cobertura_final.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "mount_file_id": "1vaCBCJslojznyyUan8Nfii9RpBN95qt2",
      "authorship_tag": "ABX9TyP3VQ3wllSDLy8oSORLsWuQ",
      "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/JorgeICS/Primeos_Analisis_Geopandas/blob/main/cobertura_final.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xz5Fski4prx8",
        "outputId": "c234f96e-5002-4470-87c9-b1055c9539c3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: geopandas in /usr/local/lib/python3.10/dist-packages (0.13.2)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (2.0.3)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (3.7.1)\n",
            "Requirement already satisfied: fiona>=1.8.19 in /usr/local/lib/python3.10/dist-packages (from geopandas) (1.9.6)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from geopandas) (24.1)\n",
            "Requirement already satisfied: pyproj>=3.0.1 in /usr/local/lib/python3.10/dist-packages (from geopandas) (3.6.1)\n",
            "Requirement already satisfied: shapely>=1.7.1 in /usr/local/lib/python3.10/dist-packages (from geopandas) (2.0.4)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas) (2023.4)\n",
            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas) (2024.1)\n",
            "Requirement already satisfied: numpy>=1.21.0 in /usr/local/lib/python3.10/dist-packages (from pandas) (1.25.2)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.2.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (4.53.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.4.5)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (3.1.2)\n",
            "Requirement already satisfied: attrs>=19.2.0 in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (23.2.0)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (2024.6.2)\n",
            "Requirement already satisfied: click~=8.0 in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (8.1.7)\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: six in /usr/local/lib/python3.10/dist-packages (from fiona>=1.8.19->geopandas) (1.16.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install  geopandas pandas matplotlib"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import geopandas as gpd\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "bSofsK4fpuh8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se cargan las agebs de México y se filtran solo las de Baja California"
      ],
      "metadata": {
        "id": "3K-LTmcJw7sx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs = gpd.read_file('/content/drive/MyDrive/MG_2020_Integrado/conjunto_de_datos/00a.shp')\n",
        "agebs_bc = agebs[agebs['CVE_ENT']=='02']\n",
        "agebs_bc.plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 481
        },
        "id": "GqbFT0nYpxqL",
        "outputId": "9506a1b2-6529-44a4-f43f-e9492e52d973"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 3
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_bc.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "Nf_K4T5Nqc5e",
        "outputId": "c7e80000-b699-4a22-cf22-2b6f7343b659"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            CVEGEO CVE_ENT CVE_MUN CVE_LOC CVE_AGEB  Ambito  \\\n",
              "479  0200102472200      02     001    0247     2200  Urbana   \n",
              "480  0200101399918      02     001    0139     9918  Urbana   \n",
              "481  020010001795A      02     001    0001     795A  Urbana   \n",
              "482  0200100011490      02     001    0001     1490  Urbana   \n",
              "483  0200102431819      02     001    0243     1819  Urbana   \n",
              "\n",
              "                                              geometry  \n",
              "479  POLYGON ((1106171.078 2273548.276, 1106181.991...  \n",
              "480  POLYGON ((1115824.070 2251960.119, 1115876.388...  \n",
              "481  POLYGON ((1115348.595 2267956.443, 1115347.288...  \n",
              "482  POLYGON ((1110338.345 2273510.431, 1110427.922...  \n",
              "483  POLYGON ((1141701.509 2206110.771, 1141638.155...  "
            ],
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              "      <th>CVEGEO</th>\n",
              "      <th>CVE_ENT</th>\n",
              "      <th>CVE_MUN</th>\n",
              "      <th>CVE_LOC</th>\n",
              "      <th>CVE_AGEB</th>\n",
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              "      <td>0247</td>\n",
              "      <td>2200</td>\n",
              "      <td>Urbana</td>\n",
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              "      <th>482</th>\n",
              "      <td>0200100011490</td>\n",
              "      <td>02</td>\n",
              "      <td>001</td>\n",
              "      <td>0001</td>\n",
              "      <td>1490</td>\n",
              "      <td>Urbana</td>\n",
              "      <td>POLYGON ((1110338.345 2273510.431, 1110427.922...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>483</th>\n",
              "      <td>0200102431819</td>\n",
              "      <td>02</td>\n",
              "      <td>001</td>\n",
              "      <td>0243</td>\n",
              "      <td>1819</td>\n",
              "      <td>Urbana</td>\n",
              "      <td>POLYGON ((1141701.509 2206110.771, 1141638.155...</td>\n",
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              "        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",
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              "      spin 1s steps(1) infinite;\n",
              "  }\n",
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              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "agebs_bc",
              "summary": "{\n  \"name\": \"agebs_bc\",\n  \"rows\": 2030,\n  \"fields\": [\n    {\n      \"column\": \"CVEGEO\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 2030,\n        \"samples\": [\n          \"0200400018803\",\n          \"0200400015372\",\n          \"0200301551349\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_ENT\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"02\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_MUN\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"001\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_LOC\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 44,\n        \"samples\": [\n          \"0585\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_AGEB\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 2030,\n        \"samples\": [\n          \"8803\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ambito\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Rural\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"geometry\",\n      \"properties\": {\n        \"dtype\": \"geometry\",\n        \"num_unique_values\": 2030,\n        \"samples\": [\n          \"POLYGON ((1095873.4243 2348819.9661, 1095812.9074999988 2348837.307500001, 1095788.9433000013 2348819.2795, 1095768.9548999965 2348819.4838999994, 1095749.887699999 2348818.0177000016, 1095727.2334999964 2348819.974300001, 1095713.9433000013 2348819.4866999984, 1095670.373499997 2348829.2313, 1095657.3410999998 2348831.967700001, 1095528.9777000025 2348840.600499999, 1095491.1963 2348837.107500002, 1095457.129900001 2348835.4886999987, 1095443.0539000034 2348828.9323000014, 1095425.063500002 2348825.1213000007, 1095413.2092999965 2348829.9891000018, 1095406.0261000022 2348835.7980999984, 1095399.8215000033 2348839.355700001, 1095392.201899998 2348841.6581000015, 1095383.844899997 2348843.892499998, 1095377.4378999993 2348845.3880999982, 1095373.3893000036 2348849.356899999, 1095363.4807000011 2348854.9869000018, 1095368.1563000008 2348862.649099998, 1095381.8012999967 2348887.1261, 1095388.2641000003 2348894.0700999983, 1095396.259499997 2348899.351300001, 1095359.250699997 2348907.5297, 1095358.7930999994 2348913.9345000014, 1095348.3043000028 2348960.219300002, 1095334.6665000021 2349015.4639, 1095271.2911000028 2349112.4459000006, 1095270.1793000028 2349126.2716999985, 1095270.4249000028 2349138.4329000004, 1095274.6743 2349154.7470999993, 1095286.4466999993 2349199.2217000015, 1095292.4877000004 2349208.2404999994, 1095298.7901000008 2349219.7710999995, 1095303.175499998 2349234.4241000004, 1095313.9100999981 2349255.2892999984, 1095329.867700003 2349318.8647000007, 1095364.4631000012 2349337.7773, 1095352.387500003 2349354.782499999, 1095330.6468999982 2349355.149099998, 1095352.3172999993 2349486.609099999, 1095352.2748999968 2349492.5779, 1095439.3747000024 2349437.5304999985, 1095926.6992999986 2349120.8561000004, 1095923.1662999988 2349078.4668999985, 1095917.6053000018 2349011.7441000007, 1095868.2652999982 2349019.910700001, 1095876.5980999991 2348993.5108999982, 1095876.5222999975 2348991.771899998, 1095876.2003000006 2348984.384300001, 1095878.0886999965 2348974.5632999986, 1095878.184299998 2348974.065299999, 1095882.1526999995 2348964.143100001, 1095881.3598999977 2348955.013700001, 1095878.925300002 2348945.6757000014, 1095877.4437000006 2348936.3621000014, 1095874.9034999982 2348927.2597000003, 1095870.0361000001 2348917.0989000015, 1095862.627700001 2348912.443500001, 1095873.4243 2348819.9661))\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_bc.crs"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mqxojDfrqCSU",
        "outputId": "20baff23-ec0f-474f-d6f7-4d2a6265276a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Projected CRS: PROJCS[\"MEXICO_ITRF_2008_LCC\",GEOGCS[\"MEXICO_ITRF_ ...>\n",
              "Name: MEXICO_ITRF_2008_LCC\n",
              "Axis Info [cartesian]:\n",
              "- [east]: Easting (metre)\n",
              "- [north]: Northing (metre)\n",
              "Area of Use:\n",
              "- undefined\n",
              "Coordinate Operation:\n",
              "- name: unnamed\n",
              "- method: Lambert Conic Conformal (2SP)\n",
              "Datum: International Terrestrial Reference Frame 2008\n",
              "- Ellipsoid: GRS 1980\n",
              "- Prime Meridian: Greenwich"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se carga el mapa de Cobertura"
      ],
      "metadata": {
        "id": "39adQFSsxeTF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cobertura_bc = gpd.read_file('/content/drive/MyDrive/Cobertura_Baja_California/COBERTURA/Baja Californiacoberturaunida124.shp')\n",
        "print(cobertura_bc.head())\n",
        "cobertura_bc.plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 574
        },
        "id": "zrhvxF4vqMf_",
        "outputId": "a0296812-6a80-43e6-8acc-64ceca272da1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "            estado      Periodo          Area  \\\n",
            "0  Baja California  1erTrim2024  1.327252e+10   \n",
            "\n",
            "                                            geometry  \n",
            "0  MULTIPOLYGON (((1077732.028 2319926.681, 10777...  \n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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M0cZypm5hFG2X5niAP3zLPAxVBkXnmsV1NMRmxijHyXRvtMZFa+R4nPNBctXCajRlfCc/n8qKhjBBDTSZiY5FQ5WJ+hRaKgw+csUCHv30ZVy/pJZ0wSZnuTTEIyxprKC9ujTLs+CU1p3csrIWv1Z6iUeyJjsHMvQm8xiKxOffsZjaqI+oTz1shqQkSdh26VtflmXOb6pgVUuCq5a3MJCX8PsN2ip9jOVNLptXyY0rW/nPD5w/cXvbcZEkj/esaefhT63jllUNYOZwHIf+sQy/eq0XkIj5VWRsLp9fhWEY1CQqqK+uJOw3GBlLMZi1GBwZ5unt3QR0jSWNMVY3x6iLTN239EZfGs91eP8FzTz/52+hMqghSfCO5TUTr8OZdDJnWL/ZNcz3X9g//Qdzljnzf90zrCKos7g+CoDjuozkbbpTFhnTmTi3Nx2XVNGhLaZimzZBTeEtC6tY1hAlETIwNBXP87h8USOL60qdu/1pi28+u29SX4LtQjJvs7g+QsGVyFs2qnr46MYjW/v49nMH37yW67K0McojbwyRHl/SUxX2c/GcauZUR9A0BUM7eD+mZdM7PMaGl1/jN9v7aYgaaIpMMmci4xEyVK6aH2dFg5/5FSqXzq+euG3Yr+M3VAYLLgNZmxd7LDzXIRGLEA/o/N3bFvCRtXUsSihUBRQCukJzRelbe1tvin3DpdOYWEAnW7B5z+omLpiT4I6r5hL2lc6kS4v0yv7TnRaaovC+KVqtwmRnbR/Jibh+SS2vdo5hOR69YwVczyN9SD9ASJOo83u01sbJewrRkI8LQj6WNVbg2TbP7xkgY3pc3F7J/z7TQX3UR53f5ZU+87CRHFmCguXQXhMi6tPYO5ih7ZCRpaLlcM3iWmz74JyNiqDBNYtrWd0c4+GtA3he6T5142B4HLrCdyxfJG06jOVs5HwPixe1EfAFMG2XoK6ybm4VVy2s5pGtvcxvbSSZLxIOM75mRqE+HsN0XF7eP0rRtrE8ja3dQyxtjBMJGgT8Pi5sDDCQdbl3YyeP7c4iSeCYNm+8/ipzay8D4IL2SizbZVFdlKGMSUvcT6rg0J/KU7RnRwfsFQuqxZqa4yCCBLh6UTVfeOgNXA/qYz56kwUsx5v41vzoJXN493l1pHI5+pM5JCTqYwaxUABPk1nZlCBoKOwaSLK6rZJfbO5mz5hXmuQ+xazKREAjnSvwxec7WFJXMSlIZKBrJEtjPDhxmTpe4qAi5ON9FzSXrue5ZHImhq7y/O5edNkjmfeojPqJBzSqKypYs6CN/b19yI5NNBSnezSPpuq0VZdKDty4pJpE2I8bLJ2qeJ5H10ga2TapjMdoiQcwLQfb8wj7/fj0UnDVVwSpi7UykMxiyT6aakYZztkEdYVobXTiuIOGBuNnQYvro1yzqJp4UGPDnjEG0nle7UzN+IlrK5tiZ/oQZgURJEBLIkhAV8iZDvtH8gR0Bc9xWNYYpTURZGVTDNdxmFNTiaGlKbgesVCAbNEaX4busXsozYK6OHdcFcR0XLZ2p8j2ZQhoMpbj4bjexDTzTftH+dIjO+lNmSyrPxginSNZmuLBSSECYFk22vjpUzpnsWcwRTJvsrVnjAq/j/pEAE+WWdUaojIyeaSqrrKKrv5h9vQM0FhdSdCvY9ouqgw+nw/LciYmWUmSRMhQ8QV0VFlicVOCsKEyVrCp8Gvo2sG3iyRJ1MRC3BALccOKgxP7PM+jWDQxDH3ScSyuj1IZMvj6k7vwqdAzVqQuarB/9PhX7Z4KUb/G6pYK9o3kePf5jWzuGuPB1/omfn/dktozeHSzhwgSSgWGVjTGeH7vMLGATqZg8v5lIRzN4NmOUYK6wpWLKik6ErIsURfS8MbrW0iSRM50SOUtXNcl6lf5g0ta2DVS5Ccbu+jPmPglh5xTmiA3mDHJFEunTiOZAg++1s/q5jhNVVGa3hQgB6iqguseWOBnk7dsamIBFjdUEA0Yhw1Puq6HLEtk8gVCfh9zmmooFE0MXUOSJPTxq4f8BtmCRS5vUxUpjazEgj4kSUKSJJLZIgPpPBGfiuQdvXl/4NTKshz6Uzmaq/TDrlMd8XHjygZe2DvCEztHqA5pVAQ00gV7YsnAqTTVgrwPXNjMn16/cOLnnGlTHfaRM22WN8Zois+MEaeZTgTJuLVzEjy/d5h0wWJNvY8RUyKVt7lxSSWrmuNkCzZjhsXShgr8hobjuCjjpxzxkIHrhSkULQJ+g7pEhIi/SFPFfL725E6e2jVK0XbxgEtbQ7wxbNGbKjKad3Adh1jw4CiIZTsosjxpKvbBymwSVdEAFSHfxOnOVA7cNuQ/OHTpMw7/YAMEfRp+/WBfi3zIor2goVIZ9rNrIMWcusRRX78Dx6hpCrp85LfViqYK2hIhVjZX8Kc/epX6qEGg0s/rfVly5rFXPJdjqhUTb74ooKv87duXnNLjOBud86M2B9xx1Vw+uLYFWZLoSLr8YnualzuT3LOpj394eCf/8uhOnt01RLpoU7Scw5b6VoZ9BPylQHA9eL0/Q08yz9tXNfH3Ny9hVXMFUb/GqrYa3ruqluz4ArieZJF/fnQn3WN5RrOlIkP7+kdI5iY3+Q/t8DtaiJwMeYoVvwDD2SKvdSU5v60a6Rjrkg9d1/Tk7qNPjY8ESqcTNyypwXFLBZaqQ1MH3am2b/jweiPCiRNBMk6RJf7uHUv5zZ9eyW9f3EY8qJM1HbJFh67RAuvmVfPglj5+s72PwWSel3b3TZxuvFkyb7G8IUZrPMD3nt9Pe1WIf33fSj52SQuW67Jp/yj2+KzZbQN5vvt8Jx/6xgvcdd9rvLhniIaqGNHA5IlQnufRP5bFfdMpQOEYxY/KkQj6WFAXIp0rMjB25A/cgdMax3EZSuX518f3kC4cbb0y2I7HO1Y20F4dYXN3imzRYk3j0WciT7d4UOez71h6Wh/zbCWC5E2qIz4+ccVcnvnMVdxx5VxMx8V0XMbSGXxOng17RuhLZtFlsCwL0yoNE+cLB2u2JkIGAZ9GQzzIf3zgfKIBnYCh0lARZEdfmsGsg09XJ158y/F4/3nVfOW9K2mtCjFe9vkwhiKTzJvs6hvDcT1yRZvtvUkc1zvmSueToaoyiXCQmliAsVxhIvzeTJIkBtJ5OkczE62rnQOZo963pso0xQP8f+9YyqVzKwn7NG5eEuXS9uhRbzddaiM+vvvRC0mEpnfh5rlKBMkR+HWFP7p2AX94Vamw8tbeNA11NdyyqomupAmqTjJvoWsqqWyejHn4N3C+aPHKvhF29CXJFy1kGV7vzRBUHK6eE+Sja+upDOksrPaTTqd4Yns/iaA+5doOSZIo2h67+0bRVYVX9g3yWtcY7dWhUp3W4+xfsG3niC2pqcRDBrqm0pyITiqAfOjj2baLZXs8tnWQ9uowH7u0jU37Ro953wFDw69K/OXbFqNrKs91moxmLSI+dWK28akSC2iiI3UaiSA5hg9cWJq34XgSf3BZKxfMSZAzHeojPrKWS65g4ToOVZEgeXPyYraAT6e+IkA8aJQ6aF2XwUyRN4ZMerMuW/oyJPMWmqbhC8d5eEsvm/YO8dzuAYrF4mHHUh3zo+s6jfEgVWEfc6qCExXNDu0wPRpVVY7YJ3I0Ab8+qZ/mwOPl8wX6hod5ZtcQm7tTXDW/ivOaY3jHGVaaqtAS9/P/rp5HR9LCdlwCusrK+uApDZM7r55H+DiLYAnHJoLkGKojPmojPlRF4UPffIm//skrLKqLEgkaxAI+TNsmWzAp2g7OFB+e6oiP2vHSfJ2jRVY2hEgEdZ7tSLGhI4XleLzWnWLTvlEun19Jc2WQguXyqzeGyRSsiVOWHX0pbMelLuJjz1CW2mgQx/PImjaqIk/L7EvLcU/4FEnXNWQtQLZoc9XCapoSAfyqwhULKo7r9pqqkCnaXDa/kn+8ZQlvW9VMtmjTMWoecXHgdDhWiQnhxIjh3+OgyBIdowVuXVVDe3WYVS2lD8lAOksyOUwsHMVQFQqmjeW4E5ttZYsWedNBHf9mnVfp57J5laxureCfHt7BnoEMKat0/4++MUj3WJ5FDVGuWFjLQ1v66B7NkS5YnN+aIKBL2LaLrirU6gr5ogmuR8F1JuaNlMtzPfrTeWpjU89nmfK1URTq40F+55I5E5ddvqjmhAIpOr5Kel5tjOpokK29KX65pe8YtyqPIqa9TysRJMehKe6nPmqwsTNFdUDm8W39LKkLUh8LYJphfEbpgxANTO64UxUZRfbY3TfGnuE8l8+vJl10OL+1io+tK/DQ6310DKbpzUksqtKpjoXYsHOQumiQqxdVI0vQMZxjLFskV3SJ+jyi43NO8gWLXUMpGmO+Ew6RIwWP7TiEjel5S5xMCylXtOhP5njH8lr2DqbZ1ndqhmZrIgaXL6g6Jfd9rhJBchyW1EdJ+GU+culchrJFbMdhOFWgKhKkaEt0DqepChuHfXgMVcFQFZJ5i7etaMCvq1wd9VM0Hd56XhuXLWlia/cIP3h6Gy8PeAxkxgipcN/L3fg0mbcvb2BOVYjBVAG/oeAzVFzXo1i08Pt1FMklHjrxDsMjBU/Ad2bmchwgeR59ozme3DFAVdjP3uE8hSNUYjtZyxqifPsjF1ARPLPP9WxzQn0k69evZ82aNYTDYaqrq7n55pvZvn37UW/zk5/8hNWrVxOLxQgGg6xcuZLvfOc7ZR306fau8xp5ZPswHcNp0jmL//j1Xvqy45XP4j5qYsHS9HDbIZU92EnqOC77hzOEAz5GcweHh43xjkqfIhGQbDb1mnQMZ3Ech5WtCS5uq6BnNIdPVyjaDkGfSlM8NL4Xr81IwSZXsFhUH8c55BQiXzAnhqOP16GrjM80TZEJ+1X6UyZBXZ72ELmgNc6/vX+VCJFT4IRaJE8++SS33347a9aswbZt/vzP/5xrr72WrVu3EgxOfV4dj8f5i7/4CxYuXIiu6zzwwAP8zu/8DtXV1Vx33XXT8iROtTlVQerCOq92pXli+yBBXWFpQ5RXusaYVxWiJlx6Y6qKjK6r9IzmGMtbLKyN0JwI0RQPTpqe7XketuvROZwlGg6QLHrURXQunFtNY0WQ1uoIa9oscgULv6GhSgdvvL0vydL6GKqqHNYC8p9Ei2Kqeihniq6rFG2H/aMFmmLT+2H/7bXN/M1NSyb6r4TpdUJB8tBDD036+Vvf+hbV1dVs3LiRyy67bMrbXHHFFZN+/tSnPsX//d//8fTTT8+aIPFpCrUxP8vqwwykiiTzFqP5Ijv6UpzXfHB0wnFcFFxiwdKw7wED6QI144vidvQleXbXIMvqw8yvreAzP9zI5fMS1EZ9fOSSOSRCBqbtsrIpRtZykBV30tCui8LmnhTLG6Kl+iJnwRBmKm/iuJDMFXi9N41jWzy7Z/rqvP7epW382Q2LJs2DEaZXWfGcTCaBUqvjeHiex2OPPcb27duPGDwAxWKRVCo16d+Zli06fP6hHdzzYicb94+SN11uWFKD67oTldRUVcFFRvK8icss28Wvl/J6z2CGZ3b1EfRpbOpM8cGvb+Cl7gzLm2K8a3UjjufieGBoCvtGclSHfcgy5Io2ruuxZyDN+S0VBA2VDXuGz4oQARhKFXh53zDP7Brk6V0j2C5T7ux3MnRV5pNvmSdC5BQ76c5W13W58847WbduHUuXHn29QjKZpKGhgWKxiKIo/Od//ifXXHPNEa+/fv16/u7v/u5kD+2UeKFjlL1DpVGEou3w441dGIpEquBw/eIqFjXE2LRvhL5UkXXtCdJ5m9aqEBs7hugby/JcR5KOkQI1YQ3XccjZ8EpPBkOVGc1a/PTlXjwkPn3NPEayJkvGyz/qiszOoTQNFQEypsOegTQLayO0JgLYtoP8ppXCs5GhKyRCOq/sG6G9KsieofxhleVO1h1XzhUTz04DyTvJRRp/8Ad/wC9/+UuefvppGhsbj3pd13XZs2cPmUyGxx57jM9+9rPcf//9h532HFAsFifN7EylUjQ1NZFMJolEIidzuGVxXY/zPvcI2aKN43o0xwNct7iKt61ooDLkw6/LFG2XVM4kFjT44Uud+BSJH23qYihrM5guPZd5CYNdw0WkQz4kiizREDX44NpmhrIWt5zXyILayMTjSlJp82tVkRlKFdBUmWjg7Oss/PHGTtriPj70rU1I0vRNGGuvCvLQnZeJvpGTlEqliEajx/zsnVSL5I477uCBBx7gqaeeOmaIQGmZ+ty5cwFYuXIl27ZtY/369UcMEsMwMIyZs5hKliUMVUZXdAbSRQZTOf7g8rlEAgbpvElkfPp4/2ievJ1nXXuC/mT+sHkQO4dLgXIguhNBnTlxgxUNYZJ5mzuumEv+kIVxB1oauwdT1IR8VJ7FGzXduLye/rEciiIR9alkijYeU9cQOZalNX58Tp5dSdg9mOUzP9rMF9+zYta33GayE4ppz/O44447uO+++3j88cdpa2s7qQd1XXfKtSQz1f7hHP2pIn5NZn5NiKUNMV7tGuWNnjFc7+AHfzBr0jmSR5U45urXoK5w88p6mit03nfxXLpG84T8GtXhw8PC86A/fbA+ieW45ItHX6Y/2/g0hebKENcsiBPTocKvnFSIAOQdQPchjY9I/eTlbv7hwW3Td7DCYU6oRXL77bdz991389Of/pRwOExfX2kaczQaxe8vjUrcdtttNDQ0sH79eqDU37F69Wra29spFos8+OCDfOc73+GrX/3qND+VU2fj/tJOfBc0R7h2eQM+GX7+Wh8Fy2NZQ5hL5yUwNI3RXJHaqJ97Xuzkuy90HfH+1rRW8LbltVy/uJqRdIG6kMrfvG3hEWeDzquJsHsgPfGzpshn5RRvSZL4gysXsK03yd/8fBsxv8RY/sRPcXYP5Q+77OtP76W9OsT7x4tnC9PrhILkwIf/zack3/zmN/nwhz8MwP79+yetLs1ms3ziE5+gq6sLv9/PwoUL+e53v8utt95a3pGfRs3x0lBuW8LHNYvryBYtNuwd5T+f3MuGPUM8+FovhuRSGfHTXhmgd/TIrZE5lX6+9O5lxIIGD23uYvdgjjuuaMPvO/JpiyJLzK+dfH56tjbTmxNBaiI+vuyT+eoTe3h2b/Kw6xwYgTnRPYX/v59vZWl9lGWNp6fmybnkhILkePpln3jiiUk/f+5zn+Nzn/vcCR3UTHNecwXrb16E7hYZHkmSiEdJBGRifpXBjEWuaNMc9yOnsrzaOUqyOPXr9I4VdcytCjCQytNcGebiebX8autm9o8VWdJ4/AvlzmaqIqMqMpfMr+ON/UM815E8bPTmQICc6MhO3nLEPr6niHhVj4MkSbzvwjYWt9Ty4r5RXusaY83cGi6ZU8G8qgB5y+O9y2O82lekM+WQKh4+B+KC1jjzasIk8xbLmkrzbhrjAb707hXsG0wzmJy9G22fCpIksbyliitaDCr8h3/fabJ0wsPDb11Wy4La8DQdoXAosWjvOEmShKGp/PjVPnYP7mZ5YwV500ZTJFQF/ueZHrJH6P+sCWl8/NIWrlhUR7ZgIkul/DZtl2jYz8rmSkZzNpGggzGDpqyfSaNZE5/fIBSpINvZj6ZIk+uTSKU9aXLmkTc1P5QkweqW46uRIpw4ESQnYE51mH/7wBryps1Y3uanr3TT/VovpgOuouPTbDRFnrTdJ0DWdIj6FHb0l87351YqdAxmaIiHyOQtokGNoE8VITLOth36UwV+8WoPI7nJ6VzaN1jCdj2SeYujFVFrrPAzkjXRVZnKgEpIzEs7ZcSpzQnyaQoVQYO2yiB3Xj2fC+YkqA8pLKgplT3MFA8fZchZLpu6Uiyqi1EVNPiz+zZTEw2QK5gEDJWAoU3UGTkenSM5htL5E6q9OptIkkRQg1svaGHnQIaFdZGJDbQkSp2tB7rrXDji9Pf3rKrlbctqWFofYW5NhNd6jj4kL5w8ESRlOr+lgsqwj6GMSVVY52OXtLGuvdQHIgHxgMZ7VtVx2bwqXuscwZMkPnpRM999bh/RoI9MwWLvUJb9wxkK4zVfPc/DOmR5f8G02dpdGoJ2HJf/fXovH//OJv7gWxvY3dXH8MjY6X7ap5SiyDQmwsypCnH7Fe0MposEdRVZAl2RwANVlo46eqPKEv2pIhfPifPxy5rZNZjlvld6sY5QCV8ojzi1KdP8mhCpYmnF79sWVjCQzPNGT5K1bTEum1fNssYIP97YzWC6yKNbezAtm0vm1fGjjV1csaCaR7b2URf1YTsQ8qlcOCeBhoemq0i2Q//IGM/t6GX7UJFF9RUoikxDzIdph6kKajy/ZwRrrJerzltIU2PDsQ94lpAkiUzBYn5tmFTeImc5aLKEhEfYV9rmM2AoOI5HznJwXG/SKE4soLGypYJ5tWF+8lIn+4az2K5Hx1CWeTWiw3W6iRZJmRbVRWmo8OOTPTbtG+W+1wbImA6tlUHe6Evxvef3050s8MNNPXzvxV429+W5cVUj7zm/gfs2dYInsas/TV8yhyJ7DCazDGSL6IrEcCrLhhdfpDpqgKKxo7/UNJeALV2j3LiinuaqGGO2yvadO7FOsKjRTOY4Ln5NIV+0aIj5kQDHg3jIh2XbVIU1dMnD9TwCmoz6plGcnOngeDJ9Y1me2TmA5Xh43rFnHAsnR7RIypTMFUkXLHYN5jBtB9stnc6M5SzeuqSaZ3cN8dDro0Bpn5c3+jL8w4Pb2N4zRsivcfm8AJfMSxAxZIqOhyLJzKkqfWMaukZGCnFlSyM/3rKVT//wFZrjAUayJqN5mxe37+dHL3USjlagGgpv/ORX3HHrW8/gqzF9Duyr7NM1AoaKKstUhnQMVUYK6OB5SJJHVbi0zqk3WcB2PVRZQpJgbnWIgObx4409jBYOnibu7M/AsjP1rM5eJ73693Q63hWIZ0rBctg9mOEffrGNZ3YPl/bJk8CvKRRMh6nOyqN+lWsWxNF0H390zVwSodLM1uT4CmKAoXSebd1jrGqK8T+/2cO/PNEx5ePLQGNE4Y51tSysi7J8/smtgZppPM9j074hOoaLdAymeXb3MEjQnzbxPEq7INqlLTRypjPRIQtgqKUNxd7snasa+PKtK0/js5jdTunqX2Eyn6awpD7Kd3/3Qj76fy/x6+0DeF6peX0kybzNb3YnUeQUl81LUBHQWdteOREiAJVhP5qWYVtvkke3Dx/xvlwgmXZ4o3uErGmfNUEiSRIrGuOsbJbpS2UxVIneoVE02aAnVaRQcJA8F1mWqYn46B47uMZmqhABWFw3876Izgaij2QaSZLEn1y3AP04a18sqg3xWxc0osmwuD5Cx2B60u8Lpk0iqDE4luEt848+mcrRFH62x+GRveZRrzfbHKgpa1oeyxuj1PltVBxCigOeh+lCe1WI4ezxrSa/ZnHNqTzcc5YIkmm2qC7CQ3dext/etJjL5lehTjHHIaTLLK4N8pbFNfSnTTbtT6EqMnfe8zK7Bw6WlfTpKvNqY1yxrIX3rqo56p4zLnDr+fUMZ86uIAF4sWOEJ3YMcWF7Ne2NVdREffTlwHZLJS07R3N4XmntzQG1ER9vfunbKoO0Voo1TaeCOLU5Bdoqg7RVtvHW5XXc/r1NvNhxcENtQ5V426IKPDvP+gffQJYlwobK1Yur+Of3nUdLPHDY/fUMjvLCniHqoj7SRxh1KNouP93cx6rGs6/pvrguzNo5CUzTpiIcwnTSLKoJsqU3gw6M5iw8b/ICPsdxWNNawQsdo6hyaXp9XfTsLQx1pokgOYWqwz6uX1o3KUhcD36+bYw/vnYu92/fScF0qAjohH06c6pCU97PnPpKdMNgrOjROWzQKCe5d6/MvrFS6yPiwZKox9xmnXdd1HJantvpFPGPb/cxvgG653kTozo500aRpUl74DRW+Jib8CMpKpos4XgwtypIU8WJbyYmHB8RJKeYe2BqtwRXLahiOGsSD2isbq3gfz90Put/+QYt8SCdo7kjTpSSZZnmqigfXCsTDof5wYO/5pJIjkU66DpgQajST+dYgfbKw1s0ZwPHcQGPoqexP2mSzJc2WJclCdctvb4Hxh9TeZsLWioYyVvUR+p4vS/HNfMrWNVyfLsdCCdOBMkp9krnGAA+BfYOZQn7VOZVB+kcKZApWDREfbQm/FzcXnnM+wqHS0Fz5YXnkQkNsOf1Hrp7MrTYkM/kueayNkKhqVs1s59H11CmNDlNkihYzsSWFaoi4XjSxK6DbTGNRFCmocKPoWpc2FbBoroQYV2s2jtVRJCcQsOZIr/ePgBA3oau0Rw1ER+5oskVC2qwXI/6iiCu6+HTDl/567jelAvSqhNRPrwuxKq4w3eezeA5cP3qubxl1dxT/pzOFM8rzWwNaDIVAY1c0cavKdiuR8hQ2TOUnVhz01gRYFFtiIguEwqG0DQFv66iquLtfqqIV/YUuufFzklzSUyndJpSEwtRtB22dCe5dH71xO9HMgUs1yOgq4QMle29SRY3xKa8b0VROG/pQlYuXoDtuOhTBNHZRFHk0t4+RZt17XFe7BilP1XEAxIBjbzlsH+kNHpTG/MR9PnQ/QZBn4ZhaBN9K8KpIYZ/y+B5Htt7k+SnmHjWn8zz5Ud2HHZ5Klfkx5u6+ewDW9m8f5Q/ufcVklkTz/MwFJmfbupiS9corusxmi2Sm6IswaFkWTrrQwRKc3Rsx2MsZ3FRa5xbVjXSFA9QMB0aKnzcuKyOqL906tKYCNFaU0FIVzCM0mWO4x6xuLZQPhEkZdo7mOHd//Usu940LLutL01l6PAaI6miy/97y1z+7IZFVAQ12ipDuOPflLIi87Er5nHR3GpSBYvKkMG+oTQdQ2Khmed5BPwa8aCOLHsUTJsVDRHm1oToT5lYtsOC8c7qmoiP0XQWXVWwbQfbtidGeYRTQ7y6ZZAkiSsW1RLxKXzkm8/xb4/tBOCxbf184aHt9KUKk66vKzIXtkRprvCjSB5zq6MsbwhTETLI5K2JPYILlkMsoNNSFaJjOEsyb06M/pyrJElCkiSiQYPFjQluPr+JpniAmoCMT5O5pD3GTcuqSQR1qkMahqZj2qVhYtf1xGnNKSb6SMrk0xQ+e/Myunv6+MOf7OTJHYO0hT0G3hQikjS+yMyFkZzF5t5+3remmbxpkTNtwodsw+nTFCzLpns4w6qmGCM5+6zdfuJEHfo6vGVRDdURg688tpsldTEigTyL60JEAgbZokXRtrBtjXCgNNLjeZ44vTlFRItkGsytDrNuWTufuHIevckCj+7JHram48AXYlPMx/MdY1yxoIqfv9JJNGAQ0A/Pc0+SyZgOiqwcscP1XLWlcwTP8+gdKzAnEeDSuXH6skUaowFuWFJNSCu1UgxVRZZlimap7qsIkVNHtEimiarIvH9tK6oq8UZPih++1Dnl9Xb0jrKrZ5jfbO3iL9++hGTWJBo8fFPwgu2wvCmO43pk8hYhv5gDAaXK+z5D5ZWOAXpTRbb25XjLwiqe2NbHFfMTzKn04Tc0NEUhUzAJhP04R1gJLEwf0SKZRlG/xrtXNdES97O04eBubqXK56X/bh8q8saITV1FgKIN/WM59g+nSWaL5AoHK6ZHfBo500GWJNFReAhdlWmrDBPy+1lWH2Vbb4qCaeP3+fn7h/Zw9/OdbN3fS9GyiAUMJDx8PvF9eaqJd+g0C/g0VjRV8L3fvZAr5leiK/LEgjJNlhmfjIntyfhVmV9u7eeN/jQPbO7hm8/spnPoYCmBoKEiyxJ+XcERHYZAafSmYFo0V/ipT0T447e005vM8/iWbnpGczy2Y4yvPtPH7sEUjgeapolTmtNABMk0e7FjhPqoTlBX+eJ7V/LgJy/hrctqCeoKIUOmKlg6RVFliW19GWoiCpe0VdFcYaBrMlt7k5jjFeQd18N13fFKYcNs2D007cebSqfZuWsXn/izX/DPX/kFGzZsmPbHmE6SJBH06YyMDDOYKlBXEaA26iNTtEgXbbKmw9beDD98sZug7/BTRuHUEEEyjWzH5ZvP7MVDQpYlKkMGc2vC/O1NS5hbE6Zgudy6up4/u34BluPww03dtIUkNmzby/ee2saGXaM88Fo/ewZLNUm2dA8znM4zkMyyqjlO1XhfSjJnYlpHrr52LHv27GHDixvpHxzkJ89u44eb+tgG7Lfhv386Mh0vxSnjeaWWWUVFguqIwWu7uhkcGeXC9gQBrfR2HslZ/GLrEG/0p49xb8J0ESeP0+ixNwaYV1Uqzry9Z4RYyE9NxE91xMePfv8iXto7xD89vIOPrIvxlVtX8sf3vsJvffcNIv7S9gr1UfjK+1cxtzrKUzsGqY/68Bs6mlKaQzGvLoptO7zaOcbi+giVJzGjtVAo8NRz2+jNwoN7LPqGkzzV44Ii4fNUmtoNXt28hRXLl56CV6h8kiThui6ZXJr+riSGaqEWHfb2jEwq6hTQFQyxYfhpI4JkGs2vDlIfVhnIWGSKBR56vZ/fXjuHRNhAU2RWtya4YE6C5/eO0DGUYSRrIcsSozmLL7xzMe+9oBUofVgum1815WOoqsK6eVUTs2FPlCzLmHkwAz5ifpV7e10W1IToGMrQkXLoSGbZsTvDz1qbZ2ShbSg9h8p4nMp4nC2dI4yN9NGdl1BUFRybsE/lz2+YzwObOrhpeQNttTEU5exfRnAmiSCZJp7n0ZwIgRdkmSLz3O4hLpxTxQ9f2kdvssBvrW1lLFvg2d3DNMZ8FG2XhqjG3KoqNnZnqFAd0nmLN/pSBA2NlgofkqwQnGLEQZElFE68A9GyLH7z9NOkbBixVPLJLEFd5bWe1PhzgKAm0dasTZQsmOnm10ZZWBchGArwtz97A12R+e8PrKJrNM/F82tRNYWn3+hmSVMl8ZAPWT7xVorremJC4DGI7SimgWU7/Pl9W9jRn+b6JdX89kVthH2lTtWOoQyvdCbBc9g5kAM8elNFcoUiGztGUVWV3lSRmF+lOqRTF/Uxmrf5/LuW4TgOtu3SkAhTHfGRLViYrke+aFFfceK1R0dHR7nvl88yqmhsTIbYPZijP32waLIEBDSJ/33/IlrjfqqqqmbNN/nOnhGG0jm+9Vw3jifxr+9fhWm7RAM6XSM5ZBlqI/6THkp3XfekQmi2E9tRnEaOB7+zroVFddHDhhpbK0O0VpaKDVm2w8Ov96JJDj/bP0bRhcFU6YM8lrexHY/3rmliZXMF+4dzrG2NEfAbZIs2juOyYyDN0vooruOc1Bu7oqKCj/zWjaX76h7i35/cyy9ePxgkSwPQY3rUxqMM57JETQu/f3YESXMiSHttjC8/spMXunJ8a8M+fveSOUiSRFNiego+F4omPkOMBE3l3IvYU8CnKSyujx1zvoLpuKxpidE/OMre4SyqNLkxmDEdfrixm/W/3I6mwPee388nv7+JG/7lN7z3v5/lhy91kSs6VASNsr4dFUVmUXM1//julfz+Jc0Tl28vQtqDnf0p/vfRLWzv7KNQOL5tHs6kzuEUg+kC/ekCKbsUfF/61Q5u+eoz7B/JTstjFAomG3d2UihjtOxsJlokp4HneWSLNkFDpWi7RKJhQnqW1c0RWip0ntydYsdgaXOnHf0ZgrrCvz6+h75UgZGMiSTBaM5kOFPEvWYesjw934rP7Rnm8Z0Hh3sPlFX5zq9fZ3MffPCiLOl0ikJBIxaLTctjngqN8YP9OX69FCSO69E5kqNnKElzvLwWieO4+Hw6NRVhnt7Rz9VL6su6v7ORaJGcArY9eZNOSZLQVZlfbx/Atl3evrKRf3r3UgJ+HzuGHd59XiNhQyEy3rGaNR1e7UrSnyqCBKbjETYUPry2gVio/C0ViqbF/zyxg7/82baJOiqyVOofAXi6H7IS9AwM8/37X0CSZvbpjSRJZHImkiTx+5fNAUrbpbYlAjzbUf5cEseD4ayJqgfImDO+S/GMEEFyCqhTzF/QVYVL5lbxQscIP9/cz+rmBL97yRx6UwV6UkX+7Lr5vHd1Iz5NRlMOniJ5HiyqDfLV3zqPD1+2sOzp3slMnv/41Wb+4eGdLKr20RwPUBXS+cvr5tBaYSCPV2M3FPj5hjSoEI3O/BEcv1EKu5xpUxXSUeVSOcr3rG4s+751VaYq7KO1KsTNqxrKvr+zkTi1OU26R7LEQz4ubq9iMF1kIGvRPZbjX25dwp/dt52xnMXHLmvnkvYYOcvlf57ez8v7x7iiPcJ5bVU8uq2ftqoAlZGTb6a7rktybIRtfRmaYqV5JO+aL9GdDxDyG7TGA3SOFXFdj5AuMZjxeN+Na6bxVSjfoTVFiqYNkkRvKo/uWiRiETRFZmVjmGTB5c6r59NU5mmNcHxEkJxC2YI5sd6jYfwN7dcVLpxTScGyMVSFF/eO8a6VNbTE/SRCCr/ZkcEwdBZWBxnLmewfLfKWBTaPbu6lJaqxoKmSFU0VqCcxjCnLMpFQkNuWx3h5yKFayjCvIcHihQtIZfL8dFMndQGPxBhkIx7vuayW6urqY97v6bZrIMVAyuT7L+yja6zA4toQH7igiVpFojVu8DsXNzOnOkptTITI6SKC5BQ60qKxRXVhLMfl7uf3M5q10VUZ05HY3pcm7NNJF0w27R8jZKi81p3is7/qJKS6XL+yAUPVTypEDojFYlyyJsql49/q6XQaHAvVM1lbkeGJfXDT1VWsmFPPkjnlnxZMB9Ny0FR5otziWM7mka19+DQF07TQFIW05WJaDv3JDBe01aGppeeXyxcJ+A+vnXtAaVEkolRDmUSQnAGSJNGXLHDlgmos2+Fbz+7hK4/twlBl2hIBLmqrIF20GRopjeTkTIecCS/uGeS6FW3T8vgHHJjBqqoqH7x+HStbdrB86WKi4Zmx0ZbtuCiyNFEqMVO0uX9TJ5IkIXsONWEDx3Go9Mv0jaQZzbmk8gUioQBOvsAbPWOcN6fmiH1L5+Iks1NBBMkZ0jw+SapoOYT9Bh++qJmc6fLw67083wEDaRNVmfzmf7k7T3tdGsdxmV8bmfLD0TGQQlNkGhInFgSaVhrivfSiC076OU237pEsY3mLhbURPM/D9eDfHt2O6Xhs2j+CjMv86jCjuSJZ08HzYDRTIFe0CPodTMdF11TypkPAEG/1U0nE8Wm0sz/Nzjctbd83kiPuV2itDCBLHtctruEzNyzg5uU1KG8Kim88s4+7n9lJsmCRPqSa2qFaqyPYts3WniTueD2T2cq0HVrjQSy31MGqyBIfXtdGbUijOmxQEwtSdDxqIgHuuGcL//jwTp7tSPF8xyhPv9EHnke6aIsQOQ1EkJxGybzFV5/YPfHz5q4x+kYzrGiKcUFrnOGsxWs9afKWwy2rG6iP+YHSHI+YX8V0XHoyDmFdmSgm7Xke1pvmrTgo6KqMLEuzuuneVh3Bdh36k6XZqZ7nIckSOdulvTpMY8xPb7LAfa/2sn8kxzN7Rvn1jmG+/HgHKdMh4NNZM2fmdRafjURUn0arW+M0xQMTP3cNZdncm+IPLptD92iWP79hASM5k539GX61d5gbFicYy5lUh3V2DeaoCJQWAj66tY8L2qu5cE6i1Ffwpqn2c2pm/ryP45E3bV7rTqLIErqqYigSO/qS1MdDyLg8vm2AN/ozeG9aCb2oLsw1SxtQZQnH9TgHNiI840SQnGbVYQPX9ZAkaEwECfhUntg+wOXzK9k/kiPvuOwazHLVwhp2dI9wUWuEyrCfVMFmOGtxw9IaFtUEaa+JkS1YBAz1iCMOuYKFrsooijwr65b6NIV186rpHssR0FVe6hjh8W0DpIs2v9jSP7FpOBwM0g9c0MSH1rXSmyxQFY4hau+fHiJITjPTcXlkaz83LqtjcV2EzrEc3SPwVz/bxsrmKN/dsA8kidUtMQZzDo/tGOHty2uR8XjfmkYefLUHbWUD8+sTGEhYjoeuHgyJgmnjODZBv4+ATyObKzKcM1FlhZhfJeA/vnU6Y9kiw9kcTtFGVzxqEzE0VTmtZQUOhN+jW/q4dF41v9rax9O7Rgjo8iEhctAHV9fyyavmkoicXN0R4eSJIDnNDFXhvMYo33x6N79zSTsRQyFWG+FTbzH425+/QWsiMP4hkHiuY4ys6bKnZ4hbzmvi6W3dfPCCGuZUhRhN56gIBw67f8tyyDsuAV+pgzIYMNg9mCER8bF3OEN91Ec06CNn2oSOMM9lNJ1jR/cwHcM5fvByPxUG5Aom77xgDu9e0zZR5MdxnFMWLI7j4noemqpQcFwURWI4Y9I9lic4vjBPkaWJ0RxJgrXzqqmKHf6aCKeeCJIzoDLi56qFtfSnCsiOyWDOwVBl1rXH+cGLXTge9I5lGU6VOhlfHrDZ2LebtyxI0DdWYCDXSyQU4J3nNyPBpAlqQb9GZsxBkiQcxyVv2ixuiCHLEiFdxaM0d+JIIdI5nOWPf/gyyDJLa0OM5R02deUAOG8kj+m4OJZH0FB5ed8Iq+dMXRKyXB6loHBdl/NaKvjgN16gc7Q0r0aRJfxaKWyL4xX3JQ8eea2bG1c0nZLjEY5OtP/OAF2VsR2LD319A5/89rP89xPbKToe5zdF+fxbm2mLKUQMlfT49sGm7WK78PC2Yb72XD/tVT6GczY9YzkGM5PrhciyTN14h66iyIT8OqqqIMsy0aCBrpa2sHScySM9tuPSN5bFtF1WNlfQNVrgG891smc4N3GdH27s5q1feoShVB7P85hbG2W6ua5LMmehKjKyXDqFeaNnjIV1Yc5vivCWBQk8D2zXw3Tcie4RF3hyxzAv7h2iN5nHdo487G3bzmHPXyiPaJGcIQ3xCEsa4/zk5W70vhF+/0oHv+rxkx0pirZHa8KHoUuYb1q2/lsXNLG0qYbe7AD/8IttnN8cZXVznMWNMZLZAq6kUDc+bHwo23FxXZei7RI2lMM6aPMFk70DKfZ19/D49jTdY/nD7mMwY5HXZboGhmipChMLTH+1sFTBJuJTsSybsbxJ0XY5ryXOsoYI+aLH5p4xchbsGsyQKdjk3YOFhkZNeM9/Pw9AUFeIBXSqIwZzq0Jc2BYnFtRojvkZzVs0xnzUxYKiFus0ES2SM8SvK/zJdfNorwxgAtf92/M88PoQVy2spCpkEAv4uOuti7hyweRTh399qpNHtvbwzlVN3LSsllVNUTKmxf6hNNGAb8oQKVgOA8ksD2/pIeLXUdXDvz+Cfh1PVhmzdKpDpS0wwoZKVdhAPeTDljFd/uyBPby879Tsf7N5/ygdgxm296dJhPw4bmmXwrG8x5LmCj52+Xy+9oGVvGdVPW2VQY6UA1mzVI6yL1lgw64BvvHMXr7wy+08+kY/v/ftjfzXU3tFiEyjEwqS9evXs2bNGsLhMNXV1dx8881s3779qLf5n//5Hy699FIqKiqoqKjg6quv5oUXXijroM8WdbEgn7hyHvp4/ZIHtwzgWQWuWlTDy51JugbH6BhIHna7z/1yF//86A427R/BcWXm1oapivoZzh48zckULEzTxnU9krkimqIQ1DWU8Q9PoWhimgdnx8qyzMVzq6iKR7h+aR1BXWVFU5S6qI+AruDXFFRZQldkekYL3P69l/i/p7aTLdrT9nq4rsfaOQlsx8WyLLJFG01y6RzOsL17mN+80cdgusBL+0dJRHxUh3UaYqVCT4ng4QO9vakiYUNlKGfTlywQ9an8aGM3WdPhj69bOG3HLZzgqc2TTz7J7bffzpo1a7Btmz//8z/n2muvZevWrQSDUy/ZfuKJJ3j/+9/PxRdfjM/n4wtf+ALXXnstr7/+Og0NokjMu85vJB7S+Z1vvshQusAL3SYdo+mJCmnmFOfyOcvlm8904AFPbR+guSrKZfMrWdVUgaJI1EYDhHwatl36Vq6JlvpM1h7SwXqkIsbNQZem9ip2DaRLk708CPlUbMdDlkqVwt67qpL3XdBK0Sl1uk4XWZbQdZWndg0RDxksbZLZNb7m6B3nNSPhURHUsRz42lN7ShXkxiWCBroi05ua3Ge0dzhb2lQLeKMvTcZ0WFgbJuoXM0ymU1nbUQwODlJdXc2TTz7JZZdddly3cRyHiooK/v3f/53bbrvtuG4z07ejKJfjetzwL0+xeyCDM8VfQ5LAUGVc152oq3rA25ZWcfPKBs5riVMR8tE9mqcu5p9oeRzp8Y72e9d1eXZ7D692jdGXdnhq9wjNFX427R/FdDw+ffV83rWqnmhAw9Cn/wO5YUc/8YifoALRoI+X9g7h9xuk8yZ3v9DJ5q4kozmTtkQAXVORJfj8LUtJF0z+9Mdb6Bot9VK3JALsHyl1FuuKTHF8KcH/3LaaaxbXTPtxn41Oy3YUyWSp2R2Px4/7NrlcDsuyjnqbYrFIsXjwmyWVSp38Qc4CiizxtQ+u5rqvPIUz/mav8cNta5v5ze4RXurK8odXtLOjL8nPXhvg0Kx5dPsw2/oytCaC3Lq6kYF0nhuXN1IxRW3X/UMZspZDZVClIuBDVaeeAyLLMq1RBSuvYsgSKxtjZE2bD1zQRNp0aa8OUX0K5mtkCiauJ+G6Di93DFMX9XNpIoyiqnzy+y8zmCmyrD6CKrl8eG0j713TwqvdKfqTebpGsvzZfVtJ5g+eru0bH3FSZWkiRKA0u1iYXicdJK7rcuedd7Ju3TqWLj3+fWI/85nPUF9fz9VXX33E66xfv56/+7u/O9lDm5VaK4O8Y2U9P3ypC4D+PGztGcNPgfnVAbYPZHjbojjZfIEdwyZDGZOc5RJQJfpTJhfNSRAL+ljbXokkywxniiRCBz8wfakcYb+KT5e4d2MPH710zlH/+I31dTTW13G56/JGXxrX82hOBIn4Tt0pgWV75G2HuliQgM9Hx3CKT35/E51jBVwPKv0S71hZQ33Ex3ktlYxki6xsjLIZj5c7U2SLU6+Itt80C7Z+ig5poTwnHSS33347W7Zs4emnnz7u23z+85/nnnvu4YknnsDnO3I19LvuuotPf/rTEz+nUimams7+iUZXLKjmgc29pVWujovsOXSmXD77nqXMqw7j1yQaahLkTZPP/Xwre0YKXL+gguaqCC1VEXqTOQxVIqDK2K5H1KeSLNgkQgau7eE3VCwXPn5ZO7JcmsylShx1dqosyyyun/75IlORZAk8B2SZeTUBAppEfTRAT8pkZ3+a1S0xqgIq3WkTT5LY1p+lKqRz9cIadvbvojLkoy9VOPJzkSAe1KkMiU2upttJBckdd9zBAw88wFNPPUVj4/GV4/viF7/I5z//eR599FGWL19+1OsahoFhnHvNz9ZEgJqwTudogd9aVcWqxgjLGnKokkfleHN8SYPOr7f105QI0RgP8EdvXcqvtg7wX0/t5cvvXU5NxIcsyewdSuF4pXok2YJN/XjNWJ+hYlmlEZ3elElN1E9whmzLGQvoxAI6luMiSxItlSHipossp2iN+wgZCvtG8rjI7BlIsbQ+TEXQIBYyuGl5PVVhjbtf6Gbv8OFzYKA0jFwV9s3KBYwz3QkN/3qexx133MF9993H448/Tlvb8ZX9+8d//Ec++9nP8tBDD7F69eqTOtBzweL6KH/51vncuCDC21c1cOP57Vy6uIUVzYlJ17uwPYHtwpWLagn6DdoSAW5cWotpu+iKTMG2aYkHGUkX8KkKnjt5iFbTNPx+P3nnyHVlzyRNkVFkicGsSVXYoCriBzwcFxbVxbhucQ1IElUhnahPo2i7VEd9NFSE0I4RigeGi4XpdUJBcvvtt/Pd736Xu+++m3A4TF9fH319feTzB78BbrvtNu66666Jn7/whS/wV3/1V3zjG9+gtbV14jaZTGb6nsVZpKUqSjwa5v+e66HoeOQdicF0btJ1ukey/OEVzbgu/Or1Xtoqg8yvDhHSFTRNpSLow9AUokGDoE8jFCh9ePKmxXCmSNdoBsdxWDjD65YENIXRTIGwT6NgQ1MihOU6pIs2S+pjvNqdRtcUDFVmNFd6bkNZ86j3KfpHTo0TCpKvfvWrJJNJrrjiCurq6ib+/eAHP5i4zv79++nt7Z10G9M0efe73z3pNl/84hen71mcReZWh1nVEmdZU4zOsRzzasPE/JO/RduqwgznPe55sRNVkgjqCrUxgzd6x+gaTrOlawxVVQkY2qTZm65l8+NN3YxlTGRZnvGV0xNhH5GAQSJkcEFbgoChEvZpDKQKbOkenSgjKUkSc6pCLKgJ0xY/eotjSf3ZN31gJjihPpLjmXLyxBNPTPq5o6PjRB5CAC5qi+PJEtWR0hCrOz7qcGBzKFWRsT2JrpEsj2/vR5Vd5lRFWNNejeeB40y98beu63xwbTMypd30ZkNXwYH5LgdCryJgkMnbRAM+FtcdbFHt6M/gItOUCLGpK8VUb1VNkXjHSjEJ8lSY2V9J56jBvM2XfrWD7X1JvvXMXnb2p/jVa11s2D0ElEoQXtqeYEV9kF9s7uX/3buF4UyBaMAg7NOoH68g77rupFWumqbg11UMXcX1PBzXO64vh5lEliV8hkr3WI7PP7Sdb2/YS38yT3M8QNdYlv5UYcoQAagKGUf8nVAesfp3Bto3lOOljlGiusfbVzUzpzJIe1UIWZYYSOawHBjMFDCwydvQGFVZ3FBB73CK0byDriu8uHeY91945M7wcjbZOpPGsgW+t6GDjfvHuGxeJelsEV2ReOT1Xl7pGmMgPXVrDKAnWWD3YIalDadnOPtcIoJkBvJpMr/81KWMZEplEv/s3k2sqvdTbTiM2QY7xmw2d6XYPViaM5HKm/zl95/G7/ej6qXK6ndc2c6G3UNc1F55hp/N9Ir4DdqqQwykC+RMm+f3juDIMqlsgUzepnNk6qHfAypD5960gtNBBMkMdP8rPfg0hYvaK/nKYzvZ1JPl0R0jRF2HFh9Y0SCvdGc5UDw+ZcJPd+SRpTw+VaYiqPNPj+zi96+Yw/6hFLqiUltxdpQgvO/lbvb0J9mwZ5j51SFe7UqxqTNJSzzAzoGjjwS2VwWpjYrh31NBBMkMYzkuHcM59g1naakwCGsefckiecshCQzYkHCyfOSiRsxinhc6kqQclZFMAUVRqI0GCOoyl86N0xQL4CITDeoUbQfjCGtrZpPn9wwSNBQsB57aNYJpu3hwzBABqA6LEDlVZueJ8lns1c4xPveOJdRFDLb2prn7pV7y1sElv4oH169soT4RYeXcg4vzFFkmXXToSea5sK2ClU0VdCeL1IZ1ipbD7oHsmXpKZUtnC2zpHuPZnf3Uh1RGsjYRf2ki2pv7Tt+1spaa0NTrgda0Hf/iUuHEiCCZYbb2ptjcNcozu4fZ0T1M1pr8UfEHNHbt6yZXtFnVFKWxMsqCmhAN8SB1UT8Rn0rnSJYvPrKT+1/pxvTg5f2jRH0H/9Sm7U7azuHA8PJw5sjrVM6UvOmQM10CqsKewQyOrPFyZ5K+VGFiaHh1S4yVTaUO1J+/NsAl8yqJBw+fsbumteK0Hvu5RATJDPPotgH+8eGdWMUCP32l57DfFyyHt61u5/zmCNv7M6SLNjsGskR8KssbI6ydU0F/qsh5zVH+8sZFRHwaly2ooTLkY2Q8KDRFwjpkWPjApLVEyIdlO4wcY3bo6WQ5LvGQznCmyONvDFLhk1ha6yeVt3Bcj7Chsmn/GJu7kgR0Bct1+flr/VM+hwUzfCbvbCaCZAZJFyy29iQp2g7feamf7SOT18goEsh4/Gb3GBVBnYCuUhX2M5wx+cz1C7igNc7r3UmuW1rLHZfPmSjOrMgShq4SHz8NkiQJ3xT7WGZyRVzHJeKbOV1nEb+GqipomsS7zqsj5De4bEENzeOV8tNFm4qAhqbI5C2HsKEesYK8NkuHvGcD8crOIK91jbGoLkLBcg+roQHgeNAehdf2D7JvKM3qlgo+c8NCfnXnJaxsjnPtoiounVuqSxKdYvOsIzEth8F0EcPQKJgW3SMzZx1U71iO4XSehdUhNuxNoqsyr3Ymueu6uUT9pcAbzlql/hKvVIV+ipcOgNHczGlpnW1EkMwgOwcyXDI3wcKaIIZSKq+YCOqsaamYKBD98qBHdwYU1cC0HSSgPh7CcT1iAYNs0aGlwkfxkJqMluOSLkxd9AdA1xQUycN2HCIhPy1VM2c9Sl0sQDRg0JMy+f1LWwnrCtcuraM+6mNVU4y2xPEH5tEmqwnlEUEyQziOw6+29PLo631c1BrhvKYIqgwXNgd5cd8o5nipQEOBxQmZBzb38qutfRN9HaoiE/Tr/MO7VzG/Lkq6UPr2dVyP3QPpI27bAGDZDiGfjl/XZmStDk1VmFMdprEygqHJ7B3M8MDrQ6ydk6Bou+iqjHoc7+RfbO499pWEkyKCZIZwPPjAhc384TXzCRsqsYDOe85vQlYnz8QsOvDqoM2PNnXz5NZuckWLVzsn7zHjU2WCRmkIVJElYgF94uc3yxQstnSNHbXFMpP4DIOgrrB7MMPPXu1hTlWQtkQA2y3NCF7WcOTW1E82ddF/lApqwskTQTJD6KrCmtYKXMfl/evm8aX3nc81i2r49fZBWhIBNOVgS+HAwrNHdya5/+VO2hKhicV3I1kTyZPwH7JNRG30yDU4PMDyoHM4M7Esf6bqT+Z5pXOUHf1pdg2k8WkKmYLFjvHJaMvqo1zaXsHyxoNrafRDmipZ0+GT33+ZguUcdt9CeUSQzCBV0SBXLKylLuonoKtUR31ct6SGZfVhfKpy2OmJ6Xj4rSQF05wIl3hQR9ePfwarX1XoSxboGsnOyNOaQ9VE/bzv/CZ8msKcRIDzmqJs7S2VDKiP+vjwuhbWtCaoDWt87NJW6iIGH13XwpqWGFAa9t64b5T3/PuTjKRmTofy2UAEyQw2rybMH1+3gKivtOz/0NEIWSpNJPvNfpP/eLKDH2/cd1KPoSgS1yyuYU5NhOQsGNVQNYUPrWvhg2ub2D2YYX51iLWtMd6xsh4JiURIZ1VjhOFMkZzl8r3nO7FsG1kCy/GwXY+9YyafvOfVSZPyhPLMnAkDwpTqYwHetbqRn23un3T5gc/Ahs4srTmPREChYyBJc2XkhPa0fWnPMH5dpi4WYMPuIW5YPrML//g0BZ8WhCaFd1keuwcyrGqKsn8kS18yx/zaMCG/znN7ezFtlzlVAV7pTk+6j0zR4aZVTeOngzO7FTZbiCCZBeYkgqys8/ObjvRhv0sXbLb3ZXjXylo8YM9girk1R6+34breRNisaa9kLFNAVmRiQYNswSJ4CveumS7VYR9vW9GI5biM5kwst1Sm8tfb+3lwywAVARVFltjRf/gpzHnNMW5d03wGjvrsJU5tZoFYyM9Q8cjfnKoMAUNlKGOxsz895QhMqnDohuGl+xpM5sfv30emYLG6NT4rQuRQmiLjVyTOa47TUhni7Sub+OCFzXiehyJ5tCaChN60P/HaOYkj3JtwskSLZJb4wIXN/NVPt0x0qqqyhEdpnkjRdvnPJzu4dlEVG/eN8PWn9/G+CxqRJZnWCoOBrEnY0DFUaE6EiQY0tvemUBWFvO3SFA8Q0DU27RvmgrZKJEmaqA87G/h0FW28REI8qHPR3Eqe2zvMw6/3M5TJH1ab9sk3evnEpc2EgmdHjZaZQLRIZonfXtvCJ65on/jZdr2JzkLHg95knm8+u5+iI7G5K8lTO4foGEyTtVwawwapvEllyKBQtJGRyBRMBjMFdFVmKGPSOZIlETTY0Tf79lm2XY9s8eC6pIAi0ZYIkgjqyBKEdBX1kH6j1/tyfOGRPUdckyOcOMmbBdV/j3dH9LOd7bgMpIv8aGMX//zIDmB89OZARXivNC8koJf2emmvDOLTJC6eE+e6pXWkCzaVYY2xnE3PaJ65tRF0uXTa4zoeiUiAupifvGnj19VJfSmzieO4KIrMc7uH+NIjO9jZn2Ysbx92vfNbKvjHdy+nvSp0Bo5ydjjez55okcwiqiJTH/PzybfM4/0XlPZCPjB643ng12QkCXKmw2jOoq3Sz5yqCLGgTlM8xPyaMGGfQVNFgPNbE9i2jeNBzKeRKtoEx+ef+PXSGe9sDBE4uHXFiqYKVjdHWdUUnbIWycZ9o1z35af425+9ztgsGPqeyUSQzFL/3zuWctn8qkmX5Sx3og+lrTLIhr2j/OzVbvKWRypfoCdVAGQiAYNoQEdTZWQJZFWlrTJMMl+cddtTHI1fV/jj6xfz/719ERfPmbo6mu16fOvZDq778pO81DEy5XWEYxNBMktpisxXbl3Jn16/gIvbDx+FSOZM8qaL60FDxODh1wfJ5C0ifhVJKhU28usGkYCPeEDHdh2aEmEkSZpYIHg2kCUI+X140uS3uiozqd9kIG1y69eeo2iL6fMnQwTJLBYP6nziirl848NrJgr9HJApOoR0mRuW1rJvLM/AWJqaqJ+hVI6BsSyv94yRNy00PHRNoSkRpmDabOoYIpWb3cvtLdvhlc4xBlN5LNulImjg02QMVebqRdWsaIzgeKXWiE+TiQc0akMKjuuxve/wuTrCsYkgOQv4NIV3n9846Y/peh5r2yvpTRWpDPl4y7Imfrmlj+G8hY1Ee1WYlkSQtFlqffSn8mztHiUWMKiMzN6Nti3HZSBVYGVTjKqIH328EtwfXN7Oxr+8mn+5dRVXzq/E80otkoAmc/XCSm5dXepz6hjOHe3uhSMQQXKWWNUcw+Xgfr6267G7P019SGYsZ+K6Du9YUccLu4epi/qpCBrIskzN+D4vQ+kirVVh5lTP7rqmmiLTEA8edrkkSYR8GgXbYWNnaYjbdj0MVSHoN6gNqfhVicAUJSiFYxMT0s4S4fEZqYf2lb7em8LzXCRVZ1VzDL+ukszb5Ip2aWTDA9/4SM2ShtgZOOrT78cbO9nak6QhViogLUnQN5ZjY0eBvO3RNSpaJCdDtEjOElPV2LBdSOYKvHNFLT96cT/9qTyKLJE3LXyaws9e7ZryvrK54sTm46NZk9e7xiieBTU8HNfj19sHWdcWo60ySNa06U+b7B7Msbm71EoJzbIlAjOFCJKzhKEcPufDcj2GCvCTl3t5+4p6In6dj10+l3CgVHXtllWN2FOMUhiGNrHxVMin0jWcIZ0/+p66M5H9ptGnwXSBm1fWoxs6G/YMs6Y5wu9c3ML+Q1oh1y6pOd2HeVYQQXKWGM5ah/0xVVkiV7R5vTdFx1CGe1/cy9M7B+kfy1EwHVRVwXZcOkcO7sKXK9ps70ujjk/q0hSZq5bU46KQN22K1uEzRGcqRZEmWlae5xHxabxjVSOfuW4B93xsLd/+vYu5YVkdBetg4LzWlTxThzuriSA5S1zQEiXwplZ5aXhTQZUAyWNJfZz+dIF80eRAA2bnQJp0zqRgOQwmc0gSNMX9eJ5HpmBh2Q6e56KrCvuGM/SMzY4+hKJpM5QqkM4XGc0WSRdsHnq9l+d2D+K4Lmta4xiqQtFyqTtkY/Gndw2dwaOevUSQnCUiQR8Xzzu8Wf6WeRUsa4iSLTq0JvxUh330pixGcqUiyNURP1v7UiQzOTZ3jpA3LYqmTTJXIGiUVtXqWqkY9YLaKLWR2bFiVtcUEmEfe4dzbOka5aV9I6QLDj98sYudfRlMs1RWoSKoc8t5DVSMp3BlyDja3QpHIILkLBJ60w55FQGN+7cM8tDr/WzuHCVjOsR8KgNZE79W+uDoqsy6eVVE/QYVAR1NLk2h17XDt6aQpMlFpWeq1zpHeX7PEM/uGiQc0IkFfTz5Rh/gEfJrvLR/jH/45XYAqkIGEUMhmS8Fy6La2T38fabM/HeFcNzevA3naM5CkwEJUkWPvpE0ldEQmiyxZyjDyuY4BcumMuRDliTaa6P4DQ1VkWftKI3neTTEAhRtm7G8zbaeJE0xP9cvrsXG44YlNewazLG4PoLjuER9Klt6MxOdy3Wx2TsZ70wSQXIWObQmxwGWC2N5m037R7l+SS15O41lw8KaEF2jWbpHcoT9Bh2DKdorQ6TzFhUhA0MrdcSqs2y/3HTexKcrxMMGtTGPRfWlspMF08anq/SN5VheHybo13BdD01T2Nw1hqbImLZL3pydAXqmza53iXBUQ5mp18iYtssF7dXUVfioixi0VgboSxXI5EzWtFXiU2XmVYfY3J1k5+DBEZyesfysWg3cO5ZjMFtk90Bpvcyhp2au4zKaLVAd8SONt7iG0wUKlkMyb2Go8kQZBeHEiSA5i3QMTT2iIkulhWwPv9pJ/+gYC2rCjORtwgEdy3bY3peicyRPMlfk3hf30Z8s3U9zIkixeLBOx0yvKFYXC9BeFWFZ0+G1RwJ+nbBPLxW3NjR6R3PEggY+TSHm10gXbOpjPtqrDp9eLxybCJKzRM606R47fNJYxJDxPNgzlCVo6PgDUcJ+nWV1UVzPY/9whkRQZSBTpCYWJBbUufelgzNefb6DoxjZoj2rWihvpioy4YCO67o0JoLomsJo1pwom3DdkjoMsdbmpIggOUvsGph657hU0UVTZPqSRR7ZOUbO9nhmRz+b9g1SLFo4nkf3aJamuI8X9gzTPVo4YkdrNKDPmoLQRyPL8kTfz47+FBG/Nr7YcfaG5JkmguQssa33yEWbdUWiNmpQG9b48aZu9o0WyVsupuOxrSdFQzxMIqAztyrA21fUcnF7BSOZAi/tGTyNz+D0OhCIFQGN81oq8Dx4oWP0DB/V7CVGbc4S23qPXJAnYzoYeRMzZOCzbfYOZclbNm/0pOkazXDBnAR+w4/rwiVzq+gZyTCWLVAVObsXsI3lTF7sGOPFPUNct6SG37+s/dg3EqYkguQs8WLHyERF+amMFhyU0TwXtMaIBXXmVoXoHcsTMX3s7E8RMjTesrQO23FJhAIoqkwsqJ/eJ3GadY3mqAxq/PVNSyjYHksbzt0dCsolguQsMJgusmcwe9QzfA9I5k1e7kxx+cJqfr19iMW1QRbWhtgzmKW1MoyHhOc5xCO+s6Iv5FgW1EZoiwfw6epE5Xnh5IhX7yzwSucY5jGGZlVZoiUeoDbq443OEVTZQ5Zl6qM+NFUmlTVRJI+I38AcLy3gHql5c5bQFJmgXxchMg1Ei+QssH8kN7HrniqBPcXn36fK+FSJVzvHeK0rycLaEJUhg9d7kty0oh5FkRhKpWmpjmNos3tfG+H0E1E8y3mex9d/swcACbjlvPrS+po3SRcdtvVnkSSI+NXSznumy+6hPOmcSdCnUXAUZFm8JYQTJ941s1zRdvnIhbU0REpVzbb0pHn7ysYpr2s5HhGfyl++dSFXLKjkhy/upyasUR8PsmcwRXtVSOw4J5wUESSznCxJ3P/aEN0pi4hPZWtvmrevrOfqRVOXDFxYE2J7X4pb/nMD1y2pIV1weGXfMI2xAJmiw1jOYu/Q1JPbBOFIRJDMcroq88fXL+Ljl8/hgrbSjnuffWAr/++aeSyombw5dsSQ2do9ylef6qAh5udnr/bRNZbnke3D7OpPsnswRW3UQJFgLFtaADjVimJBeDMRJGcBVZLwawpffM9yon6NnrE8qiyRfNOOeamiy+j4RTcur2NpfRjXg+f3jLB/NE9lQOPF3UNUh30ExgsY6apMPm+SKYhTHuHITihI1q9fz5o1awiHw1RXV3PzzTezffv2o97m9ddf513vehetra1IksRXvvKVco5XmMKl86u4aE6CqF/jK7eu5H9uW03PWIG+tHXYdStDOhe3J0jni8QCGmFD5XM3L2YwXcRzZWpDGl1jaXIFi70DaTRFxu/X8etn9yxXoTwnFCRPPvkkt99+O8899xyPPPIIlmVx7bXXks1mj3ibXC7HnDlz+PznP09tbW3ZByxMzfE8Hn69n7VzErRWBom+uRL0OF2RWNtWQW/SxHI8Pn3tvNIq2ILHN1/YT96TaKmIYHsemioznCqVFFDEULBwFJJXxrrwwcFBqqurefLJJ7nsssuOef3W1lbuvPNO7rzzzhN6nFQqRTQaJZlMEomIacxT2Tec5aEtfQxlisiSxPyaMN1jeX7wYuek8gK6KtOWCFAbMfjrty3i2xs6qIn42TmYRbaL/MmNy6kK+zBth1TepCYm6nOcy473s1fWhLRksrQHSDweL+duDlMsFikWD57fp1JHXtkqlNiuR850+KNrF0yq3fp7l87hD7//Mo9u6wdKu83Zjsv7VtfzRn+SaMCHIsu8ZUEVFSGdb/xmF39y/WIMTaHGCNI1nKE2Fph1JReF0+uk3x2u63LnnXeybt06li5dOp3HxPr164lGoxP/mpqapvX+z0adIzl+tbUf601T5f26wr//1irefX5pbonjegxlLf70vm3808O7eXrnAI9s7cXQZV7pGOEdq5rQNBVZlsnkTfrTeYpT7MYnCIc66SC5/fbb2bJlC/fcc890Hg8Ad911F8lkcuJfZ2fntD/G2eby+VV88d3LCU2xXYRPU/indy/n45fPASBvOSiyhOtBLKDTkzT5xeY+1rQlCOgwki6QzBXpHMmxqDaKrsiYs2iHPeH0O6lTmzvuuIMHHniAp556isbGqWdRlsMwDAxDbFR0IiRJYklD9Ki//8x1C9nak+I3O4eQANvxuOjCBs5virK8MYzi2TQn4mztGmNhfZRIUEMaryYmSaXtL8UCN2EqJ/Su8DyPO+64g/vuu4/HH3+ctra2U3VcwikgyxJ//bbFNMcDWI5LUJe5enENc2sCaJJCW1UERVFY2hxH01RqQj729CfpHc2RLViMZAvYtmiZCIc7oRbJ7bffzt13381Pf/pTwuEwfX19AESjUfz+0sZCt912Gw0NDaxfvx4A0zTZunXrxP93d3fzyiuvEAqFmDt37nQ+F+E4zK0OoSoSb11aw7VLapFlmUvaa1FUGWu8CPKBWiSqqrCgvoKRdIGBVJbWqug5UadEOHEnNPx7pDfRN7/5TT784Q8DcMUVV9Da2sq3vvUtADo6OqZsuVx++eU88cQTx/W4Yvh3ev3Hr3fRM5rmlpX1RHw6W/tSOI7L0sYYBctiaWMVqYJF2FCRZQnPA9O00DQFRRFV1s8lp2T493gy583h0NraOqu3MDgbffCiFq764pPcdlErliOxqCZMcyKMoins7h1BliW6RrMsbSjtD1O0LJAkJEn0jwhTE++Mc1DEp9EU99MzlkeRHfy6iuU4SMC8+tLCvzmJgwv+fLqGz9BEoSPhiESQnKNWNMZI5SzifgO/oeJJMnnTnthZL+ATa2uE4ydKLZ6jqsIGEb+O7UE+V8CyPX69Y5jGCgNJklnWXIFPkcCDyohfVE4TjkoEyTmqOe5HliCZt5AkD12RmFsTZkVTBTIO4YCP3tEcUb8qQkQ4JvEOOUflTZeMbRPQIKSrVEYC4NokM3k0WUaRJFqqwgRE+QDhOIggOUd1jmSpiwSwXY+goTOcyRML6jRVRoiE/BMzWHX9YKO1IKbJC0cgTm3OUQPpAl2jWUZ0jZ39KRorI1SHdRR58lB9Jm9iWQ6SVJoZa6iKmJQmHEYEyTnKsiwubYuRssB1g1i2TS6bpQ+XRCSCDBiGRsDQkMZHcBzXw7KcSa0UQQBxanNOGkwX+c3OIf7ou8/SM5Qim0mTGxvmsVe7eHHXMDt6hlHV0ltDHl8l3DWUQlVkNE3MbBUOJ75azkFP7hhEUVS2jLj86Y9fQ867rFlYwZK6MGY+jWmHSOYs4mEFy3bAcwkYCt2DYyQiITwJFElCF6EijBMtknPQWM6kYNkkAgrVYQMlKPP4zlG+81Iv/ak8iZBORcigUDCxXRdN09A1g7wrU3ScSRXYBAFEi+Sc9M4VtYTtNF3JPCNZi1+NmXiyioOCiULcr7G3bxhN1QgH/WSLBUI+lbk1ESzLoVCwMAwxLCwcJILkHJSIBFja3sBzj2/hkrmVZNF5cNsI6WKRS5YuZddwnsc276cuESFry6xoDLKovhKfVloNrKgKjusiy6WWSd608YsO2HOa+OufoyqCBvXxEPe9tI8hL4hpu0gS/NODW7Adl50jFnF3kJuWBwm0LmAglUVVZcI+jTdXEsgWRZCc60QfyTkqVSjSmXJ5ug92DmRRxuuObOwp8Gq/SdHyiATg1zuy6IaBLkv4VBnLsg8rC1EZ9p2hZyHMFOJr5Bzkuh7dYybtVQEAHA94Uzg4QMaFkE8mbzqYsoc3nCJkqFTHwqf/oIUZTbRIzkGZXIGCaTI4PHrU63XmIOJTqQhoZLIWpuUREEW5hSmIFsk5aHNPkoe3DvLktqNvPOZ5MK+pjjk1MUI+DRmJZN4k6NMOmyZfKNr4ptgKQzg3iL/8Oej5XYP8/LUBjqcA5luX1uA4DtXR0tadlu0ctjVFwXTIFkx8horreqKS2jlInNqcYzzPo7ur87hC5PrFVSysCTKczk1cpqmlIZtJ+9t4HhVhH5btYr9ppz/h3CCC5Bzjui4Zz8A3xV9eOaQlMbcqyBXz47y4dxC/fvR+EZ9RKn6kqbKYNn+OEqc255hU3qY14rHBBVkujc7gQsCQKLoSNYrHjRfUccWiWjpHC1y6sEFMiReOSQTJOaZgmbzr8vOoqtjJK3uGqIhF2L45RXXCo7UxxtvXLiAeCpLM5tFURUw0E46LeJecQyzLxq/r6KrGJcsX8M6LlxLx+7Bv8ZBl2N47RsTQyVsWjfEQ+0ZyovNUOC4iSM4hmqYS00p/8nio1O/heaBrpaBIhP14skxzrLT96o7+NPNqwoAIEuHoRJCcow7MAzl0OkgiUNoIy3ZcJEDHERXkheMigkSYIMsyr3UOUxcLMpwpEPCLWazC8RFfNwJQqsc6mEyjyDIVAZ2e0QwrGmNn+rCEWUIEiQCA57qM5Bx0GVIFE1lRiATFql7h+IhTGwEoTX0fSheIBAzGCknmVUfP9CEJs4gIEgGADXuHWFAfxXE8RnJFaiKif0Q4fiJIBADaq6JUhn0YmkLzmT4YYdYRfSQCAHnLwRBT4YWTJIJEAOC17jFcV6zcFU6OCBIBgPqon5196TN9GMIsJfpIBADWzas604cgzGKiRSIIQtlEkAiCUDYRJIIglE0EiSAIZRNBIghC2USQCIJQNhEkgiCUTQSJIAhlE0EiCELZRJAIglA2ESSCIJRNBIkgCGUTQSIIQtlEkAiCUDYRJIIglE0EiSAIZTuhIFm/fj1r1qwhHA5TXV3NzTffzPbt2495u3vvvZeFCxfi8/lYtmwZDz744EkfsCAIM88JBcmTTz7J7bffznPPPccjjzyCZVlce+21ZLPZI97m2Wef5f3vfz8f/ehHefnll7n55pu5+eab2bJlS9kHLwjCzCB5nued7I0HBweprq7mySef5LLLLpvyOrfeeivZbJYHHnhg4rK1a9eycuVK/uu//uu4HieVShGNRkkmk0QikZM9XEEQTtDxfvbK6iNJJpMAxOPxI15nw4YNXH311ZMuu+6669iwYcMRb1MsFkmlUpP+CYIwc510kLiuy5133sm6detYunTpEa/X19dHTU3NpMtqamro6+s74m3Wr19PNBqd+NfU1HSyhykIwmlw0kFy++23s2XLFu65557pPB4A7rrrLpLJ5MS/zs7OaX8MQRCmz0ltR3HHHXfwwAMP8NRTT9HY2HjU69bW1tLf3z/psv7+fmpra494G8MwMAyx96wgzBYn1CLxPI877riD++67j8cff5y2trZj3uaiiy7isccem3TZI488wkUXXXRiRyoIwox1Qi2S22+/nbvvvpuf/vSnhMPhiX6OaDSK3+8H4LbbbqOhoYH169cD8KlPfYrLL7+cL33pS9x4443cc889vPTSS3zta1+b5qciCMKZckItkq9+9askk0muuOIK6urqJv794Ac/mLjO/v376e3tnfj54osv5u677+ZrX/saK1as4Ec/+hH333//UTtoBUGYXcqaR3K6iHkkgnBmnJZ5JIIgCCCCRBCEaSCCRBCEsokgEQShbCJIBEEomwgSQRDKJoJEEISyiSARBKFsIkgEQSibCBJBEMomgkQQhLKJIBEEoWwiSARBKJsIEkEQyiaCRBCEsokgEQShbCJIBEEomwgSQRDKJoJEEISyiSARBKFsIkgEQSibCBJBEMomgkQQhLKJIBEEoWwiSARBKJsIEkEQyiaCRBCEsokgEQShbCJIBEEomwgSQRDKJoJEEISyiSARBKFsIkgEQSibCBJBEMomgkQQhLKJIBEEoWwiSARBKJsIEkEQyiaCRBCEsokgEQShbCJIBEEomwgSQRDKJoJEEISyiSARBKFsIkgEQSibCBJBEMomgkQQhLKJIBEEoWwiSARBKJsIEkEQyiaCRBCEsokgEQShbCccJE899RQ33XQT9fX1SJLE/ffff8zb/Md//AeLFi3C7/ezYMECvv3tb5/MsQqCMEOpJ3qDbDbLihUr+MhHPsItt9xyzOt/9atf5a677uJ//ud/WLNmDS+88AK/93u/R0VFBTfddNNJHbQgCDPLCQfJDTfcwA033HDc1//Od77Dxz/+cW699VYA5syZw4svvsgXvvAFESSCcJY44SA5UcViEZ/PN+kyv9/PCy+8gGVZaJo25W2KxeLEz6lU6lQfpiAIZTjlna3XXXcdX//619m4cSOe5/HSSy/x9a9/HcuyGBoamvI269evJxqNTvxramo61YcpCEIZTnmQ/NVf/RU33HADa9euRdM03vGOd/ChD32o9ODy1A9/1113kUwmJ/51dnae6sMUBKEMpzxI/H4/3/jGN8jlcnR0dLB//35aW1sJh8NUVVVNeRvDMIhEIpP+CYIwc53yPpIDNE2jsbERgHvuuYe3ve1tR2yRCIIwu5xwkGQyGXbt2jXx8969e3nllVeIx+M0Nzdz11130d3dPTFXZMeOHbzwwgtceOGFjI6O8s///M9s2bKF//u//5u+ZyEIwhl1wkHy0ksvceWVV078/OlPfxqAD33oQ3zrW9+it7eX/fv3T/zecRy+9KUvsX37djRN48orr+TZZ5+ltbW1/KMXBGFGkDzP8870QRxLKpUiGo2STCZFf4kgnEbH+9kTnRSCIJRNBIkgCGUTQSIIQtlEkAiCUDYRJIIglE0EiSAIZRNBIghC2USQCIJQNhEkgiCUTQSJIAhlE0EiCELZRJAIglA2ESSCIJRNBIkgCGUTQSIIQtlEkAiCUDYRJIIglE0EiSAIZRNBIghC2USQCIJQNhEkgiCUTQSJIAhlE0EiCELZRJAIglA2ESSCcAq5rseO/vSZPoxTTgSJIJxCr3aOsbUndaYP45Q74b1/BUE4fsubYlRHjMMuzxVtAsbBj5/resiyNOV9eJ6HJE39u5lCtEiEaed5HqZlM5LOnulDOeMUWaKhIjDpMs/zUCXoT+XxPA/bcUnmTEzLxnU9NneN4TgunudRNG0KRRvbcc/QMzg+okUiTLsXdvWzsWOI371y0Zk+lBlJkiRyBZN0tkC+YGE6Nr1Jk5qon4V1UYKGynCmQG+ywH88uZvVzVFCPoOl9WEW1cfQFJl80UZTZRRZmhGtFREkwrR59NW9PLEnzes9Kb7/sYvQVeVMH9KMlC1aPN0xzFjGAg9aEwHaqwLEQwFG0znaq0K4rssrnUl2D2TZ2pOmKqCQWlLLoroYruvhN1TGckVigcNPm84EESTCtHBdjz1jDhv3jbG0IYJPEyFyqIF0geqwDwDXhZaKILsHhvjyozupj/r4wIXNtFf6CegKi+slKkI+aqI+PnbZHOpjfjqGsly/uBZNPdgbMZASQSKcZYYyRZbWhrjy/SvZcg6MUpwIz/N4eEsfH7yoFYCi7bB/JE9vskDUr5Eq2HztN3vJFm0+flkb8aDGWLZIWyLAsoYYsixx6byqSfdpOy76DMpq0dkqTIvqiI+GRIC51WHyRftMH86M8p3n9nFha3Ti57G8yes9SZ7ZNcTiuhCGKpPMW7iex8829/Llx/aQKRSxTJPBdH6i0/UAx/VQldJtZgrRIhGmhe24hA2Vou2yqD567BucI375Wi//+tguln3wPGzb4YHNvTy5Y5AX940ykC7SOZrnwKivqsi0xIPguXz96X00V4Z5y+IqKkM+DL30UXVdj75kDr+mUhPxncFnNpkIEmFaqIpMPBzAdlyG0oUzfTgzgud5/NvjOxnKFMmbFruHcvzNz7bgehKqImHapSFdRZZwHQ/Tdnl61xAAN62o58cvd9MSN2iOB0kEDWRZRpYlEiEfnuviU/Uz+fQmEac2wrRSFZlrltSd6cOYESRJ4sbl9QB4SLRVBijYHj5dYTR38LTEcrzDbvvzV3tYVBsm5Pexcd8Ym/aPkh0/lfFpCn5DI+DTpnzcoXQB13XJF0/fqY8IEkE4BbJFG8/zqAyVWg13P7+fvOmwojE2cRo4FUWWCBsqH1zbguN6bOtN89CWPl7rTjGYLfByRz/dwylS2eJht7Ucl+29KTZ3jZHMFfDpKt1Dk9f5OI6LZdkToTRdxKmNIEyzZ3cN8aFvvsDXP7SGpvFZrb/Y0s+uwQ2YjofleGSO0CEd1BVMx0WVJT597XxGchYdw1me2D6Ipkhk8wWy+T7qq6K8b03rpNtqikwirNOSCODTVTzPI2e7jGZNon4NWZZQFBlFkdk/kqbdP3WL5mSIIBGEabR3KMsn7t6E5Xh0j+axXZdEUGc4a7K9P3PU28oSpAo2jRV+fvhSJ/e/0k2qYLOwNkxQV3FceHT7CE0VAaqiU7coKkOlDljTstE1lXm1pY5vx3EpmC6+8THj9prwND5rcWojCNMmXbD42LdfYixnIUnQWhngfWua+cHH1/LBtS3HvL073lUykjVxPciaDo7r8XpPiu6xPF97ag87+jNUhjTWzkkc9b6sNy3NURQZy3ZO2ZodESSCMA0c1+PTP3yVnQMZGiv8/PQT69g/nGPvUJrqkMGfXDef//3QaubXhI56P5oikTMd8pbDLasa8GkyrQk/SxsihAwVXZXZ3p+hc9Q86v0Ep+iDCQd0VOXUfORFkAhCmTzP469+uoVHtvYTMlTu/t0LMR2X3mSBp3cOE/RpRPw6C+si7B48+opoy/HQlNLEknte7KRguewbyfPE9kGGs0XCPpXf7BxixzHu5+iPMf2tEtFHIghlGkgXqQwZ/PbaZmRJojkRZEd/hk9c0c61X3mKa5fUUrRdPvadl3Dcw4d638xyPFRZwnY9fJrMJXMTLGuIYjnQnAigyRKXzqsEwHVdTMfFpx3/R1k7Ba0SyfO8Yz+zMyyVShGNRkkmk0QikTN9OIJw3BzXw/U8+pIF9g3nGM4WGc6YDGeLjGRNhjImI1lz/P+LpAul0ZygrpA1HQDWtMRYWBPiPefXIysquWKR6mgAXZbQFZmXO5Oc31JBPOw/5vFki/aUpz1HcryfPdEiEYRTSJElFCSa4gGa4oFjXt+0XUZz5qSwGc2aJHMmT+4aI2/Z1ER8rGyq5L5Xu7hqfhXLGqLHFSKl4yn3GU1NBIkgzCC6KlMT8R3XOppbx+eROI47UarRdV1k+chpcSKnQCdCBIkgzHLKIc2Mo4XIqSRGbQRBKJsIEkEQyiaCRBCEsokgEQShbCJIBEEo2wkHyVNPPcVNN91EfX09kiRx//33H/M23/ve91ixYgWBQIC6ujo+8pGPMDw8fDLHKwjCDHTCQZLNZlmxYgX/8R//cVzXf+aZZ7jtttv46Ec/yuuvv869997LCy+8wO/93u+d8MEKgjAznfA8khtuuIEbbrjhuK+/YcMGWltb+eQnPwlAW1sbH//4x/nCF75wog8tCMIMdcr7SC666CI6Ozt58MEH8TyP/v5+fvSjH/HWt771iLcpFoukUqlJ/wRBmLlOeZCsW7eO733ve9x6663ouk5tbS3RaPSop0br168nGo1O/GtqajrVhykIQhlOeZBs3bqVT33qU/z1X/81Gzdu5KGHHqKjo4Pf//3fP+Jt7rrrLpLJ5MS/zs7OU32YgiCU4ZSvtVm/fj3r1q3jT/7kTwBYvnw5wWCQSy+9lM997nPU1R2+dYFhGBjGzNjTVBCEYzvlLZJcLnfYQiJFKRWgnQWlUARBOA4nHCSZTIZXXnmFV155BYC9e/fyyiuvsH//fqB0WnLbbbdNXP+mm27iJz/5CV/96lfZs2cPzzzzDJ/85Ce54IILqK+vn55nIQjCGXXCpzYvvfQSV1555cTPn/70pwH40Ic+xLe+9S16e3snQgXgwx/+MOl0mn//93/nj/7oj4jFYlx11VUnNPx7oOUiRm8E4fQ68Jk71tnDrCi12NXVJUZuBOEM6uzspLGx8Yi/nxVB4rouPT09hMNhJEk604czSSqVoqmpic7OznOunqx47mf/c/c8j3Q6TX19/VGLJs2KCmmyLB81DWeCSCRyVr+hjkY897P7uUej0WNeR6z+FQShbCJIBEEomwiSMhmGwd/8zd+ckxPoxHM/N5/7VGZFZ6sgCDObaJEIglA2ESSCIJRNBIkgCGUTQSIIQtlEkBzFiRa67u3t5bd+67eYP38+sixz5513npbjPFVO9Pn/5Cc/4ZprrqGqqopIJMJFF13Eww8/fHoOdpqd6HN/+umnWbduHYlEAr/fz8KFC/nyl798eg52BhBBchT/f3v3D9JGH4cB/BH/YRsyWFREifEPtmpjCVI61BCFCkIQqlihIEQlm0KWDpWGkgwOQiqtoIMgkQwmkEGK4hAQQdF2CYotiNoWKghqMBS8JcXk16GY95VX+nqeyRn7fMDB+PPu+S0PlzvzVe6g62g0ioKCAjgcDjx48CDJ6ZJP7v6XlpbQ0tKC+fl5hEIhNDc3o62tDWtra0lOevXk7v327dsYGBjA0tISNjc34XA44HA4MDExkeSk14SgCwEgZmZmLrzebDYLu92etDypJnf/p2pra4XL5br6QCl02b23t7eL7u7uqw90DfGKhJImHo/j+PgY+fn5akdJubW1NayursJsNqsdJSXS4kN7lJ7cbjckSUJXV5faUVKmtLQU4XAYJycncDqdsNlsakdKCRYJJcX09DRcLhfev3+PwsJCteOkzPLyMiRJwsePH/Hy5UtUVVXh+fPnasdKOhYJXTm/3w+bzYZAIIAnT56oHSelysvLAQAGgwEHBwdwOp1/RZHwHgldKZ/Ph97eXvh8PlgsFrXjqCoejyMajaodIyV4RfIHkiThy5cvie9PB13n5+dDp9NhcHAQe3t78Hq9iTWnQ7ElSUI4HMb6+jpycnJQW1ub6viKyd3/9PQ0rFYr3r17h0ePHmF/fx8AkJeXd6HhONeJ3L2PjY1Bp9Ph3r17AH4/Cne73Yl/VXvjqf3Y6DpbXFwUAP7zZbVahRBCWK1WYTabz/zOeevLyspSnv0qyN2/2Wz+4/p0Infvo6Ojoq6uTty6dUtotVphNBrF+Pi4iMVi6mwgxThGgIgU4z0SIlKMRUJEirFIiEgxFgkRKcYiISLFWCREpBiLhIgUY5EQkWIsEqI0Jnck5HmEEHC73aiurkZubi5KSkowNDQk6xj8rA1RGjsdCdnX14eOjo5LHcNutyMYDMLtdsNgMCASiSASicg6Bv9EnuiGyMjIwMzMDJ4+fZp4LRqN4tWrV/D5fPjx4wfu37+P4eFhNDU1AQA2NzdRX1+Pz58/4+7du5c+N9/aEN1gAwMD+PDhA/x+PzY2NvDs2TO0trZiZ2cHADA7O4uKigrMzc2hvLwcer0eNptN9hUJi4Tohtrd3YXH40EgEIDJZEJlZSVevHiBxsZGeDweAMC3b9/w/ft3BAIBeL1eTE1NIRQKobOzU9a5eI+E6Ib69OkTYrEYqqurz7wejUZx584dAP8MX/J6vYl1k5OTaGhowNbW1oXf7rBIiG4oSZKQmZmJUCiEzMzMMz/TaDQAgOLiYmRlZZ0pm5qaGgC/r2hYJER/OaPRiFgshsPDQ5hMpnPXPH78GCcnJ/j69SsqKysBANvb2wCAsrKyC5+LT22I0ti/R0IajUaMjIygubk5MRKyu7sbKysrePPmDYxGI8LhMBYWFlBfXw+LxYJ4PI6HDx9Co9Hg7du3iMfj6O/vh1arRTAYvHgQFaezEZFC/zcS8ufPn+L169dCr9eL7OxsUVxcLNrb28XGxkbiGHt7e6Kjo0NoNBpRVFQkenp6xNHRkawcvCIhIsX4+JeIFGOREJFiLBIiUoxFQkSKsUiISDEWCREpxiIhIsVYJESkGIuEiBRjkRCRYiwSIlLsF6uCgRL7CackAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cobertura_bc.crs"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YepsXPwcqrum",
        "outputId": "c6786eb6-e6e8-45c8-a6af-320e2635acf9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Projected CRS: EPSG:6372>\n",
              "Name: Mexico ITRF2008 / LCC\n",
              "Axis Info [cartesian]:\n",
              "- N[north]: Northing (metre)\n",
              "- E[east]: Easting (metre)\n",
              "Area of Use:\n",
              "- name: Mexico - onshore and offshore.\n",
              "- bounds: (-122.19, 12.1, -84.64, 32.72)\n",
              "Coordinate Operation:\n",
              "- name: Mexico LCC\n",
              "- method: Lambert Conic Conformal (2SP)\n",
              "Datum: Mexico ITRF2008\n",
              "- Ellipsoid: GRS 1980\n",
              "- Prime Meridian: Greenwich"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se comparan los sistemas de referencia de ambos dataframes y se igualan"
      ],
      "metadata": {
        "id": "eEF0Zg9zxK9Q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_bc = agebs_bc.set_crs(epsg=6372, allow_override=True)"
      ],
      "metadata": {
        "id": "yAQHy4FiquOW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se hace la operacion de interseccion entre la el Df de AGEBS y el Df de Cobertura"
      ],
      "metadata": {
        "id": "aEyygkg0xl_s"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_con_cobertura = agebs_bc.overlay(cobertura_bc, how='intersection', keep_geom_type=False)\n"
      ],
      "metadata": {
        "id": "axyZpefNq7-y"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Esto nos agrupa las entidades con cobertura"
      ],
      "metadata": {
        "id": "SzsVGcCryB-f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_con_cobertura.head()"
      ],
      "metadata": {
        "id": "lSd1FZ9LrgMw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "7a3d9633-6559-41b0-8a44-5e956b6fa591"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          CVEGEO CVE_ENT CVE_MUN CVE_LOC CVE_AGEB  Ambito           estado  \\\n",
              "0  0200102472200      02     001    0247     2200  Urbana  Baja California   \n",
              "1  0200101399918      02     001    0139     9918  Urbana  Baja California   \n",
              "2  020010001795A      02     001    0001     795A  Urbana  Baja California   \n",
              "3  0200100011490      02     001    0001     1490  Urbana  Baja California   \n",
              "4  0200102431819      02     001    0243     1819  Urbana  Baja California   \n",
              "\n",
              "       Periodo          Area  \\\n",
              "0  1erTrim2024  1.327252e+10   \n",
              "1  1erTrim2024  1.327252e+10   \n",
              "2  1erTrim2024  1.327252e+10   \n",
              "3  1erTrim2024  1.327252e+10   \n",
              "4  1erTrim2024  1.327252e+10   \n",
              "\n",
              "                                            geometry  \n",
              "0  POLYGON ((1106181.991 2273545.301, 1106202.373...  \n",
              "1  POLYGON ((1115876.388 2252044.571, 1115939.958...  \n",
              "2  POLYGON ((1115347.288 2267907.628, 1115343.720...  \n",
              "3  POLYGON ((1110427.922 2273453.920, 1110419.600...  \n",
              "4  POLYGON ((1141638.155 2205987.606, 1141595.689...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ff09b4f2-aced-4916-a58a-55b2efa5c548\" 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>CVEGEO</th>\n",
              "      <th>CVE_ENT</th>\n",
              "      <th>CVE_MUN</th>\n",
              "      <th>CVE_LOC</th>\n",
              "      <th>CVE_AGEB</th>\n",
              "      <th>Ambito</th>\n",
              "      <th>estado</th>\n",
              "      <th>Periodo</th>\n",
              "      <th>Area</th>\n",
              "      <th>geometry</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0200102472200</td>\n",
              "      <td>02</td>\n",
              "      <td>001</td>\n",
              "      <td>0247</td>\n",
              "      <td>2200</td>\n",
              "      <td>Urbana</td>\n",
              "      <td>Baja California</td>\n",
              "      <td>1erTrim2024</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>POLYGON ((1106181.991 2273545.301, 1106202.373...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0200101399918</td>\n",
              "      <td>02</td>\n",
              "      <td>001</td>\n",
              "      <td>0139</td>\n",
              "      <td>9918</td>\n",
              "      <td>Urbana</td>\n",
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          },
          "metadata": {},
          "execution_count": 10
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_con_cobertura"
      ],
      "metadata": {
        "id": "-QmCzhLyr4F8",
        "colab": {
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          "height": 423
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        "outputId": "b7c949d1-ddc2-4d58-cf5e-caab4c418436"
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      "execution_count": null,
      "outputs": [
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          "data": {
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              "             CVEGEO CVE_ENT CVE_MUN CVE_LOC CVE_AGEB  Ambito           estado  \\\n",
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              "...             ...     ...     ...     ...      ...     ...              ...   \n",
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              "1948      020061139      02     006    0000     1139   Rural  Baja California   \n",
              "\n",
              "          Periodo          Area  \\\n",
              "0     1erTrim2024  1.327252e+10   \n",
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              "4     1erTrim2024  1.327252e+10   \n",
              "...           ...           ...   \n",
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              "\n",
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              "      <th>3</th>\n",
              "      <td>0200100011490</td>\n",
              "      <td>02</td>\n",
              "      <td>001</td>\n",
              "      <td>0001</td>\n",
              "      <td>1490</td>\n",
              "      <td>Urbana</td>\n",
              "      <td>Baja California</td>\n",
              "      <td>1erTrim2024</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>POLYGON ((1110427.922 2273453.920, 1110419.600...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0200102431819</td>\n",
              "      <td>02</td>\n",
              "      <td>001</td>\n",
              "      <td>0243</td>\n",
              "      <td>1819</td>\n",
              "      <td>Urbana</td>\n",
              "      <td>Baja California</td>\n",
              "      <td>1erTrim2024</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>POLYGON ((1141638.155 2205987.606, 1141595.689...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1944</th>\n",
              "      <td>020060982</td>\n",
              "      <td>02</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>0982</td>\n",
              "      <td>Rural</td>\n",
              "      <td>Baja California</td>\n",
              "      <td>1erTrim2024</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1177852.805 2114230.607, 11778...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1945</th>\n",
              "      <td>020061020</td>\n",
              "      <td>02</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>1020</td>\n",
              "      <td>Rural</td>\n",
              "      <td>Baja California</td>\n",
              "      <td>1erTrim2024</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1160784.467 2106392.172, 11607...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1946</th>\n",
              "      <td>020061035</td>\n",
              "      <td>02</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>1035</td>\n",
              "      <td>Rural</td>\n",
              "      <td>Baja California</td>\n",
              "      <td>1erTrim2024</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1182316.893 2099951.953, 11823...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1947</th>\n",
              "      <td>020061054</td>\n",
              "      <td>02</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>1054</td>\n",
              "      <td>Rural</td>\n",
              "      <td>Baja California</td>\n",
              "      <td>1erTrim2024</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1175823.743 2092033.027, 11758...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1948</th>\n",
              "      <td>020061139</td>\n",
              "      <td>02</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>1139</td>\n",
              "      <td>Rural</td>\n",
              "      <td>Baja California</td>\n",
              "      <td>1erTrim2024</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1318480.444 1830071.228, 13185...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1949 rows × 10 columns</p>\n",
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              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('agebs_con_cobertura')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "agebs_con_cobertura",
              "summary": "{\n  \"name\": \"agebs_con_cobertura\",\n  \"rows\": 1949,\n  \"fields\": [\n    {\n      \"column\": \"CVEGEO\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1949,\n        \"samples\": [\n          \"0200500010932\",\n          \"0200400013060\",\n          \"0200400012306\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_ENT\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"02\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_MUN\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"001\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_LOC\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 44,\n        \"samples\": [\n          \"0585\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_AGEB\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1949,\n        \"samples\": [\n          \"0932\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ambito\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Rural\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"estado\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Baja California\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Periodo\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"1erTrim2024\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Area\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.907838135870171e-06,\n        \"min\": 13272522475.674534,\n        \"max\": 13272522475.674534,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          13272522475.674534\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"geometry\",\n      \"properties\": {\n        \"dtype\": \"geometry\",\n        \"num_unique_values\": 1949,\n        \"samples\": [\n          \"POLYGON ((1078958.1040000021 2334426.5956999995, 1078899.5533000007 2334351.2683999985, 1078829.1493000016 2334293.9827000014, 1078769.0755999982 2334263.6022000015, 1078755.6696000025 2334266.8786999993, 1078654.9333000034 2334363.9745999984, 1078640.6048000008 2334369.1371, 1078636.0437000021 2334370.3739, 1078626.3369000033 2334373.0058999993, 1078590.988499999 2334385.7721999995, 1078553.4953999966 2334401.606899999, 1078527.4701000005 2334409.0997, 1078500.1018999964 2334411.7225, 1078476.0890000015 2334402.0102999993, 1078463.6125999987 2334391.299800001, 1078458.2326999977 2334381.7062, 1078454.7007 2334366.133200001, 1078451.925300002 2334336.0560000017, 1078446.233599998 2334314.0901000015, 1078445.9746999964 2334313.8561000004, 1078431.9596000016 2334301.1911999993, 1078418.1916999966 2334294.1372999996, 1078417.7971 2334396.2029, 1078417.3924999982 2334487.638700001, 1078370.8051000014 2334488.6702999994, 1078373.8905000016 2334542.5047000013, 1078378.0900999978 2334618.104200002, 1078379.8619000018 2334644.1515000015, 1078475.8109000027 2334629.094900001, 1078485.2924999967 2334626.876699999, 1078512.0298999995 2334619.3225000016, 1078539.269100003 2334607.0339, 1078566.641900003 2334590.041099999, 1078626.0287000015 2334573.4879, 1078881.0803000033 2334503.971099999, 1078944.804700002 2334486.5251, 1078983.8923000023 2334476.043299999, 1078958.1040000021 2334426.5956999995))\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Con la operacion de Diferencia nos muestra las entidades sin cobertura"
      ],
      "metadata": {
        "id": "rxtsizjGyKZT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_sin_cobertura = agebs_bc.overlay(cobertura_bc, how='difference', keep_geom_type=False)"
      ],
      "metadata": {
        "id": "8Z-ylBNqtCu5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_sin_cobertura.head()"
      ],
      "metadata": {
        "id": "bpXlOPwOwa98",
        "colab": {
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          "height": 206
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        "outputId": "64844b60-0761-4a9f-c83e-10295695daae"
      },
      "execution_count": null,
      "outputs": [
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            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Marcamos si tiene corbertura o no"
      ],
      "metadata": {
        "id": "5BaYFOjGdZST"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_con_cobertura['cobertura'] = True"
      ],
      "metadata": {
        "id": "o18ANtReweW2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_sin_cobertura['cobertura'] = False"
      ],
      "metadata": {
        "id": "kaHWtyAJzFL1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Combinamos ambos Dataframes"
      ],
      "metadata": {
        "id": "bJH6U5W9dh65"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# unir ambos dataframes en uno solo\n",
        "\n",
        "agebs_final = pd.concat([agebs_con_cobertura, agebs_sin_cobertura],ignore_index=True)\n",
        "agebs_final.head()\n"
      ],
      "metadata": {
        "id": "CZAPuxBi2TIn",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "3b78eae1-135b-4d01-f35f-1b13b8e8c25b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "          CVEGEO CVE_ENT CVE_MUN CVE_LOC CVE_AGEB  Ambito           estado  \\\n",
              "0  0200102472200      02     001    0247     2200  Urbana  Baja California   \n",
              "1  0200101399918      02     001    0139     9918  Urbana  Baja California   \n",
              "2  020010001795A      02     001    0001     795A  Urbana  Baja California   \n",
              "3  0200100011490      02     001    0001     1490  Urbana  Baja California   \n",
              "4  0200102431819      02     001    0243     1819  Urbana  Baja California   \n",
              "\n",
              "       Periodo          Area  \\\n",
              "0  1erTrim2024  1.327252e+10   \n",
              "1  1erTrim2024  1.327252e+10   \n",
              "2  1erTrim2024  1.327252e+10   \n",
              "3  1erTrim2024  1.327252e+10   \n",
              "4  1erTrim2024  1.327252e+10   \n",
              "\n",
              "                                            geometry  cobertura  \n",
              "0  POLYGON ((1106181.991 2273545.301, 1106202.373...       True  \n",
              "1  POLYGON ((1115876.388 2252044.571, 1115939.958...       True  \n",
              "2  POLYGON ((1115347.288 2267907.628, 1115343.720...       True  \n",
              "3  POLYGON ((1110427.922 2273453.920, 1110419.600...       True  \n",
              "4  POLYGON ((1141638.155 2205987.606, 1141595.689...       True  "
            ],
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              "summary": "{\n  \"name\": \"agebs_final\",\n  \"rows\": 2303,\n  \"fields\": [\n    {\n      \"column\": \"CVEGEO\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 2030,\n        \"samples\": [\n          \"0200400018803\",\n          \"0200400015372\",\n          \"0200301551349\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_ENT\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"02\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_MUN\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"001\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": 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\"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Periodo\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"1erTrim2024\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Area\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.907838135870171e-06,\n        \"min\": 13272522475.674534,\n        \"max\": 13272522475.674534,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          13272522475.674534\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"geometry\",\n      \"properties\": {\n        \"dtype\": \"geometry\",\n        \"num_unique_values\": 2303,\n        \"samples\": [\n          \"POLYGON ((1094541.9800999984 2349253.3059, 1094564.299800001 2349251.2250000015, 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            }
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Eliminamos duplicados"
      ],
      "metadata": {
        "id": "kfiNyd7NdoE1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_final.loc[agebs_final.duplicated(['CVE_AGEB']), 'cobertura'] = 'parcial'"
      ],
      "metadata": {
        "id": "tTwx_EyMe_Gt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "filtro = agebs_final['cobertura'] == 'parcial'"
      ],
      "metadata": {
        "id": "LYl5AWeyfQuV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_final = agebs_final[~filtro]"
      ],
      "metadata": {
        "id": "FH60eWSZfToc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_final = agebs_final[['CVEGEO','CVE_MUN','CVE_LOC','CVE_AGEB','Ambito','Area','geometry','cobertura']]\n",
        "agebs_final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "BRRtGwP6r3iD",
        "outputId": "896158a2-b4e3-4407-e810-e0e3fc442d7d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "             CVEGEO CVE_MUN CVE_LOC CVE_AGEB  Ambito          Area  \\\n",
              "0     0200102472200     001    0247     2200  Urbana  1.327252e+10   \n",
              "1     0200101399918     001    0139     9918  Urbana  1.327252e+10   \n",
              "2     020010001795A     001    0001     795A  Urbana  1.327252e+10   \n",
              "3     0200100011490     001    0001     1490  Urbana  1.327252e+10   \n",
              "4     0200102431819     001    0243     1819  Urbana  1.327252e+10   \n",
              "...             ...     ...     ...      ...     ...           ...   \n",
              "2298      020069492     006    0000     9492   Rural           NaN   \n",
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              "2301      020069191     006    0000     9191   Rural           NaN   \n",
              "2302      020069045     006    0000     9045   Rural           NaN   \n",
              "\n",
              "                                               geometry cobertura  \n",
              "0     POLYGON ((1106181.991 2273545.301, 1106202.373...      True  \n",
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              "4     POLYGON ((1141638.155 2205987.606, 1141595.689...      True  \n",
              "...                                                 ...       ...  \n",
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              "2300  POLYGON ((1425237.082 1912947.062, 1425247.290...     False  \n",
              "2301  POLYGON ((1426339.274 1910250.059, 1426350.260...     False  \n",
              "2302  POLYGON ((1425844.826 1911625.437, 1425859.037...     False  \n",
              "\n",
              "[2030 rows x 8 columns]"
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "agebs_final",
              "summary": "{\n  \"name\": \"agebs_final\",\n  \"rows\": 2030,\n  \"fields\": [\n    {\n      \"column\": \"CVEGEO\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 2030,\n        \"samples\": [\n          \"0200400018803\",\n          \"0200400015372\",\n          \"0200301551349\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_MUN\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"001\",\n          \"002\",\n          \"006\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_LOC\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 44,\n        \"samples\": [\n          \"0585\",\n          \"0340\",\n          \"1603\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_AGEB\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 2030,\n        \"samples\": [\n          \"8803\",\n          \"5372\",\n          \"1349\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ambito\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Rural\",\n          \"Urbana\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Area\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.907838135870171e-06,\n        \"min\": 13272522475.674534,\n        \"max\": 13272522475.674534,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          13272522475.674534\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"geometry\",\n      \"properties\": {\n        \"dtype\": \"geometry\",\n        \"num_unique_values\": 2030,\n        \"samples\": [\n          \"POLYGON ((1095812.9074999988 2348837.307500001, 1095788.9433000013 2348819.2795, 1095768.9548999965 2348819.4838999994, 1095749.887699999 2348818.0177000016, 1095727.2334999964 2348819.974300001, 1095713.9433000013 2348819.4866999984, 1095670.373499997 2348829.2313, 1095657.3410999998 2348831.967700001, 1095528.9777000025 2348840.600499999, 1095491.1963 2348837.107500002, 1095457.129900001 2348835.4886999987, 1095443.0539000034 2348828.9323000014, 1095425.063500002 2348825.1213000007, 1095413.2092999965 2348829.9891000018, 1095406.0261000022 2348835.7980999984, 1095399.8215000033 2348839.355700001, 1095392.201899998 2348841.6581000015, 1095383.844899997 2348843.892499998, 1095377.4378999993 2348845.3880999982, 1095373.3893000036 2348849.356899999, 1095363.4807000011 2348854.9869000018, 1095368.1563000008 2348862.649099998, 1095381.8012999967 2348887.1261, 1095388.2641000003 2348894.0700999983, 1095396.259499997 2348899.351300001, 1095359.250699997 2348907.5297, 1095358.7930999994 2348913.9345000014, 1095348.3043000028 2348960.219300002, 1095334.6665000021 2349015.4639, 1095271.2911000028 2349112.4459000006, 1095270.1793000028 2349126.2716999985, 1095270.4249000028 2349138.4329000004, 1095274.6743 2349154.7470999993, 1095286.4466999993 2349199.2217000015, 1095292.4877000004 2349208.2404999994, 1095298.7901000008 2349219.7710999995, 1095303.175499998 2349234.4241000004, 1095313.9100999981 2349255.2892999984, 1095329.867700003 2349318.8647000007, 1095364.4631000012 2349337.7773, 1095352.387500003 2349354.782499999, 1095330.6468999982 2349355.149099998, 1095352.3172999993 2349486.609099999, 1095352.2748999968 2349492.5779, 1095439.3747000024 2349437.5304999985, 1095926.6992999986 2349120.8561000004, 1095923.1662999988 2349078.4668999985, 1095917.6053000018 2349011.7441000007, 1095868.2652999982 2349019.910700001, 1095876.5980999991 2348993.5108999982, 1095876.5222999975 2348991.771899998, 1095876.2003000006 2348984.384300001, 1095878.0886999965 2348974.5632999986, 1095878.184299998 2348974.065299999, 1095882.1526999995 2348964.143100001, 1095881.3598999977 2348955.013700001, 1095878.925300002 2348945.6757000014, 1095877.4437000006 2348936.3621000014, 1095874.9034999982 2348927.2597000003, 1095870.0361000001 2348917.0989000015, 1095862.627700001 2348912.443500001, 1095873.4243 2348819.9661, 1095812.9074999988 2348837.307500001))\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cobertura\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Recuento total de cobertura"
      ],
      "metadata": {
        "id": "NhAoTCcIgX-1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_final.groupby('cobertura').agg({\n",
        "    'CVE_AGEB': 'count'\n",
        "    })"
      ],
      "metadata": {
        "id": "41TvgaOAfN4l",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "4637f8c1-9360-4e07-b7d1-b50b2092d5eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           CVE_AGEB\n",
              "cobertura          \n",
              "False            81\n",
              "True           1949"
            ],
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              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"    })\",\n  \"rows\": 2,\n  \"fields\": [\n    {\n      \"column\": \"cobertura\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_AGEB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1320,\n        \"min\": 81,\n        \"max\": 1949,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1949,\n          81\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Recuento por ambito Rural o Urbano"
      ],
      "metadata": {
        "id": "HBImyTiMgjNa"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Rurales CON cobertura (173)"
      ],
      "metadata": {
        "id": "Vpo-L7k7oXKf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#  mostrar datos con un filtro de dos condiciones\n",
        "\n",
        "agebs_final[ (agebs_final['Ambito'] == 'Rural') & (agebs_final['cobertura'] == True) ]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "ugFMtnoiFHVl",
        "outputId": "05a77539-d404-44e4-9cb5-8afcf76b3e0a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         CVEGEO CVE_MUN CVE_LOC CVE_AGEB Ambito          Area  \\\n",
              "1776  020016260     001    0000     6260  Rural  1.327252e+10   \n",
              "1777  020016434     001    0000     6434  Rural  1.327252e+10   \n",
              "1778  020016650     001    0000     6650  Rural  1.327252e+10   \n",
              "1779  020016383     001    0000     6383  Rural  1.327252e+10   \n",
              "1780  020016400     001    0000     6400  Rural  1.327252e+10   \n",
              "...         ...     ...     ...      ...    ...           ...   \n",
              "1944  020060982     006    0000     0982  Rural  1.327252e+10   \n",
              "1945  020061020     006    0000     1020  Rural  1.327252e+10   \n",
              "1946  020061035     006    0000     1035  Rural  1.327252e+10   \n",
              "1947  020061054     006    0000     1054  Rural  1.327252e+10   \n",
              "1948  020061139     006    0000     1139  Rural  1.327252e+10   \n",
              "\n",
              "                                               geometry cobertura  \n",
              "1776  MULTIPOLYGON (((1144857.213 2294314.533, 11446...      True  \n",
              "1777  MULTIPOLYGON (((1142370.378 2266393.128, 11423...      True  \n",
              "1778  MULTIPOLYGON (((1199681.108 2212145.928, 11997...      True  \n",
              "1779  MULTIPOLYGON (((1153800.800 2273007.024, 11538...      True  \n",
              "1780  MULTIPOLYGON (((1102353.916 2277527.328, 11023...      True  \n",
              "...                                                 ...       ...  \n",
              "1944  MULTIPOLYGON (((1177852.805 2114230.607, 11778...      True  \n",
              "1945  MULTIPOLYGON (((1160784.467 2106392.172, 11607...      True  \n",
              "1946  MULTIPOLYGON (((1182316.893 2099951.953, 11823...      True  \n",
              "1947  MULTIPOLYGON (((1175823.743 2092033.027, 11758...      True  \n",
              "1948  MULTIPOLYGON (((1318480.444 1830071.228, 13185...      True  \n",
              "\n",
              "[173 rows x 8 columns]"
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              "      <th></th>\n",
              "      <th>CVEGEO</th>\n",
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              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1144857.213 2294314.533, 11446...</td>\n",
              "      <td>True</td>\n",
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              "      <th>1777</th>\n",
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              "      <td>6650</td>\n",
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              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1199681.108 2212145.928, 11997...</td>\n",
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              "      <th>1779</th>\n",
              "      <td>020016383</td>\n",
              "      <td>001</td>\n",
              "      <td>0000</td>\n",
              "      <td>6383</td>\n",
              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1153800.800 2273007.024, 11538...</td>\n",
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              "      <td>1.327252e+10</td>\n",
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              "      <td>True</td>\n",
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              "      <td>0982</td>\n",
              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1177852.805 2114230.607, 11778...</td>\n",
              "      <td>True</td>\n",
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              "      <th>1945</th>\n",
              "      <td>020061020</td>\n",
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              "      <td>0000</td>\n",
              "      <td>1020</td>\n",
              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1160784.467 2106392.172, 11607...</td>\n",
              "      <td>True</td>\n",
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              "    <tr>\n",
              "      <th>1946</th>\n",
              "      <td>020061035</td>\n",
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              "      <td>1035</td>\n",
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              "      <td>1.327252e+10</td>\n",
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              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1175823.743 2092033.027, 11758...</td>\n",
              "      <td>True</td>\n",
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              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1318480.444 1830071.228, 13185...</td>\n",
              "      <td>True</td>\n",
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              "<p>173 rows × 8 columns</p>\n",
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            }
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Urbanas CON cobertura (1776)"
      ],
      "metadata": {
        "id": "r647mpEQoiJA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_final[ (agebs_final['Ambito'] == 'Urbana') & (agebs_final['cobertura'] == True) ]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "96XztLy0FMh7",
        "outputId": "68da6c5c-3817-4af3-a43e-610c0ef19dc9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "             CVEGEO CVE_MUN CVE_LOC CVE_AGEB  Ambito          Area  \\\n",
              "0     0200102472200     001    0247     2200  Urbana  1.327252e+10   \n",
              "1     0200101399918     001    0139     9918  Urbana  1.327252e+10   \n",
              "2     020010001795A     001    0001     795A  Urbana  1.327252e+10   \n",
              "3     0200100011490     001    0001     1490  Urbana  1.327252e+10   \n",
              "4     0200102431819     001    0243     1819  Urbana  1.327252e+10   \n",
              "...             ...     ...     ...      ...     ...           ...   \n",
              "1771  020060040022A     006    0040     022A  Urbana  1.327252e+10   \n",
              "1772  0200608630874     006    0863     0874  Urbana  1.327252e+10   \n",
              "1773  0200600820268     006    0082     0268  Urbana  1.327252e+10   \n",
              "1774  0200608630889     006    0863     0889  Urbana  1.327252e+10   \n",
              "1775  0200602480499     006    0248     0499  Urbana  1.327252e+10   \n",
              "\n",
              "                                               geometry cobertura  \n",
              "0     POLYGON ((1106181.991 2273545.301, 1106202.373...      True  \n",
              "1     POLYGON ((1115876.388 2252044.571, 1115939.958...      True  \n",
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              "3     POLYGON ((1110427.922 2273453.920, 1110419.600...      True  \n",
              "4     POLYGON ((1141638.155 2205987.606, 1141595.689...      True  \n",
              "...                                                 ...       ...  \n",
              "1771  POLYGON ((1152434.059 2151104.233, 1152470.684...      True  \n",
              "1772  POLYGON ((1158765.050 2139193.705, 1158769.405...      True  \n",
              "1773  POLYGON ((1157932.691 2135385.228, 1157893.400...      True  \n",
              "1774  POLYGON ((1158915.803 2137229.920, 1158918.349...      True  \n",
              "1775  POLYGON ((1158598.248 2144660.203, 1158504.144...      True  \n",
              "\n",
              "[1776 rows x 8 columns]"
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            }
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Rurales SIN cobertura (81)"
      ],
      "metadata": {
        "id": "jc44EYmBooqM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "agebs_final[ (agebs_final['Ambito'] == 'Rural') & (agebs_final['cobertura'] == False) ]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "bWviGC7uGWLP",
        "outputId": "cc4d3b25-5102-4a58-ba09-7e934514e42d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         CVEGEO CVE_MUN CVE_LOC CVE_AGEB Ambito  Area  \\\n",
              "2059  020017095     001    0000     7095  Rural   NaN   \n",
              "2060  020017112     001    0000     7112  Rural   NaN   \n",
              "2062  020016627     001    0000     6627  Rural   NaN   \n",
              "2073  020016720     001    0000     6720  Rural   NaN   \n",
              "2076  020016398     001    0000     6398  Rural   NaN   \n",
              "...         ...     ...     ...      ...    ...   ...   \n",
              "2298  020069492     006    0000     9492  Rural   NaN   \n",
              "2299  020069505     006    0000     9505  Rural   NaN   \n",
              "2300  020069172     006    0000     9172  Rural   NaN   \n",
              "2301  020069191     006    0000     9191  Rural   NaN   \n",
              "2302  020069045     006    0000     9045  Rural   NaN   \n",
              "\n",
              "                                               geometry cobertura  \n",
              "2059  POLYGON ((1267198.704 2053317.397, 1262218.510...     False  \n",
              "2060  POLYGON ((1347489.496 1977203.061, 1344949.233...     False  \n",
              "2062  POLYGON ((1216957.719 2216803.340, 1216858.473...     False  \n",
              "2073  POLYGON ((1217286.095 2203330.427, 1217286.897...     False  \n",
              "2076  POLYGON ((1196866.189 2252678.251, 1189764.708...     False  \n",
              "...                                                 ...       ...  \n",
              "2298  POLYGON ((1436927.023 1888302.585, 1436914.321...     False  \n",
              "2299  POLYGON ((1303089.052 1896091.986, 1303091.414...     False  \n",
              "2300  POLYGON ((1425237.082 1912947.062, 1425247.290...     False  \n",
              "2301  POLYGON ((1426339.274 1910250.059, 1426350.260...     False  \n",
              "2302  POLYGON ((1425844.826 1911625.437, 1425859.037...     False  \n",
              "\n",
              "[81 rows x 8 columns]"
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          "metadata": {},
          "execution_count": 58
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      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Urbanas SIN Cobertura (Ninguna)"
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      "metadata": {
        "id": "AvA8iKvDouS0"
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            "text/plain": [
              "Empty GeoDataFrame\n",
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      "execution_count": null,
      "outputs": [
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          "data": {
            "text/plain": [
              "             CVEGEO CVE_MUN CVE_LOC CVE_AGEB  Ambito          Area  \\\n",
              "0     0200102472200     001    0247     2200  Urbana  1.327252e+10   \n",
              "1     0200101399918     001    0139     9918  Urbana  1.327252e+10   \n",
              "2     020010001795A     001    0001     795A  Urbana  1.327252e+10   \n",
              "3     0200100011490     001    0001     1490  Urbana  1.327252e+10   \n",
              "4     0200102431819     001    0243     1819  Urbana  1.327252e+10   \n",
              "...             ...     ...     ...      ...     ...           ...   \n",
              "1944      020060982     006    0000     0982   Rural  1.327252e+10   \n",
              "1945      020061020     006    0000     1020   Rural  1.327252e+10   \n",
              "1946      020061035     006    0000     1035   Rural  1.327252e+10   \n",
              "1947      020061054     006    0000     1054   Rural  1.327252e+10   \n",
              "1948      020061139     006    0000     1139   Rural  1.327252e+10   \n",
              "\n",
              "                                               geometry cobertura  \n",
              "0     POLYGON ((1106181.991 2273545.301, 1106202.373...      True  \n",
              "1     POLYGON ((1115876.388 2252044.571, 1115939.958...      True  \n",
              "2     POLYGON ((1115347.288 2267907.628, 1115343.720...      True  \n",
              "3     POLYGON ((1110427.922 2273453.920, 1110419.600...      True  \n",
              "4     POLYGON ((1141638.155 2205987.606, 1141595.689...      True  \n",
              "...                                                 ...       ...  \n",
              "1944  MULTIPOLYGON (((1177852.805 2114230.607, 11778...      True  \n",
              "1945  MULTIPOLYGON (((1160784.467 2106392.172, 11607...      True  \n",
              "1946  MULTIPOLYGON (((1182316.893 2099951.953, 11823...      True  \n",
              "1947  MULTIPOLYGON (((1175823.743 2092033.027, 11758...      True  \n",
              "1948  MULTIPOLYGON (((1318480.444 1830071.228, 13185...      True  \n",
              "\n",
              "[1949 rows x 8 columns]"
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              "      <td>0200100011490</td>\n",
              "      <td>001</td>\n",
              "      <td>0001</td>\n",
              "      <td>1490</td>\n",
              "      <td>Urbana</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>POLYGON ((1110427.922 2273453.920, 1110419.600...</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0200102431819</td>\n",
              "      <td>001</td>\n",
              "      <td>0243</td>\n",
              "      <td>1819</td>\n",
              "      <td>Urbana</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>POLYGON ((1141638.155 2205987.606, 1141595.689...</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1944</th>\n",
              "      <td>020060982</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>0982</td>\n",
              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1177852.805 2114230.607, 11778...</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1945</th>\n",
              "      <td>020061020</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>1020</td>\n",
              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1160784.467 2106392.172, 11607...</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1946</th>\n",
              "      <td>020061035</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>1035</td>\n",
              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1182316.893 2099951.953, 11823...</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1947</th>\n",
              "      <td>020061054</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>1054</td>\n",
              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1175823.743 2092033.027, 11758...</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1948</th>\n",
              "      <td>020061139</td>\n",
              "      <td>006</td>\n",
              "      <td>0000</td>\n",
              "      <td>1139</td>\n",
              "      <td>Rural</td>\n",
              "      <td>1.327252e+10</td>\n",
              "      <td>MULTIPOLYGON (((1318480.444 1830071.228, 13185...</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1949 rows × 8 columns</p>\n",
              "</div>\n",
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              "\n",
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              "  .colab-df-quickchart:hover {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"agebs_final[agebs_final\",\n  \"rows\": 1949,\n  \"fields\": [\n    {\n      \"column\": \"CVEGEO\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1949,\n        \"samples\": [\n          \"0200500010932\",\n          \"0200400013060\",\n          \"0200400012306\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_MUN\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"001\",\n          \"002\",\n          \"006\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_LOC\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 44,\n        \"samples\": [\n          \"0585\",\n          \"0340\",\n          \"1603\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CVE_AGEB\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1949,\n        \"samples\": [\n          \"0932\",\n          \"3060\",\n          \"2306\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ambito\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Rural\",\n          \"Urbana\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Area\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.907838135870171e-06,\n        \"min\": 13272522475.674534,\n        \"max\": 13272522475.674534,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          13272522475.674534\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"geometry\",\n      \"properties\": {\n        \"dtype\": \"geometry\",\n        \"num_unique_values\": 1949,\n        \"samples\": [\n          \"POLYGON ((1078958.1040000021 2334426.5956999995, 1078899.5533000007 2334351.2683999985, 1078829.1493000016 2334293.9827000014, 1078769.0755999982 2334263.6022000015, 1078755.6696000025 2334266.8786999993, 1078654.9333000034 2334363.9745999984, 1078640.6048000008 2334369.1371, 1078636.0437000021 2334370.3739, 1078626.3369000033 2334373.0058999993, 1078590.988499999 2334385.7721999995, 1078553.4953999966 2334401.606899999, 1078527.4701000005 2334409.0997, 1078500.1018999964 2334411.7225, 1078476.0890000015 2334402.0102999993, 1078463.6125999987 2334391.299800001, 1078458.2326999977 2334381.7062, 1078454.7007 2334366.133200001, 1078451.925300002 2334336.0560000017, 1078446.233599998 2334314.0901000015, 1078445.9746999964 2334313.8561000004, 1078431.9596000016 2334301.1911999993, 1078418.1916999966 2334294.1372999996, 1078417.7971 2334396.2029, 1078417.3924999982 2334487.638700001, 1078370.8051000014 2334488.6702999994, 1078373.8905000016 2334542.5047000013, 1078378.0900999978 2334618.104200002, 1078379.8619000018 2334644.1515000015, 1078475.8109000027 2334629.094900001, 1078485.2924999967 2334626.876699999, 1078512.0298999995 2334619.3225000016, 1078539.269100003 2334607.0339, 1078566.641900003 2334590.041099999, 1078626.0287000015 2334573.4879, 1078881.0803000033 2334503.971099999, 1078944.804700002 2334486.5251, 1078983.8923000023 2334476.043299999, 1078958.1040000021 2334426.5956999995))\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cobertura\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          true\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "aU9Xrf_CtQVW"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}