavdOZQGgLuYoQMWmdnv6TSdKR3UT28tnJqyWcux4x1aWtugXQdbNapsoB6cUZ1waT5VB7uI7DuUBoB/ENABi7pnvyfLfI9IWvqPE1IG83m/2ax1DQe6vt64Q1r11ieaVj1ENbf2XaJP1cHOkD2H0gDwF5bcgQyY2e8VCbLfK9JsbNM7mHe3ruGA5v1mc5/H0+1g50SnOwDexQwdyFD37PfmlmM6dPS4Sr9QpPLi9LLNjx3vSBjMTesaDvRpFZvuHr5Tne4AeBMBHchCNg1t0m0Bu7S2QY9eN6Hr61Qd7LI9lAaAP7HkDrgk3Rawva8z9/ClU4fQmOw4lAaAPxHQAZek2wI23nWJOtjZcSgNAH+KGIZh57kTWYtGoyopKVFLS4uKi4vdHg7gmGPHO3TuQ2tTXvfRj6cnLWGjUxwQXFZiInvogEsGFOZrWvWQpIlx06qTt4p14lAaAP7Ekjvgoppbv6xp1UPiPpeoDh0A4mGGDris5tYvW+oUBwDxENABDxhQmN+jNA0ArGLJHQCAACCgAwAQAAR0AAACgIAOAEAAENABAAgAAjoAAAFAQAcAIAAI6AAABAABHQCAAPBcpzjz8LdoNOrySAAAcJcZC9M5GNVzAf3IkSOSpOHDh7s8EgAAvOHIkSMqKSlJeo3nzkOPxWLau3evBg8erEjE/+c6R6NRDR8+XLt37+Z8dwu4b5nhvmWG+2Yd9ywzVu+bYRg6cuSIKisrlZeXfJfcczP0vLw8nXnmmW4Pw3bFxcX80meA+5YZ7ltmuG/Wcc8yY+W+pZqZm0iKAwAgAAjoAAAEAAHdYUVFRXr44YdVVFTk9lB8hfuWGe5bZrhv1nHPMuPkffNcUhwAALCOGToAAAFAQAcAIAAI6AAABAABHQCAACCg58BPf/pTRSIR3X333W4PxfP27NmjW265RWVlZRowYIAmTJigd955x+1heVpHR4cWLVqkqqoqDRgwQKNHj9ajjz6aVu/nMNmwYYNmzpypyspKRSIRvfjiiz2eNwxDDz30kCoqKjRgwABNnTpVO3bscGewHpLsvp04cUILFizQhAkTNGjQIFVWVurWW2/V3r173RuwR6T6fevujjvuUCQS0c9//vOs3pOA7rDNmzfr6aef1nnnnef2UDzvs88+0yWXXKJ+/frp1VdfVUNDg/71X/9Vp59+uttD87Tly5drxYoV+rd/+zd99NFHWr58uR577DH98pe/dHtonnL06FGdf/75evLJJ+M+/9hjj+mJJ57QU089pbfffluDBg3SVVddpba2thyP1FuS3bfW1lbV19dr0aJFqq+v1/PPP69t27bp2muvdWGk3pLq9830wgsv6K233lJlZWX2b2rAMUeOHDHGjBljrFu3zviHf/gHY/78+W4PydMWLFhgXHrppW4Pw3euueYa4/bbb+/x2PXXX2/cfPPNLo3I+yQZL7zwQtfXsVjMKC8vN/75n/+567HDhw8bRUVFxnPPPefCCL2p932LZ9OmTYYko6mpKTeD8oFE9+2vf/2rMWzYMGPr1q3GyJEjjZ/97GdZvQ8zdAd973vf0zXXXKOpU6e6PRRfePnll3XhhRfqhhtu0JAhQ3TBBReopqbG7WF53sUXX6zXX39d27dvlyS9//77evPNN3X11Ve7PDL/aGxsVHNzc49/qyUlJfrKV76iuro6F0fmPy0tLYpEIjrttNPcHoqnxWIxzZkzR/fff7/GjRtny2t67nCWoPjd736n+vp6bd682e2h+MZf/vIXrVixQvfee68efPBBbd68WXfddZcKCws1d+5ct4fnWQ888ICi0ajGjh2r/Px8dXR0aMmSJbr55pvdHppvNDc3S5KGDh3a4/GhQ4d2PYfU2tratGDBAs2ePZsDW1JYvny5CgoKdNddd9n2mgR0B+zevVvz58/XunXr1L9/f7eH4xuxWEwXXnihli5dKkm64IILtHXrVj311FME9CR+//vf67e//a2effZZjRs3Tlu2bNHdd9+tyspK7hty5sSJE7rxxhtlGIZWrFjh9nA87d1339UvfvEL1dfX23pMOEvuDnj33Xd14MABTZo0SQUFBSooKNAf//hHPfHEEyooKFBHR4fbQ/SkiooKVVdX93js3HPP1SeffOLSiPzh/vvv1wMPPKCbbrpJEyZM0Jw5c3TPPfdo2bJlbg/NN8rLyyVJ+/fv7/H4/v37u55DYmYwb2pq0rp165idp7Bx40YdOHBAI0aM6IoRTU1Nuu+++zRq1KiMX5cZugO+9rWv6cMPP+zx2G233aaxY8dqwYIFys/Pd2lk3nbJJZdo27ZtPR7bvn27Ro4c6dKI/KG1tVV5eT0/m+fn5ysWi7k0Iv+pqqpSeXm5Xn/9dU2cOFGSFI1G9fbbb+vOO+90d3AeZwbzHTt26I033lBZWZnbQ/K8OXPm9MmtuuqqqzRnzhzddtttGb8uAd0BgwcP1vjx43s8NmjQIJWVlfV5HKfcc889uvjii7V06VLdeOON2rRpk1auXKmVK1e6PTRPmzlzppYsWaIRI0Zo3Lhxeu+99/T444/r9ttvd3tonvL555/rz3/+c9fXjY2N2rJli0pLSzVixAjdfffd+slPfqIxY8aoqqpKixYtUmVlpa677jr3Bu0Bye5bRUWFvvnNb6q+vl6vvPKKOjo6unIOSktLVVhY6NawXZfq9633B59+/fqpvLxcX/rSlzJ/06xy5JE2ytbSs2bNGmP8+PFGUVGRMXbsWGPlypVuD8nzotGoMX/+fGPEiBFG//79jbPOOsv44Q9/aLS3t7s9NE954403DEl9/ps7d65hGJ2la4sWLTKGDh1qFBUVGV/72teMbdu2uTtoD0h23xobG+M+J8l444033B66q1L9vvVmR9kax6cCABAAJMUBABAABHQAAAKAgA4AQAAQ0AEACAACOgAAAUBABwAgAAjoAAAEAAEdAIAAIKADABAABHQAAAKAgA4AQAAQ0AEACID/D1NhDMFh9cQrAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# print('Original CRS:', transmission_substations.crs)                                                \n",
        "# print(transmission_substations.head())\n",
        "transmission_substations.set_crs(\"EPSG:3857\",inplace=True)\n",
        "# print('New CRS:', transmission_substations.crs)                                                \n",
        "# print(transmission_substations.head())\n",
        "transmission_substations.to_crs(\"EPSG:4326\",inplace=True)\n",
        "# print(transmission_substations.head())\n",
        "transmission_substations.plot()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "electrical_grid.set_crs('EPSG:4326',inplace=True)\n",
        "electrical_grid.plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "q13IG7QYfDoy",
        "outputId": "05234292-1c44-4f62-ebaf-f94e79b0802d"
      },
      "execution_count": 139,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 139
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 140,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "Cek9mrorAhup",
        "outputId": "010ba0c6-ffc5-4ddd-9f32-0ef1315c4638"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 140
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# print(state_boundaries.crs)\n",
        "# print(state_boundaries.head())\n",
        "state_boundaries.set_crs(\"EPSG:3857\",inplace=True)\n",
        "# print(state_boundaries.crs)\n",
        "# print(state_boundaries.head())\n",
        "state_boundaries.to_crs(\"EPSG:4326\",inplace=True)\n",
        "# print(state_boundaries.crs)\n",
        "# print(state_boundaries.head())\n",
        "state_boundaries.plot()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 141,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "I9cpn3WsAymn",
        "outputId": "dde77e1f-2668-4e9e-89e2-ee7cfc5f5ebd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 141
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# print(power_plants.crs)\n",
        "# print(power_plants.head())\n",
        "power_plants.set_crs(\"EPSG:3857\",inplace=True)\n",
        "# print(power_plants.crs)\n",
        "# print(power_plants.head())\n",
        "power_plants.to_crs(\"EPSG:4326\",inplace=True)\n",
        "# print(power_plants.crs)\n",
        "# print(power_plants.head())\n",
        "power_plants.plot()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 142,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "AxHkP-arBAGo",
        "outputId": "c778a109-f036-45bc-fabf-d943ab8f8061"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 142
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# print('Original CRS:', transmission_lines.crs)\n",
        "transmission_lines.set_crs(\"EPSG:4326\",inplace=True)                                                \n",
        "# print('Original CRS:', transmission_lines.crs)\n",
        "transmission_lines.plot()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# print('Original CRS:', grid.crs)                                                \n",
        "# print(grid.head())\n",
        "grid.set_crs(\"EPSG:3857\",inplace=True)\n",
        "# print('New CRS:', grid.crs)                                                \n",
        "# print(grid.head())\n",
        "grid.to_crs(\"EPSG:4326\",inplace=True)\n",
        "# print(grid.head())\n",
        "grid.plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5iFJLgmfr3YF",
        "outputId": "a2228be3-49fb-450f-c325-511da5f44de1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 143
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P7vJ90gSGSJk"
      },
      "source": [
        "#  Final Map                                                "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "c5z0DX3pN7R_"
      },
      "outputs": [],
      "source": [
        "fig,ax=plt.subplots(figsize=(15,15))\n",
        "\n",
        "state_boundaries.plot(ax=ax)\n",
        "power_plants.plot(ax=ax, color='red', markersize=30,marker='D',label='Power Plants')\n",
        "transmission_substations.plot(ax=ax, color='black',markersize=20,label='Transmission Substations')\n",
        "grid.plot(ax=ax,label='Electricity Grid Line',linewidth=1,color='yellow')\n",
        "# transmission_lines.plot(ax=ax,color='green',linewidth=0.5,label='Electricity Grid Line')\n",
        "# lines=electrical_grid.plot(ax=ax,color='yellow',label='testing',linewidth=0.4)\n",
        "# lines.set_linewidth(0.01)\n",
        "\n",
        "plt.title('Electrical Connectivity Map Of Nigeria')\n",
        "plt.legend()                                         \n",
        "plt.grid(True, which='minor', linestyle='-', color='yellow', alpha=0.5)\n",
        "plt.grid(True, which='major', linestyle='-', color='black', alpha=0.5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GCUF-qPOxeAf"
      },
      "outputs": [],
      "source": [
        "minigrids.plot()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Population_Data"
      ],
      "metadata": {
        "id": "FTX0RJU2diLs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "state_lga_df=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/States&LGA/Nigeria states and population.csv')\n",
        "state_lga_df=state_lga_df.iloc[0:769,0:3]\n",
        "state_lga_df"
      ],
      "metadata": {
        "id": "zBnIbdv4Uz-z"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "wards_lga_csv=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/States&LGA/Nigeria_Wards_Lat-Long.csv')\n",
        "# wards_lga_csv\n",
        "wards_lga_csv['location']=wards_lga_csv.apply(lambda x: Point((x['Longitude'],x['Latitude'])),axis=1)                                                \n",
        "wards_lga_csv.to_csv('wards_lga_csv.csv')\n",
        "wards_lga=gpd.read_file('/content/wards_lga_csv.csv',\n",
        "                              GEOM_POSSIBLE_NAMES='location',\n",
        "                              KEEP_GEOM_COLUMNS='NO')"
      ],
      "metadata": {
        "id": "X9qp7rOzD7UV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "wards_lga_csv"
      ],
      "metadata": {
        "id": "KiB5wA7fUnDM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# fig,ax=plt.subplots(figsize=(12,12))\n",
        "# state_boundaries.plot(ax=ax)\n",
        "# wards_lga.plot(ax=ax,color='red')"
      ],
      "metadata": {
        "id": "xuFOtgQ_dpdM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# electricity_supply"
      ],
      "metadata": {
        "id": "itttA2G5e6a7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "solcast_index=pd.read_csv('/content/drive/MyDrive/TID_Innovation/Data/Solcast/solcast_index.csv')"
      ],
      "metadata": {
        "id": "X3jcyYc1fAlw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "linklist=['/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/0_9.218209_9.517949/9.218209_9.517949_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/1_6.914868_5.147814/6.914868_5.147814_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/2_8.499791_8.199694/8.499791_8.199694_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/3_9.326475_12.398385/9.326475_12.398385_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/4_6.264923_8.01373/6.264923_8.01373_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/5_12.122181_6.223582/12.122181_6.223582_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/6_12.228012_9.561587/12.228012_9.561587_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/7_12.379671_7.630575/12.379671_7.630575_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/8_13.053314_5.322272/13.053314_5.322272_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/9_11.4942_4.233335/11.4942_4.233335_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/10_10.363779_11.192759/10.363779_11.192759_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/11_11.884636_13.151967/11.884636_13.151967_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/12_7.999362_10.773986/7.999362_10.773986_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/13_11.74707_8.524711/11.74707_8.524711_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/14_10.501518_7.44084/10.501518_7.44084_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/15_7.336902_8.740369/7.336902_8.740369_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/16_5.572012_7.058822/5.572012_7.058822_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/17_10.776062_9.999194/10.776062_9.999194_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/18_9.930922_5.598321/9.930922_5.598321_Solcast_PT60M.csv',\n",
        "          '/content/drive/MyDrive/TID_Innovation/Data/Solcast/Time_Series_4632b303-484b-4395-a713-4116b250ba35_Solcast_PT60M/19_12.293876_11.439041/12.293876_11.439041_Solcast_PT60M.csv']"
      ],
      "metadata": {
        "id": "nFLRTgwE9zaU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_irradiance(state,csv_path):\n",
        "  state=pd.read_csv(csv_path)\n",
        "  state[['date','start_time']]=state['PeriodStart'].str.split('T',expand=True)\n",
        "  daily_irradiance=state.groupby('date').sum()[['Ghi','GtiFixedTilt','GtiTracking']]\n",
        "  return(list(round(daily_irradiance.mean()/1000,2)))\n",
        "  # avg_daily_irriadiance=list(zip(list(daily_irradiance.columns),round(daily_irradiance.mean()/1000,2)))\n",
        "  # return(avg_daily_irradiance)                                                 "
      ],
      "metadata": {
        "id": "2Fzlzrsq6ZIG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "irradiance_list=[]\n",
        "for index,link in enumerate(linklist):\n",
        "  state=solcast_index.loc[index,'State']\n",
        "  irradiance_list.append(get_irradiance(state,link))\n",
        "  # irradiance_list.append(get_irradiance(state,link))"
      ],
      "metadata": {
        "id": "gissThm28-lz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Ghi=[item[0] for item in irradiance_list]\n",
        "GtiFixedTilt=[item[1] for item in irradiance_list]\n",
        "GtiTracking=[item[2] for item in irradiance_list]\n",
        "state=list(solcast_index.State)\n",
        "df_dict={'state':state,'ghi':Ghi,'gtifixed':GtiFixedTilt,'gtitracking':GtiTracking}\n",
        "avg_daily_irradiance_2022=pd.DataFrame(df_dict)\n",
        "avg_daily_irradiance_2022"
      ],
      "metadata": {
        "id": "ZCz_ud8cEI2a"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [
        "Qm-1NYePB3qz",
        "hWkywFjiCFLq",
        "F0brLTdEHJEQ",
        "P7vJ90gSGSJk",
        "FTX0RJU2diLs"
      ],
      "provenance": [],
      "mount_file_id": "1dGMc43ibxORghWMmtFQVTUPWY20KYThA",
      "authorship_tag": "ABX9TyOnXTgngCyA54QP6uih8Tie",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}