INMERSION_DATOS_AULA_2.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ahcamachod/inmersion-en-datos/blob/aula-2/INMERSION_DATOS_AULA_2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qGW8k7mWhP7O"
      },
      "source": [
        "Bienvenido a nuestro primer encuentro de inmersión de datos."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y2BMxIBqhcl7",
        "outputId": "f5567dfb-4052-41ec-a38a-6b936e29174f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "id": "S73Bs_z6j2QX",
        "outputId": "4b831b26-43ba-4a3d-ce12-4323cf30379b"
      },
      "outputs": [
        {
          "data": {
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              "\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>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Baños</th>\n",
              "      <th>Área</th>\n",
              "      <th>Barrio</th>\n",
              "      <th>UPZ</th>\n",
              "      <th>Valor</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Zona Noroccidental</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>70</td>\n",
              "      <td>Zona Noroccidental</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 360.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Castilla</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>170</td>\n",
              "      <td>Castilla</td>\n",
              "      <td>KENNEDY: Castilla + Bavaria</td>\n",
              "      <td>$ 670.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>144</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 1.120.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Usaquén</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>154</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 890.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Bella Suiza</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>128</td>\n",
              "      <td>Bella Suiza</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 970.000.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Tipo                                 Descripcion  Habitaciones  \\\n",
              "0  Apartamento  Apartamento en venta en Zona Noroccidental             3   \n",
              "1         Casa                   Casa en venta en Castilla             4   \n",
              "2  Apartamento     Apartamento en venta en Chico Reservado             3   \n",
              "3  Apartamento             Apartamento en venta en Usaquén             3   \n",
              "4  Apartamento         Apartamento en venta en Bella Suiza             2   \n",
              "\n",
              "   Baños  Área              Barrio                                    UPZ  \\\n",
              "0      2    70  Zona Noroccidental     CHAPINERO: Pardo Rubio + Chapinero   \n",
              "1      3   170            Castilla            KENNEDY: Castilla + Bavaria   \n",
              "2      3   144     Chico Reservado     CHAPINERO: Chicó Lago + El Refugio   \n",
              "3      2   154             Usaquén                                Usaquén   \n",
              "4      3   128         Bella Suiza  USAQUÉN: Country Club + Santa Bárbara   \n",
              "\n",
              "             Valor  \n",
              "0    $ 360.000.000  \n",
              "1    $ 670.000.000  \n",
              "2  $ 1.120.000.000  \n",
              "3    $ 890.000.000  \n",
              "4    $ 970.000.000  "
            ]
          },
          "execution_count": 1,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "\n",
        "inmuebles = pd.read_csv('./inmuebles_bogota.csv') \n",
        "inmuebles.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qkcJjAQrmyfN",
        "outputId": "70d24523-058c-49fb-ca74-e4e9526e33cf"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(9520, 8)"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K-4LMluEnha_",
        "outputId": "41397e9d-34f1-4146-eead-7aa085322789"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Index(['Tipo', 'Descripcion', 'Habitaciones', 'Baños', 'Área', 'Barrio', 'UPZ',\n",
              "       'Valor'],\n",
              "      dtype='object')"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "X2nLnlFIn2EM",
        "outputId": "707d8466-e0a9-419e-f499-96c7a348a7c7"
      },
      "outputs": [
        {
          "data": {
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              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Barrio</th>\n",
              "      <th>UPZ</th>\n",
              "      <th>Valor</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>483</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Usaquén</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>82</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 340.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>902</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chapinero</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>73</td>\n",
              "      <td>Chapinero</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 483.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2106</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Barrios Unidos</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>230</td>\n",
              "      <td>Barrios Unidos</td>\n",
              "      <td>Los Andes</td>\n",
              "      <td>$ 1.100.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4130</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Kennedy</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>51</td>\n",
              "      <td>Kennedy</td>\n",
              "      <td>Kennedy Central</td>\n",
              "      <td>$ 169.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5243</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chapinero</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>396</td>\n",
              "      <td>Chapinero</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 2.750.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4539</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Barrios Unidos</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>83</td>\n",
              "      <td>Barrios Unidos</td>\n",
              "      <td>Los Andes</td>\n",
              "      <td>$ 465.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>104</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 1.100.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5033</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Usaquén</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>63</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 240.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>641</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Cedritos</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>176</td>\n",
              "      <td>Cedritos</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 880.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4889</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Norte</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>57</td>\n",
              "      <td>Chico Norte</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 500.000.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Tipo                              Descripcion  Habitaciones  \\\n",
              "483   Apartamento          Apartamento en venta en Usaquén             3   \n",
              "902   Apartamento        Apartamento en venta en Chapinero             2   \n",
              "2106  Apartamento   Apartamento en venta en Barrios Unidos             3   \n",
              "4130  Apartamento          Apartamento en venta en Kennedy             3   \n",
              "5243  Apartamento        Apartamento en venta en Chapinero             4   \n",
              "4539  Apartamento   Apartamento en venta en Barrios Unidos             2   \n",
              "143   Apartamento  Apartamento en venta en Chico Reservado             2   \n",
              "5033  Apartamento          Apartamento en venta en Usaquén             3   \n",
              "641   Apartamento         Apartamento en venta en Cedritos             3   \n",
              "4889  Apartamento      Apartamento en venta en Chico Norte             1   \n",
              "\n",
              "      Banos  Area           Barrio                                 UPZ  \\\n",
              "483       2    82          Usaquén                             Usaquén   \n",
              "902       2    73        Chapinero  CHAPINERO: Pardo Rubio + Chapinero   \n",
              "2106      4   230   Barrios Unidos                           Los Andes   \n",
              "4130      1    51          Kennedy                     Kennedy Central   \n",
              "5243      6   396        Chapinero  CHAPINERO: Pardo Rubio + Chapinero   \n",
              "4539      2    83   Barrios Unidos                           Los Andes   \n",
              "143       4   104  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "5033      2    63          Usaquén                             Usaquén   \n",
              "641       4   176         Cedritos                             Usaquén   \n",
              "4889      2    57      Chico Norte  CHAPINERO: Chicó Lago + El Refugio   \n",
              "\n",
              "                Valor  \n",
              "483     $ 340.000.000  \n",
              "902     $ 483.000.000  \n",
              "2106  $ 1.100.000.000  \n",
              "4130    $ 169.000.000  \n",
              "5243  $ 2.750.000.000  \n",
              "4539    $ 465.000.000  \n",
              "143   $ 1.100.000.000  \n",
              "5033    $ 240.000.000  \n",
              "641     $ 880.000.000  \n",
              "4889    $ 500.000.000  "
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "columnas = {'Baños':'Banos','Área':'Area'}\n",
        "inmuebles = inmuebles.rename(columns=columnas)\n",
        "inmuebles.sample(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KJT8oyJgo2hU",
        "outputId": "ab8a3065-0528-42fd-caba-f8862ead60cf"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9520 entries, 0 to 9519\n",
            "Data columns (total 8 columns):\n",
            " #   Column        Non-Null Count  Dtype \n",
            "---  ------        --------------  ----- \n",
            " 0   Tipo          9520 non-null   object\n",
            " 1   Descripcion   9520 non-null   object\n",
            " 2   Habitaciones  9520 non-null   int64 \n",
            " 3   Banos         9520 non-null   int64 \n",
            " 4   Area          9520 non-null   int64 \n",
            " 5   Barrio        9520 non-null   object\n",
            " 6   UPZ           9478 non-null   object\n",
            " 7   Valor         9520 non-null   object\n",
            "dtypes: int64(3), object(5)\n",
            "memory usage: 595.1+ KB\n"
          ]
        }
      ],
      "source": [
        "inmuebles.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eyrj-ItzplxW",
        "outputId": "327a14b3-831f-4714-b37b-9c18f77d8528"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Tipo                                Apartamento\n",
              "Descripcion     Apartamento en venta en Kennedy\n",
              "Habitaciones                                  2\n",
              "Banos                                         1\n",
              "Area                                         42\n",
              "Barrio                                  Kennedy\n",
              "UPZ                             Kennedy Central\n",
              "Valor                             $ 116.100.000\n",
              "Name: 300, dtype: object"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.iloc[300]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "id": "NiK43WPcr0GG",
        "outputId": "26a4823d-a49d-4f20-83eb-227a207493cb"
      },
      "outputs": [
        {
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Barrio</th>\n",
              "      <th>UPZ</th>\n",
              "      <th>Valor</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>300</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Kennedy</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>42</td>\n",
              "      <td>Kennedy</td>\n",
              "      <td>Kennedy Central</td>\n",
              "      <td>$ 116.100.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>301</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Norte</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>95</td>\n",
              "      <td>Chico Norte</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 980.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>302</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Kennedy</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>54</td>\n",
              "      <td>Kennedy</td>\n",
              "      <td>Kennedy Central</td>\n",
              "      <td>$ 237.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>303</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Kennedy</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>67</td>\n",
              "      <td>Kennedy</td>\n",
              "      <td>Kennedy Central</td>\n",
              "      <td>$ 320.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>304</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Cedritos</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>132</td>\n",
              "      <td>Cedritos</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 530.000.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9b1b806a-34a1-41c7-8552-792c69cfca85')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9b1b806a-34a1-41c7-8552-792c69cfca85 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9b1b806a-34a1-41c7-8552-792c69cfca85');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "            Tipo                          Descripcion  Habitaciones  Banos  \\\n",
              "300  Apartamento      Apartamento en venta en Kennedy             2      1   \n",
              "301  Apartamento  Apartamento en venta en Chico Norte             2      2   \n",
              "302  Apartamento      Apartamento en venta en Kennedy             3      2   \n",
              "303  Apartamento      Apartamento en venta en Kennedy             3      2   \n",
              "304  Apartamento     Apartamento en venta en Cedritos             4      4   \n",
              "\n",
              "     Area       Barrio                                 UPZ          Valor  \n",
              "300    42      Kennedy                     Kennedy Central  $ 116.100.000  \n",
              "301    95  Chico Norte  CHAPINERO: Chicó Lago + El Refugio  $ 980.000.000  \n",
              "302    54      Kennedy                     Kennedy Central  $ 237.000.000  \n",
              "303    67      Kennedy                     Kennedy Central  $ 320.000.000  \n",
              "304   132     Cedritos                             Usaquén  $ 530.000.000  "
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.iloc[300:305]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "65he94kAsMXL",
        "outputId": "c5f4c8d9-668e-45f8-d900-055b21d147fa"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'$ 116.100.000'"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles['Valor'][300]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iFH5bi8EsbRe",
        "outputId": "ec6920f5-1f96-4831-ecaa-35f96a1673ed"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "pandas.core.series.Series"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(inmuebles['Valor'][300:305])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "601xMJ2ashKu",
        "outputId": "0f16ac4f-11c8-4a46-9aa9-96c265d78dd4"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Index(['Tipo', 'Descripcion', 'Habitaciones', 'Banos', 'Area', 'Barrio', 'UPZ',\n",
              "       'Valor'],\n",
              "      dtype='object')"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I1pyNc9Xs85S",
        "outputId": "f95e05eb-5f6f-4728-83c8-3db7ee90f890"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "146.66470588235293"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.Area.mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 641
        },
        "id": "iYqOIwb_tPfj",
        "outputId": "963f5ee5-c95a-4066-c3dc-3edd6a4866fb"
      },
      "outputs": [
        {
          "data": {
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              "\n",
              "  <div id=\"df-e2bad7e0-5684-480d-a14f-03a757c5e784\">\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
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              "      <th>Valor</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7284</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Bosa</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>36</td>\n",
              "      <td>Bosa</td>\n",
              "      <td>Bosa Central</td>\n",
              "      <td>$ 98.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8347</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Zona Noroccidental</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>73</td>\n",
              "      <td>Zona Noroccidental</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 290.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4854</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Suba</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>58</td>\n",
              "      <td>Suba</td>\n",
              "      <td>Suba</td>\n",
              "      <td>$ 260.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5992</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>160</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 980.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7994</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Santa Barbara</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>130</td>\n",
              "      <td>Santa Barbara</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 600.000.000</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>9216</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Niza</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>50</td>\n",
              "      <td>Niza</td>\n",
              "      <td>Niza</td>\n",
              "      <td>$ 170.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6595</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Cedritos</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>69</td>\n",
              "      <td>Cedritos</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 330.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4412</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Suba</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>124</td>\n",
              "      <td>Suba</td>\n",
              "      <td>Suba</td>\n",
              "      <td>$ 800.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5623</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Bogotá D.C</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>566</td>\n",
              "      <td>Bogotá D.C</td>\n",
              "      <td>Ciudad Salitre Occidental</td>\n",
              "      <td>$ 2.800.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1795</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Hayuelos</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>77</td>\n",
              "      <td>Hayuelos</td>\n",
              "      <td>Modelia</td>\n",
              "      <td>$ 360.000.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 8 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e2bad7e0-5684-480d-a14f-03a757c5e784')\"\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
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              "          const element = document.querySelector('#df-e2bad7e0-5684-480d-a14f-03a757c5e784');\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ],
            "text/plain": [
              "             Tipo                                 Descripcion  Habitaciones  \\\n",
              "7284  Apartamento                Apartamento en venta en Bosa             2   \n",
              "8347  Apartamento  Apartamento en venta en Zona Noroccidental             3   \n",
              "4854  Apartamento                Apartamento en venta en Suba             3   \n",
              "5992  Apartamento     Apartamento en venta en Chico Reservado             3   \n",
              "7994  Apartamento       Apartamento en venta en Santa Barbara             2   \n",
              "...           ...                                         ...           ...   \n",
              "9216  Apartamento                Apartamento en venta en Niza             2   \n",
              "6595  Apartamento            Apartamento en venta en Cedritos             2   \n",
              "4412  Apartamento                Apartamento en venta en Suba             3   \n",
              "5623         Casa                 Casa en venta en Bogotá D.C             4   \n",
              "1795  Apartamento            Apartamento en venta en Hayuelos             3   \n",
              "\n",
              "      Banos  Area              Barrio                                    UPZ  \\\n",
              "7284      1    36                Bosa                           Bosa Central   \n",
              "8347      2    73  Zona Noroccidental     CHAPINERO: Pardo Rubio + Chapinero   \n",
              "4854      2    58                Suba                                   Suba   \n",
              "5992      3   160     Chico Reservado     CHAPINERO: Chicó Lago + El Refugio   \n",
              "7994      2   130       Santa Barbara  USAQUÉN: Country Club + Santa Bárbara   \n",
              "...     ...   ...                 ...                                    ...   \n",
              "9216      1    50                Niza                                   Niza   \n",
              "6595      2    69            Cedritos                                Usaquén   \n",
              "4412      4   124                Suba                                   Suba   \n",
              "5623      5   566          Bogotá D.C              Ciudad Salitre Occidental   \n",
              "1795      2    77            Hayuelos                                Modelia   \n",
              "\n",
              "                Valor  \n",
              "7284     $ 98.000.000  \n",
              "8347    $ 290.000.000  \n",
              "4854    $ 260.000.000  \n",
              "5992    $ 980.000.000  \n",
              "7994    $ 600.000.000  \n",
              "...               ...  \n",
              "9216    $ 170.000.000  \n",
              "6595    $ 330.000.000  \n",
              "4412    $ 800.000.000  \n",
              "5623  $ 2.800.000.000  \n",
              "1795    $ 360.000.000  \n",
              "\n",
              "[100 rows x 8 columns]"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.sample(100)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YY-zAytFuBsA",
        "outputId": "8c08827a-e7dd-4f56-a74e-5b6d0c6354f2"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0       False\n",
              "1       False\n",
              "2        True\n",
              "3       False\n",
              "4       False\n",
              "        ...  \n",
              "9515    False\n",
              "9516    False\n",
              "9517    False\n",
              "9518    False\n",
              "9519    False\n",
              "Name: Barrio, Length: 9520, dtype: bool"
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "(inmuebles.Barrio == 'Chico Reservado')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3OJg8M1TuwcZ",
        "outputId": "4e4becb5-55bb-44a7-968a-e4d33de6bf9f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "225"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "sum((inmuebles.Barrio == 'Chico Reservado'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HtT_ZLvGu_CP",
        "outputId": "e1a40547-8f08-4d93-9514-c1c21cec437c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "pandas.core.series.Series"
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles_chico = (inmuebles.Barrio == 'Chico Reservado')\n",
        "type(inmuebles_chico)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "colab": {
          "base_uri": "https://localhost:8080/",
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        },
        "id": "mQJesAi_vLbs",
        "outputId": "c498cb6e-df9d-42ae-f07d-2fc194d62433"
      },
      "outputs": [
        {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Barrio</th>\n",
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              "      <th>2</th>\n",
              "      <td>Apartamento</td>\n",
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              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>144</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 1.120.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Apartamento</td>\n",
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              "      <td>1</td>\n",
              "      <td>64</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 495.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 495.000.000</td>\n",
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              "    <tr>\n",
              "      <th>126</th>\n",
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              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>150</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 1.300.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>104</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 1.100.000.000</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",
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              "    <tr>\n",
              "      <th>9299</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>148</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 780.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9335</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>176</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 850.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9341</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>118</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 700.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>49</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 200.000.000</td>\n",
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              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>390</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 3.200.000.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>225 rows × 8 columns</p>\n",
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            "text/plain": [
              "             Tipo                              Descripcion  Habitaciones  \\\n",
              "2     Apartamento  Apartamento en venta en Chico Reservado             3   \n",
              "39    Apartamento  Apartamento en venta en Chico Reservado             1   \n",
              "72    Apartamento  Apartamento en venta en Chico Reservado             1   \n",
              "126   Apartamento  Apartamento en venta en Chico Reservado             3   \n",
              "143   Apartamento  Apartamento en venta en Chico Reservado             2   \n",
              "...           ...                                      ...           ...   \n",
              "9299  Apartamento  Apartamento en venta en Chico Reservado             3   \n",
              "9335  Apartamento  Apartamento en venta en Chico Reservado             3   \n",
              "9341  Apartamento  Apartamento en venta en Chico Reservado             2   \n",
              "9472  Apartamento  Apartamento en venta en Chico Reservado             3   \n",
              "9506  Apartamento  Apartamento en venta en Chico Reservado             3   \n",
              "\n",
              "      Banos  Area           Barrio                                 UPZ  \\\n",
              "2         3   144  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "39        1    64  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "72        1    64  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "126       4   150  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "143       4   104  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "...     ...   ...              ...                                 ...   \n",
              "9299      3   148  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "9335      3   176  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "9341      3   118  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "9472      1    49  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "9506      4   390  Chico Reservado  CHAPINERO: Chicó Lago + El Refugio   \n",
              "\n",
              "                Valor  \n",
              "2     $ 1.120.000.000  \n",
              "39      $ 495.000.000  \n",
              "72      $ 495.000.000  \n",
              "126   $ 1.300.000.000  \n",
              "143   $ 1.100.000.000  \n",
              "...               ...  \n",
              "9299    $ 780.000.000  \n",
              "9335    $ 850.000.000  \n",
              "9341    $ 700.000.000  \n",
              "9472    $ 200.000.000  \n",
              "9506  $ 3.200.000.000  \n",
              "\n",
              "[225 rows x 8 columns]"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "chico_reservado = inmuebles[inmuebles_chico]\n",
        "chico_reservado"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j3IYReywvf26",
        "outputId": "db4a79a6-9ba4-44f6-824f-7faf39b6115f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "142.78666666666666"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "chico_reservado.Area.mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P7V5_WzXxCDl",
        "outputId": "9c69cd96-1c1e-4dfa-f3b2-05b0d8c192b3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "146.66470588235293"
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.Area.mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "54SeSdSFxZ9v",
        "outputId": "c0c7c971-a08e-4b23-e3fe-e7abdfa8be42"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "149"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "len(inmuebles.Barrio.value_counts())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aJz7RkSBxpVf",
        "outputId": "a57555c8-8cf6-48ff-807e-4cf9bd46c1e6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Usaquén               1105\n",
              "Zona Noroccidental     877\n",
              "Bosa                   589\n",
              "Kennedy                589\n",
              "Cedritos               554\n",
              "                      ... \n",
              "Colinas De Suba          1\n",
              "La Estanzuela            1\n",
              "Roma                     1\n",
              "Alameda                  1\n",
              "Prado Veraniego          1\n",
              "Name: Barrio, Length: 149, dtype: int64"
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.Barrio.value_counts()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eN0cDITxxtvH",
        "outputId": "e32ef258-5506-4e7f-f9ad-b57535ccad2b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "63"
            ]
          },
          "execution_count": 28,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "len(inmuebles.UPZ.value_counts())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 389
        },
        "id": "BcKfcc3nx9fg",
        "outputId": "b2c6f105-715e-4843-bdc8-0ab0f111668d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe758b604f0>"
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "inmuebles_barrio = inmuebles.Barrio.value_counts()\n",
        "inmuebles_barrio.plot.bar()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 371
        },
        "id": "EXzn-YDLybRx",
        "outputId": "060c6792-90b6-4bee-b637-5dec6614b6f0"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe7590b21f0>"
            ]
          },
          "execution_count": 30,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "inmuebles_barrio.head(10).plot.bar()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "owP_SeWgzaYR"
      },
      "source": [
        "**Desafío**\n",
        "\n",
        "\n",
        "1. Promedio de área de todos los inmuebles en los barrios en el dataset. El top 10.\n",
        "\n",
        "2. Consultar otros datos estadísticos, conteo, mediana, valores mínimo y máximo."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YFNuHdUZJJtL"
      },
      "source": [
        "#**Aula 2**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "id": "HuNvVUa2ypG4",
        "outputId": "5be50e45-6322-4df7-cfdd-07ad8caf5eb5"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Barrio</th>\n",
              "      <th>UPZ</th>\n",
              "      <th>Valor</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2434</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Suba</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>130</td>\n",
              "      <td>Suba</td>\n",
              "      <td>Suba</td>\n",
              "      <td>$ 390.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2876</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Bosa</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>47</td>\n",
              "      <td>Bosa</td>\n",
              "      <td>Bosa Central</td>\n",
              "      <td>$ 134.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>582</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Engativa</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>73</td>\n",
              "      <td>Engativa</td>\n",
              "      <td>Engativá</td>\n",
              "      <td>$ 360.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8247</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Engativa</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>300</td>\n",
              "      <td>Engativa</td>\n",
              "      <td>Engativá</td>\n",
              "      <td>$ 1.300.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8396</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Zona Noroccidental</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>75</td>\n",
              "      <td>Zona Noroccidental</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 310.000.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Tipo                                 Descripcion  Habitaciones  \\\n",
              "2434         Casa                       Casa en venta en Suba             4   \n",
              "2876  Apartamento                Apartamento en venta en Bosa             3   \n",
              "582          Casa                   Casa en venta en Engativa             3   \n",
              "8247         Casa                   Casa en venta en Engativa             6   \n",
              "8396  Apartamento  Apartamento en venta en Zona Noroccidental             3   \n",
              "\n",
              "      Banos  Area              Barrio                                 UPZ  \\\n",
              "2434      3   130                Suba                                Suba   \n",
              "2876      1    47                Bosa                        Bosa Central   \n",
              "582       3    73            Engativa                            Engativá   \n",
              "8247      4   300            Engativa                            Engativá   \n",
              "8396      2    75  Zona Noroccidental  CHAPINERO: Pardo Rubio + Chapinero   \n",
              "\n",
              "                Valor  \n",
              "2434    $ 390.000.000  \n",
              "2876    $ 134.000.000  \n",
              "582     $ 360.000.000  \n",
              "8247  $ 1.300.000.000  \n",
              "8396    $ 310.000.000  "
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.sample(5)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jt_0FzVFz30-",
        "outputId": "44655bfd-2974-44bd-df85-52007cd743af"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9520 entries, 0 to 9519\n",
            "Data columns (total 8 columns):\n",
            " #   Column        Non-Null Count  Dtype \n",
            "---  ------        --------------  ----- \n",
            " 0   Tipo          9520 non-null   object\n",
            " 1   Descripcion   9520 non-null   object\n",
            " 2   Habitaciones  9520 non-null   int64 \n",
            " 3   Banos         9520 non-null   int64 \n",
            " 4   Area          9520 non-null   int64 \n",
            " 5   Barrio        9520 non-null   object\n",
            " 6   UPZ           9478 non-null   object\n",
            " 7   Valor         9520 non-null   object\n",
            "dtypes: int64(3), object(5)\n",
            "memory usage: 595.1+ KB\n"
          ]
        }
      ],
      "source": [
        "inmuebles.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nz5JDL5LLh5A",
        "outputId": "7f57ad13-0735-4dfb-b929-463ed9b5fbbc"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "str"
            ]
          },
          "execution_count": 34,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(inmuebles.Valor[0])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fVgx7E33L9IJ",
        "outputId": "375a0a4d-54c5-4b50-fdf8-7d1495df5899"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0      $ 360.000.000$ 670.000.000$ 360.000.000\n",
              "1      $ 360.000.000$ 670.000.000$ 670.000.000\n",
              "2    $ 360.000.000$ 670.000.000$ 1.120.000.000\n",
              "3      $ 360.000.000$ 670.000.000$ 890.000.000\n",
              "4      $ 360.000.000$ 670.000.000$ 970.000.000\n",
              "Name: Valor, dtype: object"
            ]
          },
          "execution_count": 36,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.Valor[0]+inmuebles.Valor[1]+inmuebles.Valor[:5]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RRDkYvkjMWtA",
        "outputId": "5a55ac95-5629-4d8d-af3c-a2cd2d05a4ca"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['$', '360.000.000']"
            ]
          },
          "execution_count": 37,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.Valor[0].split()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        },
        "id": "JL4ilS3UMzlq",
        "outputId": "2a5ea16d-3c07-4469-8492-1451be0d276e"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Barrio</th>\n",
              "      <th>UPZ</th>\n",
              "      <th>Valor</th>\n",
              "      <th>Moneda</th>\n",
              "      <th>Precio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7013</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Cedritos</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>107</td>\n",
              "      <td>Cedritos</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 520.000.000</td>\n",
              "      <td>$</td>\n",
              "      <td>520.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2815</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Usaquén</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>50</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 360.000.000</td>\n",
              "      <td>$</td>\n",
              "      <td>360.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8540</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Santa Barbara</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>83</td>\n",
              "      <td>Santa Barbara</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 420.000.000</td>\n",
              "      <td>$</td>\n",
              "      <td>420.000.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Tipo                            Descripcion  Habitaciones  Banos  \\\n",
              "7013  Apartamento       Apartamento en venta en Cedritos             3      2   \n",
              "2815  Apartamento        Apartamento en venta en Usaquén             2      2   \n",
              "8540  Apartamento  Apartamento en venta en Santa Barbara             2      2   \n",
              "\n",
              "      Area         Barrio                                    UPZ  \\\n",
              "7013   107       Cedritos                                Usaquén   \n",
              "2815    50        Usaquén                                Usaquén   \n",
              "8540    83  Santa Barbara  USAQUÉN: Country Club + Santa Bárbara   \n",
              "\n",
              "              Valor Moneda       Precio  \n",
              "7013  $ 520.000.000      $  520.000.000  \n",
              "2815  $ 360.000.000      $  360.000.000  \n",
              "8540  $ 420.000.000      $  420.000.000  "
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "valor = inmuebles.Valor.str.split(expand=True)\n",
        "inmuebles['Moneda'] = valor[0]\n",
        "inmuebles['Precio'] = valor[1]\n",
        "inmuebles.sample(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S0QYDqaPNLhq",
        "outputId": "f0ffb6f1-1f2c-4a6e-d4ad-90b77a42cb38"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9520 entries, 0 to 9519\n",
            "Data columns (total 10 columns):\n",
            " #   Column        Non-Null Count  Dtype \n",
            "---  ------        --------------  ----- \n",
            " 0   Tipo          9520 non-null   object\n",
            " 1   Descripcion   9520 non-null   object\n",
            " 2   Habitaciones  9520 non-null   int64 \n",
            " 3   Banos         9520 non-null   int64 \n",
            " 4   Area          9520 non-null   int64 \n",
            " 5   Barrio        9520 non-null   object\n",
            " 6   UPZ           9478 non-null   object\n",
            " 7   Valor         9520 non-null   object\n",
            " 8   Moneda        9520 non-null   object\n",
            " 9   Precio        9520 non-null   object\n",
            "dtypes: int64(3), object(7)\n",
            "memory usage: 743.9+ KB\n"
          ]
        }
      ],
      "source": [
        "inmuebles.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 179
        },
        "id": "qwRAIGd9OCYq",
        "outputId": "9aa9a2de-4fd1-4145-cb8f-a0fa48a016aa"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
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          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
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      ],
      "source": [
        "inmuebles['Precio'].sum()"
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    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "O4PZCY0AOTIh"
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      "source": [
        "inmuebles['Precio'] = inmuebles['Precio'].str.replace('.','',regex=True)\n"
      ]
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        "id": "85K4T3OXOm-_",
        "outputId": "33b97553-2f54-4cfa-b654-9be013c08ebb"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Precio</th>\n",
              "      <th>Barrio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>360000000</td>\n",
              "      <td>Zona Noroccidental</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>670000000</td>\n",
              "      <td>Castilla</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1120000000</td>\n",
              "      <td>Chico Reservado</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>890000000</td>\n",
              "      <td>Usaquén</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>970000000</td>\n",
              "      <td>Bella Suiza</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9515</th>\n",
              "      <td>290000000</td>\n",
              "      <td>Kennedy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9516</th>\n",
              "      <td>670000000</td>\n",
              "      <td>Parque Central Bavaria</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9517</th>\n",
              "      <td>900000000</td>\n",
              "      <td>Restrepo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9518</th>\n",
              "      <td>335000000</td>\n",
              "      <td>Engativa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9519</th>\n",
              "      <td>144990000</td>\n",
              "      <td>Tintala</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9520 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          Precio                  Barrio\n",
              "0      360000000      Zona Noroccidental\n",
              "1      670000000                Castilla\n",
              "2     1120000000         Chico Reservado\n",
              "3      890000000                 Usaquén\n",
              "4      970000000             Bella Suiza\n",
              "...          ...                     ...\n",
              "9515   290000000                 Kennedy\n",
              "9516   670000000  Parque Central Bavaria\n",
              "9517   900000000                Restrepo\n",
              "9518   335000000                Engativa\n",
              "9519   144990000                 Tintala\n",
              "\n",
              "[9520 rows x 2 columns]"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles[['Precio','Barrio']]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZP57N8bXO9Lm",
        "outputId": "7127ee91-ca38-442e-9430-8aa9dd59b206"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9520 entries, 0 to 9519\n",
            "Data columns (total 10 columns):\n",
            " #   Column        Non-Null Count  Dtype \n",
            "---  ------        --------------  ----- \n",
            " 0   Tipo          9520 non-null   object\n",
            " 1   Descripcion   9520 non-null   object\n",
            " 2   Habitaciones  9520 non-null   int64 \n",
            " 3   Banos         9520 non-null   int64 \n",
            " 4   Area          9520 non-null   int64 \n",
            " 5   Barrio        9520 non-null   object\n",
            " 6   UPZ           9478 non-null   object\n",
            " 7   Valor         9520 non-null   object\n",
            " 8   Moneda        9520 non-null   object\n",
            " 9   Precio        9520 non-null   object\n",
            "dtypes: int64(3), object(7)\n",
            "memory usage: 743.9+ KB\n"
          ]
        }
      ],
      "source": [
        "inmuebles.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0JwDQyb6POMq",
        "outputId": "051f1d7f-fc6b-4e2b-fd23-c2aace7491f0"
      },
      "outputs": [],
      "source": [
        "import numpy\n",
        "inmuebles['Precio']=inmuebles['Valor'].str.replace('[^\\d]',\"\",regex=True).astype(numpy.int64)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "2OFAMdrAPoNq",
        "outputId": "b591add9-b93b-4195-c15e-760f92e1a7ef"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9520 entries, 0 to 9519\n",
            "Data columns (total 10 columns):\n",
            " #   Column        Non-Null Count  Dtype \n",
            "---  ------        --------------  ----- \n",
            " 0   Tipo          9520 non-null   object\n",
            " 1   Descripcion   9520 non-null   object\n",
            " 2   Habitaciones  9520 non-null   int64 \n",
            " 3   Banos         9520 non-null   int64 \n",
            " 4   Area          9520 non-null   int64 \n",
            " 5   Barrio        9520 non-null   object\n",
            " 6   UPZ           9478 non-null   object\n",
            " 7   Valor         9520 non-null   object\n",
            " 8   Moneda        9520 non-null   object\n",
            " 9   Precio        9520 non-null   int64 \n",
            "dtypes: int64(4), object(6)\n",
            "memory usage: 743.9+ KB\n"
          ]
        }
      ],
      "source": [
        "inmuebles.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Precio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>9520.000000</td>\n",
              "      <td>9520.000000</td>\n",
              "      <td>9520.000000</td>\n",
              "      <td>9.520000e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>3.072479</td>\n",
              "      <td>2.447899</td>\n",
              "      <td>146.664706</td>\n",
              "      <td>6.020624e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.049856</td>\n",
              "      <td>1.255314</td>\n",
              "      <td>1731.379622</td>\n",
              "      <td>7.046021e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>6.000000e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>57.000000</td>\n",
              "      <td>2.500000e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>4.091825e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>135.000000</td>\n",
              "      <td>6.800000e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>110.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>166243.000000</td>\n",
              "      <td>1.600000e+10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Habitaciones        Banos           Area        Precio\n",
              "count   9520.000000  9520.000000    9520.000000  9.520000e+03\n",
              "mean       3.072479     2.447899     146.664706  6.020624e+08\n",
              "std        2.049856     1.255314    1731.379622  7.046021e+08\n",
              "min        1.000000     0.000000       2.000000  6.000000e+07\n",
              "25%        2.000000     2.000000      57.000000  2.500000e+08\n",
              "50%        3.000000     2.000000      80.000000  4.091825e+08\n",
              "75%        3.000000     3.000000     135.000000  6.800000e+08\n",
              "max      110.000000     9.000000  166243.000000  1.600000e+10"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "fA1hAJW8QWZ7",
        "outputId": "26a7b561-ac83-4bde-c08d-c863a02140fa"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Precio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>9520.00</td>\n",
              "      <td>9520.00</td>\n",
              "      <td>9520.00</td>\n",
              "      <td>9520.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>3.07</td>\n",
              "      <td>2.45</td>\n",
              "      <td>146.66</td>\n",
              "      <td>602062353.53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.05</td>\n",
              "      <td>1.26</td>\n",
              "      <td>1731.38</td>\n",
              "      <td>704602061.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>60000000.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>57.00</td>\n",
              "      <td>250000000.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>3.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>80.00</td>\n",
              "      <td>409182500.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.00</td>\n",
              "      <td>3.00</td>\n",
              "      <td>135.00</td>\n",
              "      <td>680000000.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>110.00</td>\n",
              "      <td>9.00</td>\n",
              "      <td>166243.00</td>\n",
              "      <td>16000000000.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Habitaciones   Banos      Area         Precio\n",
              "count       9520.00 9520.00   9520.00        9520.00\n",
              "mean           3.07    2.45    146.66   602062353.53\n",
              "std            2.05    1.26   1731.38   704602061.61\n",
              "min            1.00    0.00      2.00    60000000.00\n",
              "25%            2.00    2.00     57.00   250000000.00\n",
              "50%            3.00    2.00     80.00   409182500.00\n",
              "75%            3.00    3.00    135.00   680000000.00\n",
              "max          110.00    9.00 166243.00 16000000000.00"
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "pd.set_option('display.float_format', lambda x: '%.2f' % x)\n",
        "inmuebles.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Precio</th>\n",
              "      <th>PrecioMillon</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>9520.00</td>\n",
              "      <td>9520.00</td>\n",
              "      <td>9520.00</td>\n",
              "      <td>9520.00</td>\n",
              "      <td>9520.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>3.07</td>\n",
              "      <td>2.45</td>\n",
              "      <td>146.66</td>\n",
              "      <td>602062353.53</td>\n",
              "      <td>602.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.05</td>\n",
              "      <td>1.26</td>\n",
              "      <td>1731.38</td>\n",
              "      <td>704602061.61</td>\n",
              "      <td>704.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>60000000.00</td>\n",
              "      <td>60.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>57.00</td>\n",
              "      <td>250000000.00</td>\n",
              "      <td>250.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>3.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>80.00</td>\n",
              "      <td>409182500.00</td>\n",
              "      <td>409.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.00</td>\n",
              "      <td>3.00</td>\n",
              "      <td>135.00</td>\n",
              "      <td>680000000.00</td>\n",
              "      <td>680.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>110.00</td>\n",
              "      <td>9.00</td>\n",
              "      <td>166243.00</td>\n",
              "      <td>16000000000.00</td>\n",
              "      <td>16000.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Habitaciones   Banos      Area         Precio  PrecioMillon\n",
              "count       9520.00 9520.00   9520.00        9520.00       9520.00\n",
              "mean           3.07    2.45    146.66   602062353.53        602.06\n",
              "std            2.05    1.26   1731.38   704602061.61        704.60\n",
              "min            1.00    0.00      2.00    60000000.00         60.00\n",
              "25%            2.00    2.00     57.00   250000000.00        250.00\n",
              "50%            3.00    2.00     80.00   409182500.00        409.18\n",
              "75%            3.00    3.00    135.00   680000000.00        680.00\n",
              "max          110.00    9.00 166243.00 16000000000.00      16000.00"
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles['PrecioMillon']=inmuebles['Precio']/1000000\n",
        "inmuebles.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "id": "boVAQbi5RKsm",
        "outputId": "8a215d47-6536-47a2-843c-223b1fc1f013"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-ea7c1ddd-5193-4f37-9ab3-0d780991559e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
              "      <th>Habitaciones</th>\n",
              "      <th>Banos</th>\n",
              "      <th>Area</th>\n",
              "      <th>Barrio</th>\n",
              "      <th>UPZ</th>\n",
              "      <th>Valor</th>\n",
              "      <th>Moneda</th>\n",
              "      <th>Precio</th>\n",
              "      <th>Precio_Millon</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>897</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en La Uribe</td>\n",
              "      <td>110</td>\n",
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              "      <td>Usaquén</td>\n",
              "      <td>$ 480.000.000</td>\n",
              "      <td>$</td>\n",
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            "text/plain": [
              "     Tipo                Descripcion  Habitaciones  Banos  Area    Barrio  \\\n",
              "897  Casa  Casa en venta en La Uribe           110      2   110  La Uribe   \n",
              "\n",
              "         UPZ          Valor Moneda     Precio  Precio_Millon  \n",
              "897  Usaquén  $ 480.000.000      $  480000000         480.00  "
            ]
          },
          "execution_count": 51,
          "metadata": {},
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        }
      ],
      "source": [
        "inmuebles.loc[inmuebles.Habitaciones == 110]"
      ]
    },
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              "      <th></th>\n",
              "      <th>Tipo</th>\n",
              "      <th>Descripcion</th>\n",
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              "      <td>Apartamento</td>\n",
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              "      <td>Sosiego</td>\n",
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            "text/plain": [
              "             Tipo                            Descripcion  Habitaciones  Banos  \\\n",
              "8401  Apartamento  Apartamento en venta en San Cristobal             3      1   \n",
              "\n",
              "      Area         Barrio      UPZ          Valor Moneda     Precio  \\\n",
              "8401     2  San Cristobal  Sosiego  $ 180.000.000      $  180000000   \n",
              "\n",
              "      Precio_Millon  \n",
              "8401         180.00  "
            ]
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          "execution_count": 52,
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      "source": [
        "inmuebles.loc[inmuebles.Area == 2]"
      ]
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        "id": "fd44PJPCSJwN",
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "<AxesSubplot:ylabel='Frequency'>"
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          },
          "execution_count": 26,
          "metadata": {},
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nAgN/3oXb7dbgwYM5hwgAANQ6XgWioKAgLVy4UE8//bQ2b96s0NBQdejQQS1btqzs/gAAAKqcV4Go3BVXXKErrriisnoBAADwCa8CUVlZmTIyMpSVlaWioiK53W6P9VWrVlVKcwAAANXBq0A0atQoZWRkKCkpSe3bt5efn19l9wUAAFBtvApECxYs0KJFi9SnT5/K7gcAAKDaeXXZfVBQkFq3bl3ZvQAAAPiEV4Fo3Lhxmjlzpowxld0PAABAtfPqI7PPP/9cq1ev1vLly3X11VerXr16HutLliyplOYAAACqg1eBKCIiQn379q3sXgAAAHzCq0A0d+7cyu4DAADAZ7w6h0iSTp8+rU8++USvvfaajh49KknKz8/XsWPHKq05AACA6uDVEaJ9+/apd+/eysvL08mTJ/U///M/atiwoaZNm6aTJ08qPT29svsEAACoMl4dIRo1apS6du2qI0eOKDQ01Nnet29fZWVlVVpzAAAA1cGrI0SfffaZvvzySwUFBXlsb9WqlX744YdKaQwAAKC6eHWEyO12q6ysrML2AwcOqGHDhhfdFAAAQHXyKhD16tVLM2bMcL728/PTsWPH9OSTT/LnPAAAQK3j1UdmL7zwghITE9WuXTudOHFC9957r3bv3q2mTZvqnXfeqeweAQAAqpRXgah58+bavHmzFixYoC1btujYsWMaNmyYkpOTPU6yBgAAqA28CkSSFBgYqIEDB1ZmLwAAAD7hVSB68803z7k+ePBgr5oBAADwBa8C0ahRozy+Li0t1Y8//qigoCDVr1+fQAQAAGoVr64yO3LkiMfj2LFjys3NVY8ePTipGgAA1Dpe/y2zX2rTpo2mTp1a4egRAABATVdpgUj6+UTr/Pz8ytwlAABAlfPqHKIPPvjA42tjjA4ePKiXX35Z3bt3r5TGAAAAqotXgeiuu+7y+NrPz0+XXnqp/vu//1svvPBCZfQFAABQbbwKRG63u7L7AAAA8JlKPYcIAACgNvLqCNHYsWN/c+306dO9eQoAAIBq41Ug2rhxozZu3KjS0lJdeeWVkqRdu3YpICBAnTt3dur8/Pwqp0sAAIAq5FUguv3229WwYUPNmzdPjRo1kvTzzRqHDh2qm266SePGjavUJgEAAKqSV+cQvfDCC0pNTXXCkCQ1atRIzzzzDFeZAQCAWserQORyuXTo0KEK2w8dOqSjR49edFMAAADVyatA1LdvXw0dOlRLlizRgQMHdODAAf3v//6vhg0bpn79+lV2jwAAAFXKq3OI0tPT9eijj+ree+9VaWnpzzsKDNSwYcP0/PPPV2qDAAAAVc2rQFS/fn29+uqrev755/Wvf/1LknT55ZerQYMGldocAABAdbioGzMePHhQBw8eVJs2bdSgQQMZYyqrLwAAgGrjVSD6z3/+o549e+qKK65Qnz59dPDgQUnSsGHDuOQeAADUOl4FojFjxqhevXrKy8tT/fr1ne133323VqxYUWnNAQAAVAevziH6+OOPtXLlSjVv3txje5s2bbRv375KaQwAAKC6eHWE6Pjx4x5HhsodPnxYwcHBF90UAABAdfIqEN1000168803na/9/PzkdruVlpamW265pdKaAwAAqA5eBaK0tDTNmTNHt956q06dOqUJEyaoffv2Wrt2raZNm+ZVI1OnTpWfn59Gjx7tbDtx4oRSUlLUpEkTXXLJJerfv78KCws9vi8vL09JSUmqX7++IiMjNX78eJ0+fdqj5tNPP1Xnzp0VHBys1q1bKyMjw6seAQBA3eRVIGrfvr127dqlHj166M4779Tx48fVr18/bdy4UZdffvkF7+/rr7/Wa6+9pmuuucZj+5gxY/Thhx9q8eLFWrNmjfLz8z3uhF1WVqakpCSdOnVKX375pebNm6eMjAxNmTLFqdm7d6+SkpJ0yy23aNOmTRo9erT+/Oc/a+XKld6MDgAA6iA/c4E3DyotLVXv3r2Vnp6uNm3aXHQDx44dU+fOnfXqq6/qmWeeUceOHTVjxgyVlJTo0ksv1fz58/WHP/xBkrRz505dddVVys7O1g033KDly5frtttuU35+vqKioiT9fBftiRMn6tChQwoKCtLEiRO1bNkybdu2zXnOAQMGqLi4+DdfEedyuRQeHq6SkhKFhYVd9My/1GrSskrfZ1X7fmqSr1sAAOCcLuT9+4KPENWrV09btmzxurlfSklJUVJSkhISEjy25+TkqLS01GN727Zt1aJFC2VnZ0uSsrOz1aFDBycMSVJiYqJcLpe2b9/u1Pxy34mJic4+zubkyZNyuVweDwAAUHd59ZHZwIED9frrr1/0ky9YsEAbNmxQampqhbWCggIFBQUpIiLCY3tUVJQKCgqcmjPDUPl6+dq5alwul3766aez9pWamqrw8HDnERsb69V8AACgdvDqPkSnT5/WG2+8oU8++URdunSp8DfMpk+fft597N+/X6NGjVJmZqZCQkK8aaPKTJ48WWPHjnW+drlchCIAAOqwCwpEe/bsUatWrbRt2zZ17txZkrRr1y6PGj8/v9+0r5ycHBUVFTn7kX4+SXrt2rV6+eWXtXLlSp06dUrFxcUeR4kKCwsVHR0tSYqOjtb69es99lt+FdqZNb+8Mq2wsFBhYWEKDQ09a2/BwcHcTwkAAItcUCBq06aNDh48qNWrV0v6+U91zJo1q8JHUr9Fz549tXXrVo9tQ4cOVdu2bTVx4kTFxsaqXr16ysrKUv/+/SVJubm5ysvLU3x8vCQpPj5ezz77rIqKihQZGSlJyszMVFhYmNq1a+fUfPTRRx7Pk5mZ6ewDAADgggLRLy9IW758uY4fP+7VEzds2FDt27f32NagQQM1adLE2T5s2DCNHTtWjRs3VlhYmP7yl78oPj5eN9xwgySpV69eateunQYNGqS0tDQVFBTo8ccfV0pKinOEZ8SIEXr55Zc1YcIE3X///Vq1apUWLVqkZctq35VdAACganh1DlG5C7xi/4K9+OKL8vf3V//+/XXy5EklJibq1VdfddYDAgK0dOlSPfTQQ4qPj1eDBg00ZMgQPfXUU05NXFycli1bpjFjxmjmzJlq3ry5/vnPfyoxMbFKewcAALXHBd2HKCAgQAUFBbr00ksl/XyUZ8uWLYqLi6uyBmsC7kNUEfchAgDUdBfy/n3BH5ndd999zsdRJ06c0IgRIypcZbZkyZILbBkAAMB3LigQDRkyxOPrgQMHVmozAAAAvnBBgWju3LlV1QcAAIDPeHWnagAAgLqEQAQAAKxHIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9QhEAADAegQiAABgPQIRAACwHoEIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKxHIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9QhEAADAegQiAABgPQIRAACwHoEIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKxHIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9QhEAADAegQiAABgPQIRAACwnk8DUWpqqq677jo1bNhQkZGRuuuuu5Sbm+tRc+LECaWkpKhJkya65JJL1L9/fxUWFnrU5OXlKSkpSfXr11dkZKTGjx+v06dPe9R8+umn6ty5s4KDg9W6dWtlZGRU9XgAAKCW8GkgWrNmjVJSUvTVV18pMzNTpaWl6tWrl44fP+7UjBkzRh9++KEWL16sNWvWKD8/X/369XPWy8rKlJSUpFOnTunLL7/UvHnzlJGRoSlTpjg1e/fuVVJSkm655RZt2rRJo0eP1p///GetXLmyWucFAAA1k58xxvi6iXKHDh1SZGSk1qxZo5tvvlklJSW69NJLNX/+fP3hD3+QJO3cuVNXXXWVsrOzdcMNN2j58uW67bbblJ+fr6ioKElSenq6Jk6cqEOHDikoKEgTJ07UsmXLtG3bNue5BgwYoOLiYq1YseK8fblcLoWHh6ukpERhYWGVPnerScsqfZ9V7fupSb5uAQCAc7qQ9+8adQ5RSUmJJKlx48aSpJycHJWWliohIcGpadu2rVq0aKHs7GxJUnZ2tjp06OCEIUlKTEyUy+XS9u3bnZoz91FeU76PXzp58qRcLpfHAwAA1F01JhC53W6NHj1a3bt3V/v27SVJBQUFCgoKUkREhEdtVFSUCgoKnJozw1D5evnauWpcLpd++umnCr2kpqYqPDzcecTGxlbKjAAAoGaqMYEoJSVF27Zt04IFC3zdiiZPnqySkhLnsX//fl+3BAAAqlCgrxuQpJEjR2rp0qVau3atmjdv7myPjo7WqVOnVFxc7HGUqLCwUNHR0U7N+vXrPfZXfhXamTW/vDKtsLBQYWFhCg0NrdBPcHCwgoODK2U2AABQ8/n0CJExRiNHjtS7776rVatWKS4uzmO9S5cuqlevnrKyspxtubm5ysvLU3x8vCQpPj5eW7duVVFRkVOTmZmpsLAwtWvXzqk5cx/lNeX7AAAAdvPpEaKUlBTNnz9f77//vho2bOic8xMeHq7Q0FCFh4dr2LBhGjt2rBo3bqywsDD95S9/UXx8vG644QZJUq9evdSuXTsNGjRIaWlpKigo0OOPP66UlBTnKM+IESP08ssva8KECbr//vu1atUqLVq0SMuW1b6ruwAAQOXz6RGi2bNnq6SkRP/1X/+lZs2aOY+FCxc6NS+++KJuu+029e/fXzfffLOio6O1ZMkSZz0gIEBLly5VQECA4uPjNXDgQA0ePFhPPfWUUxMXF6dly5YpMzNT1157rV544QX985//VGJiYrXOCwAAaqYadR+imor7EFXEfYgAADVdrb0PEQAAgC8QiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9QhEAADAegQiAABgPQIRAACwHoEIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKxHIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9QhEAADAegQiAABgPQIRAACwHoEIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKxHIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6wX6ugHUTq0mLfN1Cxfs+6lJvm4BAFBDcYQIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFjPqkD0yiuvqFWrVgoJCVG3bt20fv16X7cEAABqAGv+dMfChQs1duxYpaenq1u3bpoxY4YSExOVm5uryMhIX7eHasCfGwEA/BprjhBNnz5dDzzwgIYOHap27dopPT1d9evX1xtvvOHr1gAAgI9ZcYTo1KlTysnJ0eTJk51t/v7+SkhIUHZ2doX6kydP6uTJk87XJSUlkiSXy1Ul/blP/lgl+0Xt12LMYl+3cMG2/S3R1y0AgKT/f982xpy31opA9O9//1tlZWWKiory2B4VFaWdO3dWqE9NTdXf/va3CttjY2OrrEegrgif4esOAMDT0aNHFR4efs4aKwLRhZo8ebLGjh3rfO12u3X48GE1adJEfn5+lfIcLpdLsbGx2r9/v8LCwiplnzVNXZ+xrs8nMWNdUNfnk+r+jHV9PqnqZjTG6OjRo4qJiTlvrRWBqGnTpgoICFBhYaHH9sLCQkVHR1eoDw4OVnBwsMe2iIiIKuktLCyszv4DL1fXZ6zr80nMWBfU9fmkuj9jXZ9PqpoZz3dkqJwVJ1UHBQWpS5cuysrKcra53W5lZWUpPj7eh50BAICawIojRJI0duxYDRkyRF27dtX111+vGTNm6Pjx4xo6dKivWwMAAD5mTSC6++67dejQIU2ZMkUFBQXq2LGjVqxYUeFE6+oSHBysJ598ssJHc3VJXZ+xrs8nMWNdUNfnk+r+jHV9PqlmzOhnfsu1aAAAAHWYFecQAQAAnAuBCAAAWI9ABAAArEcgAgAA1iMQ+cgrr7yiVq1aKSQkRN26ddP69et93VIFqampuu6669SwYUNFRkbqrrvuUm5urkfNiRMnlJKSoiZNmuiSSy5R//79K9wAMy8vT0lJSapfv74iIyM1fvx4nT592qPm008/VefOnRUcHKzWrVsrIyOjqsc7q6lTp8rPz0+jR492ttX2GX/44QcNHDhQTZo0UWhoqDp06KBvvvnGWTfGaMqUKWrWrJlCQ0OVkJCg3bt3e+zj8OHDSk5OVlhYmCIiIjRs2DAdO3bMo2bLli266aabFBISotjYWKWlpVXLfGVlZXriiScUFxen0NBQXX755Xr66ac9/nZRbZtx7dq1uv322xUTEyM/Pz+99957HuvVOc/ixYvVtm1bhYSEqEOHDvroo4+qdL7S0lJNnDhRHTp0UIMGDRQTE6PBgwcrPz+/1sx3vhl/acSIEfLz89OMGTM8ttfkGX/LfDt27NAdd9yh8PBwNWjQQNddd53y8vKc9Rr32mpQ7RYsWGCCgoLMG2+8YbZv324eeOABExERYQoLC33dmofExEQzd+5cs23bNrNp0ybTp08f06JFC3Ps2DGnZsSIESY2NtZkZWWZb775xtxwww3mxhtvdNZPnz5t2rdvbxISEszGjRvNRx99ZJo2bWomT57s1OzZs8fUr1/fjB071nz77bfmpZdeMgEBAWbFihXVOu/69etNq1atzDXXXGNGjRrlbK/NMx4+fNi0bNnS3HfffWbdunVmz549ZuXKlea7775zaqZOnWrCw8PNe++9ZzZv3mzuuOMOExcXZ3766Senpnfv3ubaa681X331lfnss89M69atzT333OOsl5SUmKioKJOcnGy2bdtm3nnnHRMaGmpee+21Kp3PGGOeffZZ06RJE7N06VKzd+9es3jxYnPJJZeYmTNn1toZP/roI/PYY4+ZJUuWGEnm3Xff9Vivrnm++OILExAQYNLS0sy3335rHn/8cVOvXj2zdevWKpuvuLjYJCQkmIULF5qdO3ea7Oxsc/3115suXbp47KMmz3e+Gc+0ZMkSc+2115qYmBjz4osv1poZzzffd999Zxo3bmzGjx9vNmzYYL777jvz/vvve7zP1bTXVgKRD1x//fUmJSXF+bqsrMzExMSY1NRUH3Z1fkVFRUaSWbNmjTHm5xeuevXqmcWLFzs1O3bsMJJMdna2MebnXxp/f39TUFDg1MyePduEhYWZkydPGmOMmTBhgrn66qs9nuvuu+82iYmJVT2S4+jRo6ZNmzYmMzPT/P73v3cCUW2fceLEiaZHjx6/uu52u010dLR5/vnnnW3FxcUmODjYvPPOO8YYY7799lsjyXz99ddOzfLly42fn5/54YcfjDHGvPrqq6ZRo0bOvOXPfeWVV1b2SBUkJSWZ+++/32Nbv379THJysjGm9s/4yzeb6pznT3/6k0lKSvLop1u3bubBBx+ssvnOZv369UaS2bdvnzGmds1nzK/PeODAAXPZZZeZbdu2mZYtW3oEoto049nmu/vuu83AgQN/9Xtq4msrH5lVs1OnTiknJ0cJCQnONn9/fyUkJCg7O9uHnZ1fSUmJJKlx48aSpJycHJWWlnrM0rZtW7Vo0cKZJTs7Wx06dPC4AWZiYqJcLpe2b9/u1Jy5j/Ka6vx5pKSkKCkpqUIftX3GDz74QF27dtUf//hHRUZGqlOnTvrHP/7hrO/du1cFBQUevYWHh6tbt24e80VERKhr165OTUJCgvz9/bVu3Tqn5uabb1ZQUJDHfLm5uTpy5EiVznjjjTcqKytLu3btkiRt3rxZn3/+uW699dY6M+OZqnOemvC7Kf382uPn5+f8Tcm6MJ/b7dagQYM0fvx4XX311RXWa/OMbrdby5Yt0xVXXKHExERFRkaqW7duHh+r1cTXVgJRNfv3v/+tsrKyCnfIjoqKUkFBgY+6Oj+3263Ro0ere/fuat++vSSpoKBAQUFBFf7w7ZmzFBQUnHXW8rVz1bhcLv30009VMY6HBQsWaMOGDUpNTa2wVttn3LNnj2bPnq02bdpo5cqVeuihh/TII49o3rx5Hv2d699jQUGBIiMjPdYDAwPVuHHjC/oZVJVJkyZpwIABatu2rerVq6dOnTpp9OjRSk5O9nj+2jzjmapznl+rqc55T5w4oYkTJ+qee+5x/uhnXZhv2rRpCgwM1COPPHLW9do8Y1FRkY4dO6apU6eqd+/e+vjjj9W3b1/169dPa9ascfqqaa+t1vzpDlyclJQUbdu2TZ9//rmvW6lU+/fv16hRo5SZmamQkBBft1Pp3G63unbtqueee06S1KlTJ23btk3p6ekaMmSIj7urHIsWLdLbb7+t+fPn6+qrr9amTZs0evRoxcTE1JkZbVVaWqo//elPMsZo9uzZvm6n0uTk5GjmzJnasGGD/Pz8fN1OpXO73ZKkO++8U2PGjJEkdezYUV9++aXS09P1+9//3pft/SqOEFWzpk2bKiAgoMKZ9IWFhYqOjvZRV+c2cuRILV26VKtXr1bz5s2d7dHR0Tp16pSKi4s96s+cJTo6+qyzlq+dqyYsLEyhoaGVPY6HnJwcFRUVqXPnzgoMDFRgYKDWrFmjWbNmKTAwUFFRUbV6xmbNmqldu3Ye26666irnSo/y/s717zE6OlpFRUUe66dPn9bhw4cv6GdQVcaPH+8cJerQoYMGDRqkMWPGOEf86sKMZ6rOeX6tpjrmLQ9D+/btU2ZmpnN0qLyv2jzfZ599pqKiIrVo0cJ53dm3b5/GjRunVq1aOb3V1hmbNm2qwMDA87721LTXVgJRNQsKClKXLl2UlZXlbHO73crKylJ8fLwPO6vIGKORI0fq3Xff1apVqxQXF+ex3qVLF9WrV89jltzcXOXl5TmzxMfHa+vWrR6/2OUvbuW/LPHx8R77KK+pjp9Hz549tXXrVm3atMl5dO3aVcnJyc5/1+YZu3fvXuFWCbt27VLLli0lSXFxcYqOjvbozeVyad26dR7zFRcXKycnx6lZtWqV3G63unXr5tSsXbtWpaWlTk1mZqauvPJKNWrUqMrmk6Qff/xR/v6eL2UBAQHO/6XWhRnPVJ3z+OrfbXkY2r17tz755BM1adLEY722zzdo0CBt2bLF43UnJiZG48eP18qVK2v9jEFBQbruuuvO+dpTI98/Lvg0bFy0BQsWmODgYJORkWG+/fZbM3z4cBMREeFxJn1N8NBDD5nw8HDz6aefmoMHDzqPH3/80akZMWKEadGihVm1apX55ptvTHx8vImPj3fWyy+b7NWrl9m0aZNZsWKFufTSS8962eT48ePNjh07zCuvvOKTy+7LnXmVmTG1e8b169ebwMBA8+yzz5rdu3ebt99+29SvX9+89dZbTs3UqVNNRESEef/9982WLVvMnXfeedZLuDt16mTWrVtnPv/8c9OmTRuPy3+Li4tNVFSUGTRokNm2bZtZsGCBqV+/frVcdj9kyBBz2WWXOZfdL1myxDRt2tRMmDCh1s549OhRs3HjRrNx40YjyUyfPt1s3LjRucqquub54osvTGBgoPn73/9uduzYYZ588slKuWT7XPOdOnXK3HHHHaZ58+Zm06ZNHq89Z15NVZPnO9+MZ/PLq8xq+oznm2/JkiWmXr16Zs6cOWb37t3O5fCfffaZs4+a9tpKIPKRl156ybRo0cIEBQWZ66+/3nz11Ve+bqkCSWd9zJ0716n56aefzMMPP2waNWpk6tevb/r27WsOHjzosZ/vv//e3HrrrSY0NNQ0bdrUjBs3zpSWlnrUrF692nTs2NEEBQWZ3/3udx7PUd1+GYhq+4wffvihad++vQkODjZt27Y1c+bM8Vh3u93miSeeMFFRUSY4ONj07NnT5ObmetT85z//Mffcc4+55JJLTFhYmBk6dKg5evSoR83mzZtNjx49THBwsLnsssvM1KlTq3w2Y4xxuVxm1KhRpkWLFiYkJMT87ne/M4899pjHm2dtm3H16tVn/d0bMmRItc+zaNEic8UVV5igoCBz9dVXm2XLllXpfHv37v3V157Vq1fXivnON+PZnC0Q1eQZf8t8r7/+umndurUJCQkx1157rXnvvfc89lHTXlv9jDnjdq4AAAAW4hwiAABgPQIRAACwHoEIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKz3f7y2z4CQJj13AAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "inmuebles['PrecioMillon'].plot.hist(bins=10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        },
        "id": "yhdim-1uSx2c",
        "outputId": "00df0c40-2bc9-460a-d4fd-d0089fab4b5c"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "plt.figure(figsize=(10,6))\n",
        "grafica = sns.histplot(data=inmuebles, x='PrecioMillon', kde=True, hue='Tipo')\n",
        "grafica.set_title('Distribución de Valores de los inmuebles en Bogotá')\n",
        "plt.xlim((50,1000))\n",
        "plt.savefig('./valor_inmuebles.png',format='png')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q4dm6mfCYB-h"
      },
      "source": [
        "**Desafíos**\n",
        "\n",
        "1. Estudiar mejor el histograma de valores, seleccionar 3 tipos de inmuebles (Refinar el gráfico: Títulos, aumentar el tamaño de labels, colores, conclusión de la información)\n",
        "\n",
        "2. Precio del m2 por barrio y hacer el gráfico más adecuado para esta nueva variable."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uWrFOixRmcZr"
      },
      "source": [
        "# **Resolución de Desafíos**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Precio del metro cuadrado por barrio"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Area</th>\n",
              "      <th>PrecioMillon</th>\n",
              "      <th>Precio por Metro Cuadrado</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Barrio</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Alameda</th>\n",
              "      <td>97</td>\n",
              "      <td>580.00</td>\n",
              "      <td>5.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alhambra</th>\n",
              "      <td>3237</td>\n",
              "      <td>12790.00</td>\n",
              "      <td>3.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andes Norte</th>\n",
              "      <td>874</td>\n",
              "      <td>4967.00</td>\n",
              "      <td>5.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Antonio Nariño</th>\n",
              "      <td>7827</td>\n",
              "      <td>22042.65</td>\n",
              "      <td>2.82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Barrancas</th>\n",
              "      <td>1053</td>\n",
              "      <td>4712.00</td>\n",
              "      <td>4.47</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                Area  PrecioMillon  Precio por Metro Cuadrado\n",
              "Barrio                                                       \n",
              "Alameda           97        580.00                       5.98\n",
              "Alhambra        3237      12790.00                       3.95\n",
              "Andes Norte      874       4967.00                       5.68\n",
              "Antonio Nariño  7827      22042.65                       2.82\n",
              "Barrancas       1053       4712.00                       4.47"
            ]
          },
          "execution_count": 52,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "BarrioAcumulado=inmuebles[['Barrio','Area','PrecioMillon']].groupby(['Barrio']).sum()\n",
        "BarrioAcumulado['Precio por Metro Cuadrado']=BarrioAcumulado['PrecioMillon']/BarrioAcumulado['Area']\n",
        "BarrioAcumulado.head()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 106,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Barrio</th>\n",
              "      <th>Precio por Metro Cuadrado</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>134</th>\n",
              "      <td>Timiza</td>\n",
              "      <td>2.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>Rafael Uribe Uribe</td>\n",
              "      <td>2.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>Galicia</td>\n",
              "      <td>2.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144</th>\n",
              "      <td>Villa Maria</td>\n",
              "      <td>1.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>Santa Librada</td>\n",
              "      <td>1.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80</th>\n",
              "      <td>Las Ferias</td>\n",
              "      <td>1.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83</th>\n",
              "      <td>Libertador</td>\n",
              "      <td>1.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>Roma</td>\n",
              "      <td>1.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Bosa Piamonte</td>\n",
              "      <td>1.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>Modelia</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 Barrio  Precio por Metro Cuadrado\n",
              "134              Timiza                       2.33\n",
              "113  Rafael Uribe Uribe                       2.33\n",
              "56              Galicia                       2.25\n",
              "144         Villa Maria                       1.94\n",
              "127       Santa Librada                       1.93\n",
              "80           Las Ferias                       1.72\n",
              "83           Libertador                       1.59\n",
              "116                Roma                       1.35\n",
              "11        Bosa Piamonte                       1.18\n",
              "92              Modelia                       0.16"
            ]
          },
          "execution_count": 106,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "BarrioValorMetroCuadrado=BarrioAcumulado.reset_index()[['Barrio','Precio por Metro Cuadrado']]\n",
        "\n",
        "BarrioValorMetroCuadrado.sort_values(by=['Precio por Metro Cuadrado'], ascending=False).tail(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 82,
      "metadata": {},
      "outputs": [],
      "source": [
        "top10=BarrioValorMetroCuadrado.sort_values(by=['Precio por Metro Cuadrado'], ascending=False).head(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 100,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.barh(top10['Barrio'], top10['Precio por Metro Cuadrado'],color='orange')\n",
        "plt.gca().invert_yaxis()\n",
        "plt.title('TOP 10 de Barrios con mayor Precio del metro cuadrado')\n",
        "plt.xlabel('Precio por Metro Cuadrado')\n",
        "plt.ylabel('Barrios')\n",
        "for valor, categoria in zip(top10['Precio por Metro Cuadrado'], top10['Barrio']):\n",
        "    plt.text(valor, categoria, str('%.2f' %valor), ha='left', va='center')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 131,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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pEydOFKf379+/yHEVljBNmzZNnN+3b1+ZeX369BHnTZ8+vcDtFJYwmZmZCdHR0TLLXLp0SejevbvY9fTjZXJ3j859fJcvX55n+7k/yHr27JlnvryE6dy5c+I0Y2Nj4d27d2L7nOQIgDB//nxBEP7vw1VDQ0M4cOCAkJycXOAxye3Fixfil0SlSpWEK1euyG1X3Jhyf8kYGRmJhZ7Hjx+L0+vVq1dofB8nTEuWLBEACJUrVxYH4/zuu+9kijIfn8n7888/hdatWwuVK1cWKlWqlOf/ef78eUEQBGHmzJnitG3btgmC8OFyg5xpOa+TTzkWWlpacrupy1OUwc9VVVXFszG523/ca0cQZM96eXt7i4M4Hjt2TLCwsBCAD2exnj17JmRlZcn00Nm3b1+R/kc5nzFhYWHiNF9fX7Htu3fvZHryxMXFFXgMijL4eadOneS2l/d+y30m7M8//xSn//nnn+J0JycncXru9/f+/fsFQRCEZ8+eyWz/5s2bgiAIwunTp8VpHTt2FARB9rNWVVVVOHDggHjMhw8fLrafO3euIAiCMGzYMHHauHHjxDiuX78us80c8gpTL168EBNpNTU1mWT8p59+Etv/8MMPBR57Iioa5lnMswpS0fOsDh06iNMXLVokfsetWLFCnN6+fXuxfe7/Z+7eeLlPqMTHxwuCIAijRo0Sp/30009i22fPnok9YyQSiZhXFfZayE9RBj93cXER3r9/n6f9x712intMcudmlpaW4v9RHnnv5+LmNYWtO7+HRCKR+X/lnpeTH+X4lNeyqampeKnjr7/+Kk5v1qyZuI7cJ/x27tyZ5zgWJcfV0tIS2+ec3BQE2c/bwgpTpZXrljYOfk5flGfPnuHVq1cAAA0NDdStW1ec16hRI/Hv69ev51nWwMAA1tbWctuX5q1ENTU1xb8zMjJk5r17905uu8LkDGj4999/Y9q0aZBIJEhMTESnTp3w+PFjAB8GeXR1dcWmTZvw4MEDZGZm5lnP69ev5a7fx8enwO0XNj9H7uNev359qKioiM/l/X/69esHiUSC9PR0tGrVCrq6ujA1NUXv3r0LHajx5s2byM7OBgDUrFkTdnZ2pRJTbt988w3U1NQAAIaGhuL0/I5jQXr16gUNDQ08f/4c+/btAwAMGjQo3/bbt2+Hj48PYmJi8Pz5c2RlZeVpkxOHv78/KlWqBADYsGEDAGDXrl0AIN72Gvi0Y+Hm5gYDA4Mi7Wth6tWrh+joaDRs2DDPPBsbG9SuXVtmWu54/vrrLzRr1kx83L17FwAgCAKuXr2K58+f4+XLlwAANTU1tGrVqlix5d5W48aNxb9VVFRkBgOWd4yKSlNTE6NGjcr3VuTy3m/5xVXY/y13m9z/P319fVhZWQEAKleuLE7PeU09f/5c/Kx99+4dWrVqJR7zpUuXiu0TEhIAyH6G5v6/2tjYQF9fX25cH7tx44Z4W2srKyuZ91xR9pOIPh3zLOZZOSp6npU7nlGjRonfcbmXyfmO+5i7u7v4t7y48/vOrly5MmrWrAngQ95y8+bNPOsu6muhMKqqqujduzeio6PFHDG39u3b55lWnGOSu22rVq3E/2NRfUpeU1TW1tbYvHkzOnbsmGeeuro6WrdunW9MxX0tN2jQAEpKH0orufOt3AO+y8u3ipPjPn36FKmpqQA+fL7VqVNHbnyFKY9ctyRYmKIvlkQiKfB5cZcvLRYWFuLfT548kZmXk9wAgKWlZZHXmXNnlhYtWiAoKAienp4AgP/++08sQKxZswYpKSkAgCZNmmDnzp04duwYxo8fL64nJ8H4WNWqVQvcfmHzi0Le8W7Tpg1iY2MxaNAgODs7Q0NDAw8ePMCGDRvg7u5eqolsUWPKLfcPamVlZfHvnB/PxaGrq4vvv/9efF69enV4e3vn2z73nYD8/f2xf/9+HDt2TOZLNOf/aWJiAi8vLwDAnj17cP36dfz7778AgC5dusjEnp/CjsWnvAZy7vJ06tQpJCUlIS4uDi1atCj17Xx8RxWJRFKq7/OSrivnrnyxsbG4dOkSXr16hYULF0JDQ0Nu++Icg6LElHMXlpyECQB0dHTkti3ua7sod7Epjf9BWX1eE1H+mGcxzyqLmHJTZJ5VFPl9x31K3GWVb+UUV48fP47z58/j9evXWLdunUzhrDS2U9Z3r/uUz42cu/KdPHkS9+7dw40bN9ClSxe5bY2MjEo1rtx3vFNEvlVan7eKzLdYmKIvSpUqVaCnpwfgwxv08uXL4rycH+IAUKtWrTzLvnz5UubMRO72OWcvSoOrq6v4gRQXFyfefvXt27eIi4sDAFSqVAlNmjQp8TZyf5jl9A55+PChOO2XX35Bhw4d0LRpUyQnJxe6vsI+hIr6IZX7uMfFxcnc4lbe/0cQBDRp0gTLly/HuXPn8ObNG8ybNw8AkJ6ejujo6Hy3ZW1tLR7n27dv4+rVq6USU1nKffve3L2c5Mn9/wwPD0fr1q3h6uoqMz23AQMGAPhw9rh///5ictyjRw+xzacci0/5osq5TW3Dhg1lbk8uj7zt5I7Hz88PwofL0GUeaWlp8PT0ROXKlcWE8e3btzhw4ECxYs29rVOnTol/Z2Zmiu/fj9sVxszMDE2bNoWrqyvs7e1lzsDJU9gxyB1XWb2Gcx9HLS0tvHnzJs8xz8rKQmRkJADZz9DcZ+Fv3rwpfkYVxtraWtz3W7du4cWLF+K88n6vEn2tmGd9wDyr4udZueM5dOiQ3Nzi1q1bJYojv+/sFy9eiOuUSCQyPQxzlDTfyimuurm5wdHREVKptMD2heUahR2T3G0PHDgg01uxKMoir3FxcUHTpk3RuHFjmJmZFdi2sP0vr9dycXJcIyMjsSdoWlqaTI++3PEVZ5ulleuWhsJPoxN9RpSUlNC9e3csW7YMwIduu1OmTMGrV68wZcoUsV3uH+O59ezZE5MmTcKDBw+wYMECcXqHDh0K3fZff/2FtLQ0PHr0SJyWnp6OP/74A8CHM3guLi4wNjZGhw4dsGPHDiQnJ6NHjx7o378/IiMjxTNtnTp1KtaZiqdPn+L48eN4//49Tpw4gZiYGHFezoeGubm5OG3RokVQVVXFv//+i1WrVhV5O5+qXr16sLOzQ0JCApKSktCrVy/4+/vj33//xY4dOwB86Frs6+sL4EM34aSkJLRu3RqmpqZQVlbGsWPHxPV93EU/NwMDA3h7e2PPnj3IysqCt7c3Jk2aBFNTU1y+fBnnzp3DunXrih1TWWrWrBlCQkLw9u1bmeRJHnNzc7EL7eTJk+Hp6Yl169bhypUrctu3b98eRkZGePr0KWJjYwF8KIi4urqKbT6nY1EcrVu3RpUqVfDs2TOsXbsWBgYGaN26NbKysnD37l3Exsbi/PnzuHLlCpSUlNCzZ08sWbIEwIf3fFBQEGxtbXH79m3s2rULe/fuzXdb33//PX7++WdkZmZi+/btmDJlCr755husWbMGSUlJAIA6derAycmpXPY9R8+ePXHhwgUAwIgRI/DmzRtIJBJMmDBBbJPf515JKCkpoUePHli6dClSU1PRpk0bjBo1CpUrV8aDBw9w6dIlbN++HatXr4aHhwe+++47REREAPjQ269GjRowNzfHzJkzi7xNQ0NDeHp6Ijo6GhkZGejatSt+/PFH3Lp1S+bywdLcTyKSxTyLeVaOip5n9erVC//73/8AAH369MHEiRNhY2ODZ8+e4caNG9izZw+8vb1lXvdF1aNHDyxatAjAh+9EExMT2NjYYMGCBeIx9/T0LLUhEkpLcY5JmzZtxLzzzp07aNOmDQICAqCuro7jx4/D0NAQ48aNy3db5Z3XFIUiXsvFzXHbt2+PzZs3A/jwPwoKCsLDhw9lPm8L87nmuhz8nD5b+d0t5sWLF4Xexjj3XQRyphsYGAg1atTI075169ZFuutA7njkPXIPNJeYmCh3W8CHwTQfPHhQ6PaKMqBh/fr1xYH57t27J3NHhpxH7rtS5L51a+79kSe/24vmKI3bGA8YMCDffZNKpcKtW7cKPEb37t3L9ziXxm2MP771bs50eYOxFnT8IiIi8m2X36Ccue+MkvNQV1cXGjRokO//ZezYsTLtx48fn2d7pXUsCiLvrnxFbZ/7/5bbnj178r2V7sf/k9evX8sMqplfu7K8ha68u/IVtb2899vbt2+FZs2a5bv/H99WOb/3t7zjkN/xf/XqVZ47y3z8yB2rt7d3nvlVqlSRua1xjvxeW7du3ZIZePPjx88//1zosSSiomGexTzra86zBEEQ+vbtW+D/vyj/z/z+j7nvqvbxw9jYWLh9+3ah6yiMvLvyFbV9ZGSk3DbFOSZ79+7NNzfL3U7e/7W4eU1+ci+Tc1e+orTP7zVWGq/l/N67+R3/4uS4169fF3R0dPK0yblr98exlGWuW9p4KR99cQwMDHDy5EkEBgaidu3aUFNTg6amJho2bIiIiAhs3LhRbvdMbW1tHDt2DD4+PtDU1ISBgQGGDh2K7du3l/r1tKampjh9+jSGDBmC6tWrQ0VFBdWrV8eQIUNw6tQpVK9evcTrlkqlqFu3LiZOnIhDhw6JlwWZmZlh//79aNSoEaRSKaysrLB06dJCzxiVtkaNGuHs2bPw8/ND9erVoaysDH19fXh5eWH//v0YNmyY2LZXr17w8/ND7dq1oauri0qVKsHIyAgdO3bEsWPHCu36b2Zmhri4OIwfPx62trZQV1eHlpYW6tWrJzPOQHFi+lx8//33+O2332BjYwN1dXU0bNgQ0dHRMgPRfizncr4c8s40fYnHAgDatm2LM2fOoE+fPqhRowZUVFRQuXJl1KtXD2PGjMHWrVvFtrq6uvjnn38wffp0ODk5QSqVQkNDA3Z2dujbt2+h2xo+fDhiYmLg7e0NAwMDKCsrw8TEBH379sXZs2flDtpe1tTU1BATE4PZs2eLXfTV1dXh4OCAkJAQ7N+/H6qqqqW6TT09PbnH0cbGBt9//z1+//13fPPNN2L7rVu3YsSIETA0NISGhgY8PT1x9OhR8bKgoqhZsybOnTuHgIAAWFpaQkVFBTo6OmjevDk2b96M2bNnl+o+ElFezLOYZ+WoyHkW8GHcsLVr18Ld3R26urpQVVWFmZkZvv32WyxatAjDhw8v8bpDQ0OxZcsWuLu7Q0dHByoqKrCwsMCIESNw7ty5Yo2BVp6Kc0y8vb1x9uxZmdzM0NAQHh4eaNasWYHbUUReUxSKeC0XJ8e1sbHBoUOH0Lx5c6ipqcHY2Bg///wzwsPDi7XNzzHXlQhCCUaXI/qC5CRD5ubm4t0NiCqqmjVr4s6dO7Czs8v3sj8iIqLSwjyLiIg+FceYIiL6wr1//x7p6enYv38/7ty5AwBF6hlERERERESkaCxMERF94davX49+/fqJz42MjDB06FAFRkRERERERFQ0HGOKiKiCUFdXR9OmTfHXX38Va1wfIiIiIiIiReEYU0REREREREREpBDsMUVERERERERERArBwhQRERERERERESkEBz+ncpGdnY1Hjx5BW1tbvK0wERFRaRMEAW/evIGJiQmUlHj+jb4ezLWIiKg8lEWuxcIUlYtHjx7B1NRU0WEQEdFX4v79+6hRo4aiwyAqN8y1iIioPJVmrsXCFJULbW1tAB9evDo6OgqOhoiIKqqUlBSYmpqK3ztEXwvmWkREVB7KItdiYYrKRU6Xch0dHSZLRERU5ngpE31tmGsREVF5Ks1ci4MvEBERERERERGRQrAwRURERERERERECsHCFBERERERERERKQQLU0REREREREREpBAsTBERERERERERkUKwMEVERERERERERArBwhQRERERERERESkEC1NERERERERERKQQLEwREREREREREZFCsDBFREREREREREQKwcIUEREREREREREpBAtTRERERERERESkECxMERERERERERGRQrAwRURERERERERECsHCFBERERERERERKQQLU0REREREREREpBDKig6Avi66IbqAuqKjICKiz4kwRVB0CEQVhq5u+WxH4NuWiIhKCXtMERERERERERGRQrAwRURERERERERECsHCFBERERERERERKQQLU0REREREREREpBAsTBERERERERERkUKwMEVERERERERERArBwhQRERERERERESkEC1NERERERERERKQQLEwRERHRZ+Ho0aPw8fGBiYkJJBIJdu7cKTNfEARMnjwZ1apVg1QqRatWrXDjxo0C1xkSEoKGDRtCW1sbRkZG6NixI65duybTxsPDAxKJROYxdOjQ0t49qiAOHz4MiUSC169fF3kZCwsLLFiwQHwu7/X9JVuyZAksLCygrq6Oxo0b49SpU/m2vXz5Mnx9fWFhYQGJRCJzXHJ7+PAhevfuDUNDQ0ilUjg4OODMmTNltAdERKRILEwVw7NnzzBs2DCYmZlBTU0NxsbG8PT0RGxsbKlux9/fHx07dizVdQ4ZMgSVKlXC1q1bS3W9REREpSUtLQ1OTk5YsmSJ3Plz5szBokWLsGzZMvz777/Q1NSEp6cn3r59m+86jxw5ghEjRuDkyZOIiYlBZmYm2rRpg7S0NJl2gwYNQlJSkviYM2dOqe4blR9/f/98i4sjRoyARCKBv79/+QeWS1JSEry9vRUaQ2nZvHkzxowZgylTpuDcuXNwcnKCp6cnnj59Krd9eno6atasidmzZ8PY2Fhum1evXsHNzQ0qKir466+/cOXKFcybNw/6+vpluStERKQgyooO4Evi6+uLd+/eYc2aNahZsyaePHmCgwcP4sWLF4oOrUDp6enYtGkTxo8fj9WrV6NLly6KDomIiCgPb2/vfH+sC4KABQsWYNKkSejQoQMAYO3atahatSp27tyJ7t27y10uOjpa5nlUVBSMjIxw9uxZNG/eXJyuoaGR749k+vKYmppi06ZNmD9/PqRSKQDg7du32LhxI8zMzBQcHSrUay0sLAyDBg1Cv379AADLli3Dnj17sHr1akyYMCFP+4YNG6Jhw4YAIHc+AISGhsLU1BSRkZHiNEtLyzKInoiIPgfsMVVEr1+/xrFjxxAaGooWLVrA3NwcjRo1QmBgIL777juxXVhYGBwcHKCpqQlTU1MMHz4cqamp4vyoqCjo6elh3759sLOzg5aWFry8vJCUlAQACA4Oxpo1a/C///1PvJzg8OHDAICff/4ZtWrVgoaGBmrWrImgoCBkZmYWGvvWrVtRp04dTJgwAUePHsX9+/dl5uf00Jo7dy6qVasGQ0NDjBgxQmbd69atg4uLC7S1tWFsbIyePXvmeyaMiIiotN25cwePHz9Gq1atxGm6urpo3Lgx/vnnnyKvJzk5GQBgYGAgM33Dhg2oXLky6tati8DAQKSnp5dO4KQQ9evXh6mpKbZv3y5O2759O8zMzODs7CxOy8jIwKhRo2BkZAR1dXU0bdoUp0+fllnX3r17UatWLUilUrRo0QJ3797Ns73jx4+jWbNmkEqlMDU1xahRo/L0ysvt40v5SprjKdq7d+9w9uxZmfelkpISWrVqVaz35cd27doFFxcXdOnSBUZGRnB2dsaKFStKI2QiIvoMsTBVRFpaWtDS0sLOnTuRkZGRbzslJSUsWrQIly9fxpo1a/D3339j/PjxMm3S09Mxd+5crFu3DkePHkViYiLGjh0LABg7diy6du0qFquSkpLg6uoKANDW1kZUVBSuXLmChQsXYsWKFZg/f36hsa9atQq9e/eGrq4uvL29ERUVlafNoUOHcOvWLRw6dAhr1qxBVFSUTLvMzExMnz4d58+fx86dO3H37l2Fd4MnIqKvx+PHjwEAVatWlZletWpVcV5hsrOzMXr0aLi5uaFu3bri9J49e2L9+vU4dOgQAgMDsW7dOvTu3bv0gieF6N+/v0yPm9WrV4u9enKMHz8e27Ztw5o1a3Du3DlYW1vD09MTL1++BADcv38fnTt3ho+PD+Lj4zFw4MA8vXxu3boFLy8v+Pr64sKFC9i8eTOOHz+OgICAIsda0hxP0Z4/f46srKxPel/Kc/v2bURERMDGxgb79u3DsGHDMGrUKKxZs+ZTQyYios8QL+UrImVlZURFRWHQoEFYtmwZ6tevD3d3d3Tv3h2Ojo5iu9GjR4t/W1hYYMaMGRg6dCiWLl0qTs/MzMSyZctgZWUFAAgICMC0adMAfCiASaVSZGRk5OnmPWnSJJl1jx07VrxELz83btzAyZMnxTOGvXv3xpgxYzBp0iRIJBKxnb6+PhYvXoxKlSrB1tYW7dq1w8GDBzFo0CAAH5K7HDVr1sSiRYvQsGFDpKamQktLK892MzIyZAp4KSkp+cZIRERUHkaMGIFLly7h+PHjMtMHDx4s/u3g4IBq1arh22+/xa1bt8Tvavry9O7dG4GBgbh37x4AIDY2Fps2bRJ7oqelpSEiIgJRUVHiJaQrVqxATEwMVq1ahXHjxiEiIgJWVlaYN28eAKB27dq4ePEiQkNDxe2EhISgV69eYg5oY2ODRYsWwd3dHREREVBXVy801pLkeBU518rOzoaLiwtmzZoFAHB2dsalS5ewbNky+Pn5KTg6IiIqbewxVQy+vr549OgRdu3aBS8vLxw+fBj169eX6Vl04MABfPvtt6hevTq0tbXRp08fvHjxQuaSAA0NDZlEt1q1akW6LG7z5s1wc3ODsbExtLS0MGnSJCQmJha4zOrVq+Hp6YnKlSsDANq2bYvk5GT8/fffMu3s7e1RqVKlfGM6e/YsfHx8YGZmBm1tbbi7uwNAvtsPCQmBrq6u+DA1NS10/4iIiPKTc7LmyZMnMtOfPHlSpPF6AgICsHv3bhw6dAg1atQosG3jxo0BADdv3ixhtPQ5qFKlCtq1a4eoqChERkaiXbt2Yj4EfOjplJmZCTc3N3GaiooKGjVqhISEBABAQkKC+HrI0aRJE5nn58+fR1RUlNi7XktLC56ensjOzsadO3eKFGtJcrzPIdeqXLkyKlWqVOL3ZX6qVauGOnXqyEyzs7Mr9JgQEdGXiYWpYlJXV0fr1q0RFBSEEydOwN/fH1OmTAEA3L17F+3bt4ejoyO2bduGs2fPincWevfunbgOFRUVmXVKJBIIglDgdv/55x/06tULbdu2xe7duxEXF4eJEyfKrPdjWVlZWLNmDfbs2QNlZWUoKytDQ0MDL1++xOrVq2XayospOzsbwIczip6entDR0cGGDRtw+vRp7NixI89+5RYYGIjk5GTx8fG4VkRERMVhaWkJY2NjHDx4UJyWkpKCf//9N0+hIDdBEBAQEIAdO3bg77//LtIAyvHx8QA+/DimL1v//v0RFRWFNWvWyPT+Lk2pqakYMmQI4uPjxcf58+dx48aNIvW4K0mOB3weuZaqqioaNGgg877Mzs7GwYMHC3xfFsbNzQ3Xrl2TmXb9+nWYm5uXeJ1ERPT54qV8n6hOnTri4JVnz55FdnY25s2bByWlDzW/LVu2FHudqqqqyMrKkpl24sQJmJubY+LEieK0nK7p+dm7dy/evHmDuLg4md5Qly5dQr9+/fD69Wvo6ekVGs/Vq1fx4sULzJ49Wzwbd+bMmQKXUVNTg5qaWqHrJiIiypGamirTS+nOnTuIj4+HgYEBzMzMMHr0aMyYMQM2NjawtLREUFAQTExM0LFjR3EZHx8fmXWOGDECGzduxP/+9z9oa2uL497o6upCKpXi1q1b2LhxI9q2bQtDQ0NcuHABP/74I5o3by5zqT59mby8vPDu3TtIJBJ4enrKzLOysoKqqipiY2PFgkdmZiZOnz4tXpZnZ2eHXbt2ySx38uRJmef169fHlStXYG1tXaIYS5LjAZ9PrjVmzBj4+fnBxcUFjRo1woIFC5CWliaO59W3b19Ur14dISEhAD6c1Lxy5Yr498OHDxEfHw8tLS3xGP74449wdXXFrFmz0LVrV5w6dQrLly/H8uXLFbOTRERUpliYKqIXL16gS5cu6N+/PxwdHaGtrY0zZ85gzpw54m2rra2tkZmZifDwcPj4+CA2NhbLli0r9rYsLCywb98+XLt2DYaGhtDV1YWNjQ0SExOxadMmNGzYEHv27BF7LeVn1apVaNeuHZycnGSm16lTBz/++CM2bNiAESNGFBqPmZkZVFVVER4ejqFDh+LSpUuYPn16sfeLiIioIGfOnEGLFi3E52PGjAEA+Pn5ISoqCuPHj0daWhoGDx6M169fo2nTpoiOjpYZw+fjO6ZFREQAADw8PGSmR0ZGwt/fH6qqqjhw4ID4Y9rU1BS+vr4yY/7Ql6tSpUriZXm5T9IBgKamJoYNG4Zx48aJxc85c+YgPT0dAwYMAAAMHToU8+bNw7hx4zBw4ECcPXs2z01kfv75Z3zzzTcICAjAwIEDoampiStXriAmJgaLFy8uNMaS5Hifk27duuHZs2eYPHkyHj9+jHr16iE6OlocED0xMVE8YQsAjx49krkz4ty5czF37ly4u7uL4381bNgQO3bsQGBgIKZNmwZLS0ssWLAAvXr1Ktd9IyKi8sHCVBFpaWmhcePGmD9/vjgmgampKQYNGoRffvkFAODk5ISwsDCEhoYiMDAQzZs3R0hICPr27VusbQ0aNAiHDx+Gi4sLUlNTcejQIXz33Xf48ccfERAQgIyMDLRr1w5BQUEIDg6Wu44nT55gz5492LhxY555SkpK6NSpE1atWlWkwlSVKlUQFRWFX375BYsWLUL9+vUxd+5cfPfdd8XaLyIiooJ4eHgUeGm7RCLBtGnTxBuGyHPx4kXo6uqKzwu7VN7U1BRHjhwpfrD0xdDR0cl33uzZs5GdnY0+ffrgzZs3cHFxwb59+6Cvrw/gw8m5bdu24ccff0R4eDgaNWqEWbNmyVwW6OjoiCNHjmDixIlo1qwZBEGAlZUVunXrVqT4ipvjfY4CAgLyvQthTrEph4WFRaHvSwBo37492rdvXxrhERHRZ04iFOWbgegTpaSkfPihMAFA4TenISKir4gwpfRSkZzvm+Tk5AILEkQVjZhrIRlA2b/2+QuCiOjrVBa5Fgc/JyIiIiIiIiIihWBhioiIiIiIiIiIFIKFKSIiIiIiIiIiUggWpoiIiIiIiIiISCFYmCIiIiIiIiIiIoVgYYqIiIiIiIiIiBSChSkiIiIiIiIiIlIIFqaIiIiIiIiIiEghWJgiIiIiIiIiIiKFUFZ0APR1SQ5Mho6OjqLDICIiIqqQkpMBplpERPQlYY8pIiIiIiIiIiJSCBamiIiIiIiIiIhIIViYIiIiIiIiIiIihWBhioiIiIiIiIiIFIKFKSIiIiIiIiIiUggWpoiIiIiIiIiISCGUFR0AfV10Q3QBdUVHQUREZUmYIig6BKKvlq6uoiMg+nwI/Doi+iKwxxQRERERERERESkEC1NERERERERERKQQLEwREREREREREZFCsDBFREREREREREQKwcIUEREREREREREpBAtTRERERERERESkECxMERERERERERGRQrAwRURERERERERECsHCFBEREZWJN2/eYPTo0TA3N4dUKoWrqytOnz5d4DJLliyBnZ0dpFIpateujbVr18rM3759O1xcXKCnpwdNTU3Uq1cP69atK8vdICKiL9zRo0fh4+MDExMTSCQS7Ny5s8D2SUlJ6NmzJ2rVqgUlJSWMHj1abrsFCxagdu3akEqlMDU1xY8//oi3b9+W/g4QVXAsTH0mivIBWZjg4GDUq1evVOIhIiL6VAMHDkRMTAzWrVuHixcvok2bNmjVqhUePnwot31ERAQCAwMRHByMy5cvY+rUqRgxYgT+/PNPsY2BgQEmTpyIf/75BxcuXEC/fv3Qr18/7Nu3r7x2iz4zUVFR0NPTU3QYRPQZS0tLg5OTE5YsWVKk9hkZGahSpQomTZoEJycnuW02btyICRMmYMqUKUhISMCqVauwefNm/PLLL6UZOtFXgYWpcuDv7w+JRJLn4eXlVaTlfXx88m177NgxSCQSXLhwAWPHjsXBgwdLM3QiIqIS+e+//7Bt2zbMmTMHzZs3h7W1NYKDg2FtbY2IiAi5y6xbtw5DhgxBt27dULNmTXTv3h2DBw9GaGio2MbDwwOdOnWCnZ0drKys8MMPP8DR0RHHjx8vr12rsD7OVwwNDeHl5YULFy4oNK6oqCgxJiUlJdSoUQP9+vXD06dPAQDdunXD9evXFRpjUd29excSiQTx8fGKDoXoq+Lt7Y0ZM2agU6dORWpvYWGBhQsXom/fvtDV1ZXb5sSJE3Bzc0PPnj1hYWGBNm3aoEePHjh16lRphk70VWBhqpx4eXkhKSlJ5vH7778XadkBAwYgJiYGDx48yDMvMjISLi4ucHR0hJaWFgwNDfNdz7t37+ROz8zMLNpOEBERFdH79++RlZUFdXV1melSqTTfIlJGRobc9qdOnZL7XSUIAg4ePIhr166hefPmpRf8Vyx3vnLw4EEoKyujffv2ig4LOjo6SEpKwoMHD7BixQr89ddf6NOnD4APrxEjIyMFR0hEXxtXV1ecPXtWLETdvn0be/fuRdu2bRUcGdGXh4WpcqKmpgZjY2OZh76+fpGWbd++PapUqYKoqCiZ6ampqdi6dSsGDBgAIO+lfP7+/ujYsSNmzpwJExMT1K5dWzxTt3nzZri7u0NdXR0bNmwAAKxcuRJ2dnZQV1eHra0tli5dKq6rZcuWCAgIkNn+s2fPoKqqyl5aRESUh7a2Npo0aYLp06fj0aNHyMrKwvr16/HPP/8gKSlJ7jKenp5YuXIlzp49C0EQcObMGaxcuRKZmZl4/vy52C45ORlaWlpQVVVFu3btEB4ejtatW5fXrlVoufOVevXqYcKECbh//z6ePXsmtrl48SJatmwJqVQKQ0NDDB48GKmpqeL8w4cPo1GjRtDU1ISenh7c3Nxw7949AMCtW7fQoUMHVK1aFVpaWmjYsCEOHDhQaFwSiQTGxsYwMTGBt7c3Ro0ahQMHDuC///7LcylfUbZhYWGBGTNmoG/fvtDS0oK5uTl27dqFZ8+eoUOHDtDS0oKjoyPOnDkjs9y2bdtgb28PNTU1WFhYYN68eXnWO2vWLPTv3x/a2towMzPD8uXLxfmWlpYAAGdnZ0gkEnh4eIjzCsrDiOjz07NnT0ybNg1NmzaFiooKrKys4OHhwUv5iEqAhakvgLKyMvr27YuoqCgIgiBO37p1K7KystCjR498l805kxwTE4Pdu3eL0ydMmIAffvgBCQkJ8PT0xIYNGzB58mTMnDkTCQkJmDVrFoKCgrBmzRoAH8YJ2bhxIzIyMsR1rF+/HtWrV0fLli3zbDcjIwMpKSkyDyIi+rqsW7cOgiCgevXqUFNTw6JFi9CjRw8oKclPP4KCguDt7Y1vvvkGKioq6NChA/z8/ABAZhltbW3Ex8fj9OnTmDlzJsaMGYPDhw+Xxy59VVJTU7F+/XpYW1uLPbLT0tLg6ekJfX19nD59Glu3bsWBAwfEk1fv379Hx44d4e7ujgsXLuCff/7B4MGDIZFIxHW2bdsWBw8eRFxcHLy8vODj44PExMRixSaVSpGdnY3379/Ljbso25g/fz7c3NwQFxeHdu3aoU+fPujbty969+6Nc+fOwcrKCn379hVzr7Nnz6Jr167o3r07Ll68iODgYAQFBeU5cThv3jy4uLggLi4Ow4cPx7Bhw3Dt2jUAEHtWHDhwAElJSdi+fTsAFJqHycNci0ixDh8+jFmzZmHp0qU4d+4ctm/fjj179mD69OmKDo3oi8PCVDnZvXs3tLS0ZB6zZs0q8vL9+/fHrVu3cOTIEXFaZGQkfH19873uGQA0NTWxcuVK2Nvbw97eXpw+evRodO7cGZaWlqhWrRqmTJmCefPmidM6d+6MH3/8Eb/99hsAoHPnzgCA//3vf+I6oqKixPEoPhYSEgJdXV3xYWpqWuR9JSKiisHKygpHjhxBamoq7t+/L16SV7NmTbntpVIpVq9ejfT0dNy9exeJiYmwsLCAtrY2qlSpIrZTUlKCtbU16tWrh59++gnff/89QkJCymu3KrTc+Yq2tjZ27dqFzZs3i4XBjRs34u3bt1i7di3q1q2Lli1bYvHixVi3bh2ePHmClJQUJCcno3379rCysoKdnR38/PxgZmYGAHBycsKQIUNQt25d2NjYYPr06bCyssKuXbuKHOONGzewbNkyuLi4QFtbO8/8om6jbdu2GDJkCGxsbDB58mSkpKSgYcOG6NKlC2rVqoWff/4ZCQkJePLkCQAgLCwM3377LYKCglCrVi34+/sjICAAv/76a571Dh8+HNbW1vj5559RuXJlHDp0CADE17GhoSGMjY1hYGAAAIXmYfIw1yJSrKCgIPTp0wcDBw6Eg4MDOnXqhFmzZiEkJATZ2dmKDo/oi8LCVDlp0aIF4uPjZR5Dhw4t8vK2trZwdXXF6tWrAQA3b97EsWPHxMv48uPg4ABVVdU8011cXMS/09LScOvWLQwYMECmcDZjxgzcunULAKCuro4+ffqI2z937hwuXboEf39/udsNDAxEcnKy+Lh//36R95WIiCoWTU1NVKtWDa9evcK+ffvQoUOHAturqKigRo0aqFSpEjZt2oT27dvn28sKALKzs2V69FLJ5c5XTp06BU9PT3h7e4uX4iUkJMDJyQmampriMm5ubsjOzsa1a9dgYGAAf39/eHp6wsfHBwsXLpS5dDM1NRVjx46FnZ0d9PT0oKWlhYSEhEJ7TOVcvqmhoYHatWujatWq4lAEHyvqNhwdHcW/q1atCuBD3vTxtJxB1hMSEuDm5iazDjc3N9y4cQNZWVly15tzCWLOOuQpSh4mD3MtIsVKT0/P891UqVIlAJC5yoWICqes6AC+FpqamrC2tv6kdQwYMAAjR47EkiVLEBkZCSsrK7i7uxe63cKm54wLsWLFCjRu3FimXc6HK/Dhcr569erhwYMHiIyMRMuWLWFubi53/WpqalBTUyvSfhERUcW0b98+CIKA2rVr4+bNmxg3bhxsbW3Rr18/AB9+WD98+BBr164FAFy/fh2nTp1C48aN8erVK4SFheHSpUsylzOFhITAxcUFVlZWyMjIwN69e7Fu3bp87/RHxfNxvrJy5Uro6upixYoVmDFjRpHWERkZiVGjRiE6OhqbN2/GpEmTEBMTg2+++QZjx45FTEwM5s6dC2tra0ilUnz//ff53qAlh7a2Ns6dOwclJSVUq1YNUqk037ZF3YaKior4d07vb3nTitvzIfc6ctZT0DqKmod9jLkWUdGlpqbi5s2b4vM7d+4gPj4eBgYGMDMzy/N9BEC8e2ZqaiqePXuG+Ph4qKqqok6dOgA+3Dk9LCwMzs7OaNy4MW7evImgoCD4+PgU+N4lorxYmPqCdO3aFT/88AM2btyItWvXYtiwYXIvoyuuqlWrwsTEBLdv30avXr3ybefg4AAXFxesWLECGzduxOLFiz9520REVHElJycjMDAQDx48gIGBAXx9fTFz5kzxh3tSUpJML5asrCzMmzcP165dg4qKClq0aIETJ07AwsJCbJOWlobhw4fjwYMHkEqlsLW1xfr169GtW7fy3r2vgkQigZKSEv777z8AgJ2dHaKiopCWliae5IqNjYWSkhJq164tLufs7AxnZ2cEBgaiSZMm2LhxI7755hvExsbC399fvGV7amoq7t69W2gcOZdvFkVJt1EYOzs7xMbG5tlWrVq1ivwjNKcXe+4eVkXNw4io5M6cOYMWLVqIz8eMGQMA8PPzQ1RUVJ7vI+DD51iOs2fPYuPGjTA3Nxc/TyZNmgSJRIJJkybh4cOHqFKlCnx8fDBz5syy3yGiCoaFqXKSkZGBx48fy0xTVlZG5cqVi7wOLS0tdOvWDYGBgUhJScn3MrqSmDp1KkaNGgVdXV14eXkhIyMDZ86cwatXr8QPbuBDr6mAgABoamqKCR8REZE8Xbt2RdeuXfOd//Gg0XZ2doiLiytwnTNmzChyzx0qvtz5yqtXr7B48WKkpqbCx8cHANCrVy9MmTIFfn5+CA4OxrNnzzBy5Ej06dMHVatWxZ07d7B8+XJ89913MDExwbVr13Djxg307dsXAGBjY4Pt27fDx8cHEokEQUFBpT4WS1lt46effkLDhg0xffp0dOvWDf/88w8WL15crLvnGRkZQSqVIjo6GjVq1IC6ujp0dXWLnIcRUcl4eHgUeHndx99HQOGX4ykrK2PKlCmYMmXKp4ZH9NXjGFPlJDo6GtWqVZN5NG3atNjrGTBgAF69egVPT0+YmJiUWnwDBw7EypUrERkZCQcHB7i7uyMqKkq8rXGOHj16QFlZGT169IC6unqpbZ+IiIgUL3e+0rhxY/HOex4eHgAADQ0N7Nu3Dy9fvkTDhg3x/fff49tvvxV7UWtoaODq1avw9fVFrVq1MHjwYIwYMQJDhgwB8GEAcX19fbi6usLHxweenp6oX79+qe5DWW2jfv362LJlCzZt2oS6deti8uTJmDZtWrFOFCorK2PRokX47bffYGJiIo63VtQ8jIiIqCKSCByZjYrh7t27sLKywunTp4uV5KWkpHy4e+AEAKxnERFVaMIUxaUWOd83ycnJ0NHRUVgcROVNzLWQDICvfSIA4C9dotJXFrkWL+WjIsnMzMSLFy8wadIkfPPNN6V+dpOIiIiIiIiIvj68lI+KJDY2FtWqVcPp06exbNkyRYdDRERERERERBUAe0xRkRQ2YCARERERERERUXGxxxQRERERERERESkEC1NERERERERERKQQLEwREREREREREZFCsDBFREREREREREQKwcIUEREREREREREpBO/KR+UqOTAZOjo6ig6DiIiIqEJKTgaYahER0ZeEPaaIiIiIiIiIiEghWJgiIiIiIiIiIiKFYGGKiIiIiIiIiIgUgoUpIiIiIiIiIiJSCBamiIiIiIiIiIhIIViYIiIiIiIiIiIihWBhioiIiIiIiIiIFEJZ0QHQ10U3RBdQV3QURERfNmGKoOgQiOgzpaur6AiIvm4Cv6KJio09poiIiIiIiIiISCFYmCIiIiIiIiIiIoVgYYqIiIiIiIiIiBSChSkiIiIiIiIiIlIIFqaIiIiIiIiIiEghWJgiIiIiIiIiIiKFYGGKiIiIiIiIiIgUgoUpIiIiIiIiIiJSCBamPnMWFhZYsGBBkdsHBwejXr16n7zdw4cPQyKR4PXr15+8LiIiKn1ZWVkICgqCpaUlpFIprKysMH36dAiCUOByGzZsgJOTEzQ0NFCtWjX0798fL168EOdnZmZi2rRpsLKygrq6OpycnBAdHV3Wu0NERFShHD16FD4+PjAxMYFEIsHOnTsLbH/8+HG4ubnB0NAQUqkUtra2mD9/vkyb4OBgSCQSmYetrW0Z7gVR+ahQhSl/f3907Nix1NcbFxeHLl26oGrVqlBXV4eNjQ0GDRqE69evl/q2Pheurq5ISkqCrq6uokMhIiI5QkNDERERgcWLFyMhIQGhoaGYM2cOwsPD810mNjYWffv2xYABA3D58mVs3boVp06dwqBBg8Q2kyZNwm+//Ybw8HBcuXIFQ4cORadOnRAXF1ceu0WkUP7+/uKPPRUVFVhaWmL8+PF4+/atokMjoi9MWloanJycsGTJkiK119TUREBAAI4ePYqEhARMmjQJkyZNwvLly2Xa2dvbIykpSXwcP368LMInKlfKig7gc7d79274+vrC09MTGzZsgJWVFZ4+fYqtW7ciKCgImzdvVnSIpS4zMxOqqqowNjZWdChERJSPEydOoEOHDmjXrh2ADz1sf//9d5w6dSrfZf755x9YWFhg1KhRAABLS0sMGTIEoaGhYpt169Zh4sSJaNu2LQBg2LBhOHDgAObNm4f169eX4R4RfR68vLwQGRmJzMxMnD17Fn5+fpBIJDLvEyKiwnh7e8Pb27vI7Z2dneHs7Cw+t7CwwPbt23Hs2DEMHjxYnK6srMzfaVThVKgeU4UJCwuDg4MDNDU1YWpqiuHDhyM1NTXf9unp6ejXrx/atm2LXbt2oVWrVrC0tETjxo0xd+5c/PbbbwA+XE4xYMAA8XKK2rVrY+HChTLryunNNXfuXFSrVg2GhoYYMWIEMjMzxTZPnz6Fj48PpFIpLC0tsWHDhjwxvX79GgMHDkSVKlWgo6ODli1b4vz58/nuw+nTp9G6dWtUrlwZurq6cHd3x7lz52TaSCQSRERE4LvvvoOmpiZmzpyZ51K+Fy9eoEePHqhevTo0NDTg4OCA33//vdBjTkREZcPV1RUHDx4Ue++eP38ex48fLzAJbtKkCe7fv4+9e/dCEAQ8efIEf/zxh1iEAoCMjAyoq6vLLCeVSnlGlr4aampqMDY2hqmpKTp27IhWrVohJiYGwIf3x6hRo2BkZAR1dXU0bdoUp0+fFpfNyZ/27dsHZ2dnSKVStGzZEk+fPsVff/0FOzs76OjooGfPnkhPTxeXi46ORtOmTaGnpwdDQ0O0b98et27dKvd9J6LPR1xcHE6cOAF3d3eZ6Tdu3ICJiQlq1qyJXr16ITExUUEREpWer6owpaSkhEWLFuHy5ctYs2YN/v77b4wfPz7f9vv27cPz58/zbaOnpwcAyM7ORo0aNbB161ZcuXIFkydPxi+//IItW7bItD906BBu3bqFQ4cOYc2aNYiKikJUVJQ439/fH/fv38ehQ4fwxx9/YOnSpXj69KnMOrp06SImN2fPnkX9+vXx7bff4uXLl3JjfPPmDfz8/HD8+HGcPHkSNjY2aNu2Ld68eSPTLjg4GJ06dcLFixfRv3//POt5+/YtGjRogD179uDSpUsYPHgw+vTpU+CZeSIiKjsTJkxA9+7dYWtrCxUVFTg7O2P06NHo1atXvsu4ublhw4YN6Natm9gzVldXV+YyA09PT4SFheHGjRvIzs5GTEwMtm/fjqSkpPLYLaLPyqVLl3DixAmoqqoCAMaPH49t27ZhzZo1OHfuHKytreHp6ZknDwsODsbixYtx4sQJ3L9/H127dsWCBQuwceNG7NmzB/v375e57DYtLQ1jxozBmTNncPDgQSgpKaFTp07Izs4u1/0lIsWrUaMG1NTU4OLighEjRmDgwIHivMaNGyMqKgrR0dGIiIjAnTt30KxZszy/7Yi+NF/VpXyjR48W/7awsMCMGTMwdOhQLF26VG77GzduAEChA8qpqKhg6tSp4nNLS0v8888/2LJlC7p27SpO19fXx+LFi1GpUiXY2tqiXbt2OHjwoDhe1V9//YVTp06hYcOGAIBVq1bBzs5OXP748eM4deoUnj59CjU1NQDA3LlzsXPnTvzxxx8yXTxztGzZUub58uXLoaenhyNHjqB9+/bi9J49e6Jfv37i89u3b8ssV716dYwdO1Z8PnLkSOzbtw9btmxBo0aN8mw3IyMDGRkZ4vOUlJR8jh4REZXEli1bsGHDBmzcuBH29vaIj4/H6NGjYWJiAj8/P7nLXLlyBT/88AMmT54MT09PJCUlYdy4cRg6dChWrVoFAFi4cCEGDRoEW1tbSCQSWFlZoV+/fli9enV57h6RwuzevRtaWlp4//49MjIyoKSkhMWLFyMtLQ0RERGIiooSeyauWLECMTExWLVqFcaNGyeuY8aMGXBzcwMADBgwAIGBgbh16xZq1qwJAPj+++9x6NAh/PzzzwAAX19fmRhWr16NKlWq4MqVK6hbt67cOJlrEVVMx44dQ2pqKk6ePIkJEybA2toaPXr0AACZXtGOjo5o3LgxzM3NsWXLFgwYMEBRIRN9sq+qMHXgwAGEhITg6tWrSElJwfv37/H27Vukp6dDQ0MjT/vC7myU25IlS7B69WokJibiv//+w7t37/LcHc/e3h6VKlUSn1erVg0XL14EACQkJEBZWRkNGjQQ59va2oq9soAPl2mkpqbC0NBQZr3//fdfvt29nzx5gkmTJuHw4cN4+vQpsrKykJ6enqfLp4uLS4H7l5WVhVmzZmHLli14+PAh3r17h4yMDLnHDQBCQkJkinVERFS6xo0bJ/aaAgAHBwfcu3cPISEh+RamQkJC4ObmJv6AdnR0hKamJpo1a4YZM2agWrVqqFKlCnbu3Im3b9/ixYsXMDExwYQJE8Qf1EQVXYsWLRAREYG0tDTMnz8fysrK8PX1xYULF5CZmSkWnIAPJycbNWqEhIQEmXU4OjqKf1etWhUaGhoy76GqVavK9Dq/ceMGJk+ejH///RfPnz8Xe0olJibmW5hirkVUMVlaWgL48L3+5MkTBAcHi4Wpj+np6aFWrVq4efNmeYZIVOq+mkv57t69i/bt28PR0RHbtm3D2bNnxUsX3r17J3eZWrVqAQCuXr1a4Lo3bdqEsWPHYsCAAdi/fz/i4+PRr1+/POtVUVGReS6RSIrVRTs1NRXVqlVDfHy8zOPatWsyZ+ly8/PzQ3x8PBYuXIgTJ04gPj4ehoaGeWLT1NQscNu//vorFi5ciJ9//hmHDh1CfHw8PD098z12gYGBSE5OFh/3798v8n4SEVHh0tPToaQk+zVeqVKlAr9X8lsGyHsyRl1dHdWrV8f79++xbds2dOjQoZQiJ/q8aWpqwtraGk5OTli9ejX+/fdfsUdhUeXO+XLu8Jfbxzmgj48PXr58iRUrVuDff//Fv//+CyD/HBVgrkX0NcjOzpbpGfmx1NRU3Lp1C9WqVSvHqIhK31fTY+rs2bPIzs7GvHnzxKT84zGgPtamTRtUrlwZc+bMwY4dO/LMf/36NfT09BAbGwtXV1cMHz5cnFfcASttbW3x/v17nD17VryU79q1a+Lg4wBQv359PH78GMrKyrCwsCjSemNjY7F06VJxYNv79+/j+fPnxYotZz0dOnRA7969AXz4kLx+/Trq1Kkjt72ampp4uSEREZU+Hx8fzJw5E2ZmZrC3t0dcXBzCwsJkxgkMDAzEw4cPsXbtWnGZQYMGISIiQryUb/To0WjUqBFMTEwAAP/++y8ePnyIevXq4eHDhwgODkZ2dnaBYzISVVRKSkr45ZdfMGbMGNy8eROqqqqIjY2Fubk5gA93Mj59+rTMcBHF9eLFC1y7dg0rVqxAs2bNAKBINxtgrkX0eUtNTZXpyXTnzh3Ex8fDwMAAZmZmeb6jlyxZAjMzM3EYmaNHj2Lu3LninXQBYOzYsfDx8YG5uTkePXqEKVOmoFKlSvn2qCL6UlS4wlRycjLi4+NlphkaGsLa2hqZmZkIDw+Hj48PYmNjsWzZsgLXpampiZUrV6JLly747rvvMGrUKFhbW+P58+fYsmULEhMTsWnTJtjY2GDt2rXYt28fLC0tsW7dOpw+fVrshlkUtWvXhpeXF4YMGYKIiAgoKytj9OjRkEqlYptWrVqhSZMm6NixI+bMmYNatWrh0aNH2LNnDzp16iT3cjwbGxusW7cOLi4uSElJwbhx42TWWVQ2Njb4448/cOLECejr6yMsLAxPnjzJtzBFRERlKzw8HEFBQRg+fDiePn0KExMTDBkyBJMnTxbbJCUlyVy67e/vjzdv3mDx4sX46aefoKenh5YtWyI0NFRs8/btW0yaNAm3b9+GlpYW2rZti3Xr1slcWk70NenSpQvGjRuHiIgIDBs2DOPGjRN/WM6ZMwfp6emfNLaLvr4+DA0NsXz5clSrVg2JiYmYMGFCKe4BESnCmTNn0KJFC/H5mDFjAHy4oiUqKirPd3R2djYCAwNx584dKCsrw8rKCqGhoRgyZIjY5sGDB+jRowdevHiBKlWqoGnTpjh58iSqVKlSfjtGVAYqXGHq8OHDcHZ2lpk2YMAArFy5EmFhYQgNDUVgYCCaN2+OkJAQ9O3bt8D1dejQASdOnEBISAh69uyJlJQUmJqaomXLlpgxYwYAYMiQIYiLi0O3bt0gkUjQo0cPDB8+HH/99VexYo+MjMTAgQPh7u6OqlWrYsaMGQgKChLnSyQS7N27FxMnTkS/fv3w7NkzGBsbo3nz5qhatarcda5atQqDBw9G/fr1YWpqilmzZskMYl5UOT9SPD09oaGhgcGDB6Njx45ITk4u9rqIiOjTaWtrY8GCBViwYEG+bXLf+TXHyJEjMXLkyHyXcXd3x5UrV0ohQqKKQVlZGQEBAZgzZw7u3LmD7Oxs9OnTB2/evIGLiwv27dsHfX39Eq9fSUkJmzZtwqhRo1C3bl3Url0bixYtgoeHR+ntBBGVOw8PjwLHLP74O7qw72fgwxAyRBWRRCjOCN9EJZSSkgJdXV1gAgB1RUdDRPRlE6bwqzs/Od83ycnJ0NHRUXQ4ROVGzLWQDICvfSJF4a9rqujKItf6agY/JyIiIiIiIiKizwsLU0REREREREREpBAsTBERERERERERkUKwMEVERERERERERArBwhQRERERERERESkEC1NERERERERERKQQLEwREREREREREZFCsDBFREREREREREQKwcIUEREREREREREphLKiA6CvS3JgMnR0dBQdBhEREVGFlJwMMNUiIqIvCXtMERERERERERGRQrAwRURERERERERECsHCFBERERERERERKQQLU0REREREREREpBAsTBERERERERERkUKwMEVERERERERERAqhrOgA6OuiG6ILqCs6CiKiL4swRVB0CET0hdDVVXQERPS5E5hW0GeGPaaIiIiIiIiIiEghWJgiIiIiIiIiIiKFYGGKiIiIiIiIiIgUgoUpIiIiIiIiIiJSCBamiIiIiIiIiIhIIViYIiIiIiIiIiIihWBhioiIiIiIiIiIFIKFKSIiIiIiIiIiUggWpoiIiL4AWVlZCAoKgqWlJaRSKaysrDB9+nQIgpDvMv7+/pBIJHke9vb2YhsLCwu5bUaMGFEeu0VEREQKcPToUfj4+MDExAQSiQQ7d+4ssP3hw4fl5guPHz8W27x58wajR4+Gubk5pFIpXF1dcfr06TLeE6oIWJiiErOwsMCCBQsUHQYR0VchNDQUERERWLx4MRISEhAaGoo5c+YgPDw832UWLlyIpKQk8XH//n0YGBigS5cuYpvTp0/LtImJiQEAmTZEipb7R9Pdu3chkUgQHx+v0JiKgrkSEX2u0tLS4OTkhCVLlhRruWvXrsnkDUZGRuK8gQMHIiYmBuvWrcPFixfRpk0btGrVCg8fPizt8KmCYWGqGPz9/dGxY8dSXWfOmepNmzblmWdvbw+JRIKoqKhS3SYREX15Tpw4gQ4dOqBdu3awsLDA999/jzZt2uDUqVP5LqOrqwtjY2PxcebMGbx69Qr9+vUT21SpUkWmze7du2FlZQV3d/fy2C0iUUF5VlJSEry9vcsljqL0HCAi+tJ5e3tjxowZ6NSpU7GWMzIykskblJQ+lBT+++8/bNu2DXPmzEHz5s1hbW2N4OBgWFtbIyIioix2gSoQFqY+A6ampoiMjJSZdvLkSTx+/BiampqftO5379590vJERPR5cHV1xcGDB3H9+nUAwPnz53H8+PFi/VhftWoVWrVqBXNzc7nz3717h/Xr16N///6QSCSlEjdRaTA2NoaamlqZbuNzzJk+x5iI6OtWr149VKtWDa1bt0ZsbKw4/f3798jKyoK6urpMe6lUiuPHj5d3mPSFYWGqFIWFhcHBwQGampowNTXF8OHDkZqaWuhyvXr1wpEjR3D//n1x2urVq9GrVy8oKyvLtH39+jUGDhyIKlWqQEdHBy1btsT58+fF+cHBwahXrx5WrlwJS0tL8YPh9evXGDJkCKpWrQp1dXXUrVsXu3fvFpc7fvw4mjVrBqlUClNTU4waNQppaWni/KdPn8LHxwdSqRSWlpbYsGFDiY8TEREV34QJE9C9e3fY2tpCRUUFzs7OGD16NHr16lWk5R89eoS//voLAwcOzLfNzp078fr1a/j7+5dS1ESlQ14vpqtXr8LV1VXMa44cOSIz/9KlS/D29oaWlhaqVq2KPn364Pnz5+J8Dw8PBAQEYPTo0ahcuTI8PT1hYWEBAOjUqRMkEon4/NatW+jQoQOqVq0KLS0tNGzYEAcOHJDZXlFypcTERHTo0AFaWlrQ0dFB165d8eTJE3F+fnkcEZGiVatWDcuWLcO2bduwbds2mJqawsPDA+fOnQMAaGtro0mTJpg+fToePXqErKwsrF+/Hv/88w+SkpIUHD197liYKkVKSkpYtGgRLl++jDVr1uDvv//G+PHjC12uatWq8PT0xJo1awAA6enp2Lx5M/r375+nbZcuXfD06VP89ddfOHv2LOrXr49vv/0WL1++FNvcvHkT27Ztw/bt2xEfH4/s7Gx4e3sjNjYW69evx5UrVzB79mxUqlQJwIdky8vLC76+vrhw4QI2b96M48ePIyAgQFynv78/7t+/j0OHDuGPP/7A0qVL8fTp03z3KSMjAykpKTIPIiIquS1btmDDhg3YuHEjzp07hzVr1mDu3Lnid0dh1qxZAz09vQIvSV+1ahW8vb1hYmJSSlETlZ1x48bhp59+QlxcHJo0aQIfHx+8ePECwIcTci1btoSzszPOnDmD6OhoPHnyBF27dpVZx5o1a6CqqorY2FgsW7ZMHKQ3MjISSUlJ4vPU1FS0bdsWBw8eRFxcHLy8vODj44PExERxXYXlStnZ2ejQoQNevnyJI0eOICYmBrdv30a3bt1kYvo4j8sPcy0iKk+1a9fGkCFD0KBBA7i6umL16tVwdXXF/PnzxTbr1q2DIAioXr061NTUsGjRIvTo0UO83I8oP8qFN6GiGj16tPi3hYUFZsyYgaFDh2Lp0qWFLtu/f3/89NNPmDhxIv744w9YWVmhXr16Mm2OHz+OU6dO4enTp2J39rlz52Lnzp34448/MHjwYAAfun2vXbsWVapUAQDs378fp06dQkJCAmrVqgUAqFmzprjekJAQ9OrVS4zfxsYGixYtgru7OyIiIpCYmIi//voLp06dQsOGDQF8+PFiZ2eX7/6EhIRg6tSphe43EREVzbhx48ReUwDg4OCAe/fuISQkBH5+fgUuKwgCVq9ejT59+kBVVVVum3v37uHAgQPYvn17qcdOVBYCAgLg6+sLAIiIiEB0dDRWrVqF8ePHY/HixXB2dsasWbPE9qtXr4apqSmuX78u5kM2NjaYM2dOnnXr6enB2NhYfO7k5AQnJyfx+fTp07Fjxw7s2rULAQEBuH79eqG50sGDB3Hx4kXcuXMHpqamAIC1a9fC3t4ep0+fFpf7OI/LD3MtIlK0Ro0ayVymZ2VlhSNHjiAtLQ0pKSmoVq0aunXrJvPbk0geli5L0YEDB/Dtt9+ievXq0NbWRp8+ffDixQukp6cXumy7du2QmpqKo0ePYvXq1XJ7S50/fx6pqakwNDSElpaW+Lhz5w5u3boltjM3N5dJZuLj41GjRg0xCZO33qioKJl1enp6Ijs7G3fu3EFCQgKUlZXRoEEDcRlbW1vo6enluz+BgYFITk4WH7kvUyQiouJLT0/Pc8axUqVKyM7OLnTZI0eO4ObNmxgwYEC+bSIjI2FkZIR27dp9cqxE5aFJkybi38rKynBxcUFCQgKAD7nNoUOHZHIbW1tbAJDJmXLnNgVJTU3F2LFjYWdnBz09PWhpaSEhIUHsMVWUXCkhIQGmpqZiUQoA6tSpAz09PTFuIG8elx/mWkSkaPHx8ahWrVqe6ZqamqhWrRpevXqFffv2oUOHDgqIjr4k7DFVSu7evYv27dtj2LBhmDlzJgwMDHD8+HEMGDAA7969g4aGRoHLKysro0+fPpgyZQr+/fdf7NixI0+b1NRUVKtWDYcPH84zL3fi8/GA6VKptMBtp6amYsiQIRg1alSeeWZmZuJAu8WhpqZW5oOUEhF9TXx8fDBz5kyYmZnB3t4ecXFxCAsLkzmRERgYiIcPH2Lt2rUyy65atQqNGzdG3bp15a47OzsbkZGR8PPzyzO2IdGXKDU1FT4+PggNDc0zL/ePqKLeZGbs2LGIiYnB3LlzYW1tDalUiu+//75MBicvakzMtYjoU6SmpuLmzZvi8zt37iA+Ph4GBgYwMzPLk1MsWLAAlpaWsLe3x9u3b7Fy5Ur8/fff2L9/v7iOffv2QRAE1K5dGzdv3sS4ceNga2srczdgInmYfZaSs2fPIjs7G/PmzRPPaG/ZsqVY6+jfvz/mzp2Lbt26QV9fP8/8+vXr4/Hjx1BWVhYH4ywKR0dHPHjwQKbr+sfrvXLlCqytreUub2tri/fv3+Ps2bNiN/Nr167h9evXRY6BiIg+TXh4OIKCgjB8+HA8ffoUJiYmGDJkCCZPniy2SUpKkhnzBgCSk5Oxbds2LFy4MN91HzhwAImJiXJ76xJ9rk6ePInmzZsDgJin5IyPWb9+fWzbtg0WFhbFLraqqKggKytLZlpsbCz8/f3F26qnpqbi7t274vyi5Ep2dna4f/8+7t+/L/aaunLlCl6/fo06deoUK0Yiok915swZtGjRQnw+ZswYAICfnx+ioqLy5BTv3r3DTz/9hIcPH0JDQwOOjo44cOCAzDqSk5MRGBiIBw8ewMDAAL6+vpg5cyZUVFTKb8foi8TCVDElJyfnGYjS0NAQ1tbWyMzMRHh4OHx8fMRBNIvDzs4Oz58/z7d3VatWrdCkSRN07NgRc+bMQa1atfDo0SPs2bMHnTp1gouLi9zl3N3d0bx5c/j6+iIsLAzW1ta4evUqJBIJvLy88PPPP+Obb75BQEAABg4cCE1NTVy5cgUxMTFYvHgxateuDS8vLwwZMgQRERFQVlbG6NGjC+2JRUREpUdbWxsLFizAggUL8m0TFRWVZ5qurm6hl5S3adMGgiB8YoREny6/PEueJUuWwMbGBnZ2dpg/fz5evXolFldHjBiBFStWoEePHhg/fjwMDAxw8+ZNbNq0CStXrhRvACOPhYUFDh48CDc3N6ipqUFfXx82NjbYvn07fHx8IJFIEBQUJHMZbVFypVatWsHBwQG9evXCggUL8P79ewwfPhzu7u755nBERGXFw8OjwO/+j3OK8ePHF3pjr65du+a5yQRRUXCMqWI6fPgwnJ2dZR5Tp06Fk5MTwsLCEBoairp162LDhg0ICQkp9voNDQ3zLfhIJBLs3bsXzZs3R79+/VCrVi10794d9+7dQ9WqVQtc77Zt29CwYUP06NEDderUwfjx48WzgY6Ojjhy5AiuX7+OZs2awdnZGZMnT5a5K1NkZCRMTEzg7u6Ozp07Y/DgwTAyMir2/hERERHlJ788S57Zs2dj9uzZcHJywvHjx7Fr1y5UrlwZAGBiYoLY2FhkZWWhTZs2cHBwwOjRo6Gnp1fo3aHmzZuHmJgYmJqawtnZGQAQFhYGfX19uLq6wsfHB56enqhfv77McoXlShKJBP/73/+gr6+P5s2bo1WrVqhZsyY2b978KYeMiIjoiycReIqUykFKSgp0dXWBCQDUFR0NEdGXRZjCr+qiyvm+SU5Oho6OjqLDISo3Yq6FZAB87RNR/lgBoE9RFrkWe0wREREREREREZFCsDBFREREREREREQKwcIUEREREREREREpBAtTRERERERERESkECxMERERERERERGRQrAwRURERERERERECsHCFBERERERERERKQQLU0REREREREREpBDKig6Avi7JgcnQ0dFRdBhEREREFVJyMsBUi4iIviTsMUVERERERERERArBwhQRERERERERESkEC1NERERERERERKQQLEwREREREREREZFCsDBFREREREREREQKwcIUEREREREREREpBAtTRERERERERESkEMqKDoC+LrohuoC6oqMgIlIsYYqg6BCIqILS1VV0BET0tRKY3lAJsccUEREREREREREpBAtTRERERERERESkECxMERERERERERGRQrAwRURERERERERECsHCFBERERERERERKQQLU0REREREREREpBAsTBERERERERERkUKwMEVERERERERERArBwlQZkkgk2Llzp6LDkMvDwwOjR48Wn1tYWGDBggXi8885diKiiiArKwtBQUGwtLSEVCqFlZUVpk+fDkEQirR8bGwslJWVUa9ePZnpFhYWkEgkeR4jRowog70govxERUVBT09P0WEQEZWro0ePwsfHByYmJkX6Tenv7y83b7G3txfbhISEoGHDhtDW1oaRkRE6duyIa9eulfGeUHliYaqE8nsDeXl5FWs9jx8/xsiRI1GzZk2oqanB1NQUPj4+OHjwYKnEefjwYUgkErx+/Vpm+vbt2zF9+vRS2QYRERVfaGgoIiIisHjxYiQkJCA0NBRz5sxBeHh4ocu+fv0affv2xbfffptn3unTp5GUlCQ+YmJiAABdunQp9X0gKiv+/v7o2LFjuW3Pw8NDbl73/v37Eq+zW7duuH79eilGSUT0+UtLS4OTkxOWLFlSpPYLFy6UyVvu378PAwMDmbzlyJEjGDFiBE6ePImYmBhkZmaiTZs2SEtLK6vdoHKmrOgAvmReXl6IjIyUmaamplbk5e/evQs3Nzfo6enh119/hYODAzIzM7Fv3z6MGDECV69eLe2QRQYGBmW2biIiKtyJEyfQoUMHtGvXDsCHnk6///47Tp06VeiyQ4cORc+ePVGpUqU8ZyKrVKki83z27NmwsrKCu7t7qcVOVBENGjQI06ZNk5mmrFyyVDkzMxNSqRRSqbQ0QiMi+mJ4e3vD29u7yO11dXWhq6srPt+5cydevXqFfv36idOio6NllomKioKRkRHOnj2L5s2bf3rQpHDsMfUJ1NTUYGxsLPPQ19cv8vLDhw+HRCLBqVOn4Ovri1q1asHe3h5jxozByZMnxXZhYWFwcHCApqYmTE1NMXz4cKSmporz7927Bx8fH+jr60NTUxP29vbYu3cv7t69ixYtWgAA9PX1IZFI4O/vDyDvpXyFuXjxIlq2bAmpVApDQ0MMHjxYJgYiIioeV1dXHDx4UOxRcf78eRw/frzQZC4yMhK3b9/GlClTCt3Gu3fvsH79evTv3x8SiaRU4ib6HJQ0NyqIhoZGnrwux8qVK2FnZwd1dXXY2tpi6dKl4ry7d+9CIpFg8+bNcHd3h7q6OjZs2JDnUr5bt26hQ4cOqFq1KrS0tNCwYUMcOHBAJoalS5fCxsYG6urqqFq1Kr7//vtPPFJERF+WVatWoVWrVjA3N8+3TXJyMgB2tqhI2GNKQV6+fIno6GjMnDkTmpqaeebnTmSUlJSwaNEiWFpa4vbt2xg+fDjGjx8vJkUjRozAu3fvcPToUWhqauLKlSvQ0tKCqakptm3bBl9fX1y7dg06OjolOnOXlpYGT09PNGnSBKdPn8bTp08xcOBABAQEICoqqqSHgIjoqzZhwgSkpKTA1tYWlSpVQlZWFmbOnIlevXrlu8yNGzcwYcIEHDt2rEg9OXbu3InXr1+LJyWIKoqS5kYlsWHDBkyePBmLFy+Gs7Mz4uLiMGjQIGhqasLPz09sN2HCBMybNw/Ozs5QV1fHvn37ZNaTmpqKtm3bYubMmVBTU8PatWvh4+ODa9euwczMDGfOnMGoUaOwbt06uLq64uXLlzh27FjJDxIR0Rfm0aNH+Ouvv7Bx48Z822RnZ2P06NFwc3ND3bp1yzE6KkssTH2C3bt350lyfvnlF/zyyy+FLnvz5k0IggBbW9tC2348SPmMGTMwdOhQMflKTEyEr68vHBwcAAA1a9YU2+dUkY2MjEo8AOfGjRvx9u1brF27ViyiLV68GD4+PggNDUXVqlXzLJORkYGMjAzxeUpKSom2TURUUW3ZsgUbNmzAxo0bYW9vj/j4eIwePRomJiYyP3ZzZGVloWfPnpg6dSpq1apVpG2sWrUK3t7eMDExKe3wiRTqU3Kj/CxduhQrV64Unw8ZMgTz5s3DlClTMG/ePHTu3BkAYGlpiStXruC3336Tea+OHj1abCOPk5MTnJycxOfTp0/Hjh07sGvXLgQEBCAxMRGamppo3749tLW1YW5uDmdn53zXx1yLiCqaNWvWQE9Pr8AxBkeMGIFLly7h+PHj5RcYlblPLkzl3D3oa7xEoEWLFoiIiJCZVtTuhEW96xIAHDhwACEhIbh69SpSUlLw/v17vH37Funp6dDQ0MCoUaMwbNgw7N+/H61atYKvry8cHR2LtS8FSUhIgJOTk0zPLjc3N2RnZ+PatWtyC1MhISGYOnVqqcVARFTRjBs3DhMmTED37t0BAA4ODrh37x5CQkLkFqbevHmDM2fOIC4uDgEBAQA+nDUUBAHKysrYv38/WrZsKba/d+8eDhw4gO3bt5fPDlGxfM35U2koi9yoV69emDhxovhcT08PaWlpuHXrFgYMGIBBgwaJ896/fy8zJgoAuLi4FLj+1NRUBAcHY8+ePUhKSsL79+/x33//ITExEQDQunVrmJubo2bNmvDy8oKXlxc6deoEDQ0NuetjrkVEFYkgCFi9ejX69OkDVVVVuW0CAgKwe/duHD16FDVq1CjnCKkslXiMqbVr18LBwUEc2NHR0RHr1q0rzdg+e5qamrC2tpZ5FLUwZWNjA4lEUugA53fv3kX79u3h6OiIbdu24ezZs+IdDt69ewcAGDhwIG7fvo0+ffrg4sWLcHFxKdJdncpSYGAgkpOTxcf9+/cVGg8R0ecmPT0dSkqyX8OVKlVCdna23PY6Ojq4ePEi4uPjxcfQoUNRu3ZtxMfHo3HjxjLtIyMjYWRkJA6uTp8H5k+frqxyI11dXZmcrnLlyuK4VStWrJB57126dElmPFAAcodmyG3s2LHYsWMHZs2ahWPHjiE+Ph4ODg5izNra2jh37hx+//13VKtWDZMnT4aTk1OeOyvnYK5FRBXJkSNHcPPmTQwYMCDPPEEQEBAQgB07duDvv/+GpaWlAiKkslSiHlNhYWEICgpCQEAA3NzcAADHjx/H0KFD8fz5c/z444+lGmRFZGBgAE9PTyxZsgSjRo3Kk8y8fv0aenp6OHv2LLKzszFv3jzxB8yWLVvyrM/U1BRDhw7F0KFDERgYiBUrVmDkyJFitTkrK6vEsdrZ2SEqKgppaWlinLGxsVBSUkLt2rXlLqOmplasOxQSEX1tfHx8MHPmTJiZmcHe3h5xcXEICwtD//79xTaBgYF4+PAh1q5dCyUlpTxjKRgZGUFdXT3P9OzsbERGRsLPz6/EdxWj0sf8qXR8am5UHFWrVoWJiQlu375d4PhvRREbGwt/f3906tQJwIceVHfv3pVpo6ysjFatWqFVq1aYMmUK9PT08Pfff8u9RJC5FhF9jlJTU3Hz5k3x+Z07dxAfHw8DAwOYmZnJ5Da5rVq1Co0bN5Y7btSIESOwceNG/O9//4O2tjYeP34M4MMJBd79tGIoUbYaHh6OiIgI9O3bV5z23Xffwd7eHsHBwV9NYpWRkSG+KXIoKyujcuXKRVp+yZIlcHNzQ6NGjTBt2jQ4Ojri/fv3iImJQUREBBISEmBtbY3MzEyEh4fDx8cHsbGxWLZsmcx6Ro8eDW9vb9SqVQuvXr3CoUOHYGdnBwAwNzeHRCLB7t270bZtW0il0mIP/tmrVy9MmTIFfn5+CA4OxrNnzzBy5Ej06dNH7mV8RERUuPDwcAQFBWH48OF4+vQpTExMMGTIEEyePFlsk5SUJF7mUxwHDhxAYmKiTJGLFI/5U/EkJycjPj5eZpqhoeEn50bFNXXqVIwaNQq6urrw8vJCRkYGzpw5g1evXmHMmDFFXo+NjQ22b98OHx8fSCQSBAUFyfSQ3L17N27fvo3mzZtDX18fe/fuRXZ2dr4nAYmIPkdnzpwR7wwPQPyc9PPzQ1RUlNzcJjk5Gdu2bcPChQvlrjNn+BwPDw+Z6ZGRkbzBSwVRosJUUlISXF1d80x3dXVFUlLSJwf1pYiOjka1atVkptWuXbvQy/Ny1KxZE+fOncPMmTPx008/ISkpCVWqVEGDBg3EN5+TkxPCwsIQGhqKwMBANG/eHCEhITJJbVZWFkaMGIEHDx5AR0cHXl5emD9/PgCgevXqmDp1KiZMmIB+/fqhb9++xb6TnoaGBvbt24cffvgBDRs2hIaGBnx9fREWFlas9RAR0f/R1tbGggULsGDBgnzbFPZ5HRwcjODg4DzT27RpU6yxDKl8MH8qnsOHD+cZ/HvAgAFYuXLlJ+VGxTVw4EBoaGjg119/xbhx46CpqQkHBweZAdiLIqdHpKurKypXroyff/5ZZsByPT09bN++HcHBwXj79i1sbGzw+++/w97evkRxExEpgoeHR4E5iLzcRldXF+np6fkuw5ym4pMIJfgv161bFz179sxz97kZM2Zg8+bNuHjxYqkFSBVDSkrKh0FCJwBQV3Q0RESKJUxhglVWcr5vkpOToaOjo+hwZDB/orIk5lpIBvB5vfaJ6OvA+tHXoSxyrRL1mJo6dSq6deuGo0ePimMkxMbG4uDBg3Kv8SciIiL62jF/IiIiIsqrRHfl8/X1xb///ovKlStj586d2LlzJypXroxTp06JAzoSERER0f9h/kRERESUV4ku5SMqLl7KR0T0f3gpX9n5nC/lIypLvJSPiBSNlYWvg0Iv5UtJSRE3mnugRnmYCBIRERExfyIiIiIqTJELU/r6+khKSoKRkRH09PQgkUjytBEEARKJBFlZWaUaJBEREdGXiPkTERERUcGKXJj6+++/YWBgAAA4dOhQmQVEREREVFEwfyIiIiIqWJELU+7u7gCA9+/f48iRI+jfvz9q1KhRZoERERERfemYPxEREREVrNh35VNWVsavv/6K9+/fl0U8RERERBUO8yciIiIi+YpdmAKAli1b4siRI6UdCxEREVGFxfyJiIiIKK8iX8qXm7e3NyZMmICLFy+iQYMG0NTUlJn/3XfflUpwVPEkB/L23URE9HVi/kTlITkZYKpFRERfEokgCEJxF1JSyr+jFe8qQ/KkpKRAV1cXycksTBERUdn5nL9vmD9RWfqcX/tERFRxlMX3TYl6TGVnZ5fKxomIiIi+FsyfiIiIiPIq9hhTmZmZUFZWxqVLl8oiHiIiIqIKh/kTERERkXzFLkypqKjAzMyM3c2JiIiIioj5ExEREZF8Jbor38SJE/HLL7/g5cuXpR0PERERUYXE/ImIiIgorxKNMbV48WLcvHkTJiYmMDc3z3NXmXPnzpVKcEREREQVBfMnIiIiorxKVJjq2LFjKYdBXwvdEF1AXdFREBGVL2FKsW+ASxUQ8ycqD7q6io6AiEjxBKZeX5QSFaamTJlS2nEQERERVWjMn4iIiIjyKtEYU0RERERERERERJ+qRD2msrKyMH/+fGzZsgWJiYl49+6dzHwO6klEREQki/kTERERUV4l6jE1depUhIWFoVu3bkhOTsaYMWPQuXNnKCkpITg4uJRDJCIiIvryMX8iIiIiyqtEhakNGzZgxYoV+Omnn6CsrIwePXpg5cqVmDx5Mk6ePFnaMRIRERF98Zg/EREREeVVosLU48eP4eDgAADQ0tJCcnIyAKB9+/bYs2dP6UVHREREVEEwfyIiIiLKq0SFqRo1aiApKQkAYGVlhf379wMATp8+DTU1tdKLjoiIiKiCYP5ERERElFeJClOdOnXCwYMHAQAjR45EUFAQbGxs0LdvX/Tv379UAyQiIiKqCJg/EREREeVVosLU7Nmz8csvvwAAunXrhmPHjmHYsGH4448/MHv27FINkIiIqCLIyspCUFAQLC0tIZVKYWVlhenTp0MQhHyXOX78ONzc3GBoaAipVApbW1vMnz9fpk1wcDAkEonMw9bWtqx3h0qA+RMREVH5Onr0KHx8fGBiYgKJRIKdO3cWusySJUtgZ2cHqVSK2rVrY+3atTLzt2/fDhcXF+jp6UFTUxP16tXDunXrymgPvg4lKky9ePFC/Pv+/fvYu3cvkpKSoKurW2qBfY4KeyEfPnwYEokEr1+/LreYiIjoyxAaGoqIiAgsXrwYCQkJCA0NxZw5cxAeHp7vMpqamggICMDRo0eRkJCASZMmYdKkSVi+fLlMO3t7eyQlJYmP48ePl/XuUAl8rfnT5ygqKgp6enri8+DgYNSrV6/cts+ckYiofKSlpcHJyQlLliwpUvuIiAgEBgYiODgYly9fxtSpUzFixAj8+eefYhsDAwNMnDgR//zzDy5cuIB+/fqhX79+2LdvX1ntRoVXrMLUxYsXYWFhASMjI9ja2iI+Ph4NGzbE/PnzsXz5crRs2bJIFcjP0ePHjzFy5EjUrFkTampqMDU1hY+Pj9jlvihcXV3LPMH08PCARCLBpk2bZKYvWLAAFhYWn7x+JkpERGXjxIkT6NChA9q1awcLCwt8//33aNOmDU6dOpXvMs7OzujRowfs7e1hYWGB3r17w9PTE8eOHZNpp6ysDGNjY/FRuXLlst4dKoaKkD89e/YMw4YNg5mZGdTU1GBsbAxPT0/ExsaW6nb8/f3RsWPHUllXQScUu3XrhuvXr5fKdoiI6PPl7e2NGTNmoFOnTkVqv27dOgwZMgTdunVDzZo10b17dwwePBihoaFiGw8PD3Tq1Al2dnawsrLCDz/8AEdHR54Y/ATFKkyNHz8eDg4OOHr0KDw8PNC+fXu0a9cOycnJePXqFYYMGfJFdkW/e/cuGjRogL///hu//vorLl68iOjoaLRo0QIjRowo8npUVVVhbGwMiURShtEC6urqmDRpEjIzM0t1vaW9PiIi+j+urq44ePCg+GP4/PnzOH78OLy9vYu8jri4OJw4cQLu7u4y02/cuAETExPUrFkTvXr1QmJiYqnGTp+mIuRPvr6+iIuLw5o1a3D9+nXs2rULHh4eMr3AviRSqRRGRkaftI53796VUjRERPS5yMjIgLq6usw0qVSKU6dOyf29LAgCDh48iGvXrqF58+blFWaFU6zC1OnTpzFz5ky4ublh7ty5ePToEYYPHw4lJSUoKSlh5MiRuHr1alnFWmaGDx8OiUSCU6dOwdfXF7Vq1YK9vT3GjBmDkydPyrR9/vw5OnXqBA0NDdjY2GDXrl3iPHm9jWJjY+Hh4QENDQ3o6+vD09MTr169AvDhRT9q1CgYGRlBXV0dTZs2xenTpwuNt0ePHnj9+jVWrFhRYLuIiAhYWVlBVVUVtWvXznPdq0QiQUREBL777jtoampi0KBBaNGiBQBAX18fEokE/v7+AIDs7GyEhISIY6M4OTnhjz/+KDRWIiL6YMKECejevTtsbW2hoqICZ2dnjB49Gr169Sp02Ro1akBNTQ0uLi4YMWIEBg4cKM5r3LgxoqKiEB0djYiICNy5cwfNmjXDmzdvynJ3qBi+9Pzp9evXOHbsGEJDQ9GiRQuYm5ujUaNGCAwMxHfffSe2CwsLg4ODAzQ1NWFqaorhw4cjNTVVnJ9z+dy+fftgZ2cHLS0teHl5iXcqDA4Oxpo1a/C///1PHC/t8OHDAICff/4ZtWrVgoaGBmrWrImgoKBPOqH28aV8OX777TeYmppCQ0MDXbt2RXJysjgvpzfXzJkzYWJigtq1awP4cHbdxcUF2traMDY2Rs+ePfH06VOZ9e7duxe1atWCVCpFixYtcPfuXZn5L168QI8ePVC9enVoaGjAwcEBv//+e4n3j4iISsbT0xMrV67E2bNnIQgCzpw5g5UrVyIzMxPPnz8X2yUnJ0NLSwuqqqpo164dwsPD0bp1awVG/mUrVmHq5cuXMDY2BgBoaWlBU1MT+vr64nx9ff0vLhF++fIloqOjMWLECGhqauaZ/3HSMnXqVHTt2hUXLlxA27Zt0atXL7x8+VLuuuPj4/Htt9+iTp06+Oeff3D8+HH4+PggKysLwIczqNu2bcOaNWtw7tw5WFtbw9PTM9/15dDR0cHEiRMxbdo0pKWlyW2zY8cO/PDDD/jpp59w6dIlDBkyBP369cOhQ4dk2gUHB6NTp064ePEipk6dim3btgEArl27hqSkJCxcuBAAEBISgrVr12LZsmW4fPkyfvzxR/Tu3RtHjhyRu/2MjAykpKTIPIiIvmZbtmzBhg0bsHHjRpw7dw5r1qzB3LlzsWbNmkKXPXbsGM6cOYNly5ZhwYIFMj9Yvb290aVLFzg6OsLT0xN79+7F69evsWXLlrLcHSqGLz1/0tLSgpaWFnbu3ImMjIx82ykpKWHRokW4fPky1qxZg7///hvjx4+XaZOeno65c+di3bp1OHr0KBITEzF27FgAwNixY9G1a1exWJWUlARXV1cAgLa2NqKionDlyhUsXLgQK1asyHMjgE918+ZNbNmyBX/++Seio6MRFxeH4cOHy7TJOSseExOD3bt3A/jQ43z69Ok4f/48du7cibt374on9oAP44l17twZPj4+iI+Px8CBAzFhwgSZ9b59+xYNGjTAnj17cOnSJQwePBh9+vQp8FJf5lpERKUvKCgI3t7e+Oabb6CiooIOHTrAz88PwIfvuRza2tqIj48XTz6NGTNGPJlCxadc3AU+vkytrC9bK2s3b96EIAhFvoORv78/evToAQCYNWsWFi1ahFOnTsHLyytP2zlz5sDFxQVLly4Vp9nb2wP4MAhbREQEoqKixMs4VqxYgZiYGKxatQrjxo0rMI7hw4dj4cKFCAsLQ1BQUJ75c+fOhb+/v5hQ5fT+mjt3rtgrCgB69uyJfv36ic/v3LkDADAyMhKLchkZGZg1axYOHDiAJk2aAABq1qyJ48eP47fffstzSQnwoZA1derUAveBiOhrMm7cOLHXFAA4ODjg3r17CAkJEROe/FhaWorLPHnyBMHBweJ30cf09PRQq1Yt3Lx5s3R3gD7Jl5w/KSsrIyoqCoMGDcKyZctQv359uLu7o3v37nB0dBTbjR49WvzbwsICM2bMwNChQ2XyoMzMTCxbtgxWVlYAgICAAEybNg3AhwKYVCpFRkaGWMjLMWnSJJl1jx07Fps2bcpT+PoUb9++xdq1a1G9enUAQHh4ONq1a4d58+aJ8WhqamLlypVQVVUVl+vfv7/4d82aNbFo0SI0bNgQqamp0NLSEnuwz5s3DwBQu3ZtXLx4UWa8kurVq4sFOgAYOXIk9u3bhy1btqBRo0Zy42WuRURU+qRSKVavXo3ffvsNT548QbVq1bB8+XJoa2ujSpUqYjslJSVYW1sDAOrVq4eEhASEhITAw8NDQZF/2YpdmPL394eamhqAD1/gQ4cOFXsaFXQW7XNV0G265cmdgGlqakJHRydPd+0c8fHx6NKli9x5t27dQmZmJtzc3MRpKioqaNSoERISEgqNQ01NDdOmTcPIkSMxbNiwPPMTEhIwePBgmWlubm5iD6gcLi4uhW7r5s2bSE9Pz9M18d27d3B2dpa7TGBgIMaMGSM+T0lJgampaaHbIiKqqNLT02XOtAFApUqVkJ2dXaz1ZGdnF/h9m5qailu3bqFPnz4lipPKxpeeP/n6+qJdu3Y4duwYTp48ib/++gtz5szBypUrxd5BBw4cQEhICK5evYqUlBS8f/8eb9++RXp6OjQ0NAAAGhoaYlEKAKpVq5ZvHpXb5s2bsWjRIty6dQupqal4//49dHR0SnUfzczMxKIUADRp0gTZ2dm4du2aWJhycHCQKUoBwNmzZxEcHIzz58/j1atX4ns6MTERderUQUJCAho3biyzTM6JvhxZWVmYNWsWtmzZgocPH+Ldu3fIyMgQj5s8zLWIiMqOiooKatSoAQDYtGkT2rdvnyePy62w/IwKVqzC1MdndHv37p2nTd++fT8tonJmY2MDiURS5LEdVFRUZJ5LJJJ8f1RIpdJPjq8gvXv3xty5czFjxowS35FP3uWLH8sZH2LPnj0yCRsAMcn+mJqaWr7ziIi+Rj4+Ppg5cybMzMxgb2+PuLg4hIWFyfS2CAwMxMOHD7F27VoAwJIlS2BmZib26j169Cjmzp2LUaNGicuMHTsWPj4+MDc3x6NHjzBlyhRUqlQp3x5VVP4qSv6krq6O1q1bo3Xr1ggKCsLAgQMxZcoU+Pv74+7du2jfvj2GDRuGmTNnwsDAAMePH8eAAQPw7t07scAiL48q7CThP//8g169emHq1Knw9PSErq4uNm3aJPZAKk8f501paWnw9PSEp6cnNmzYgCpVqiAxMRGenp7FGhz9119/xcKFC7FgwQJxnK7Ro0cXuA7mWkREhUtNTZXpRX7nzh3Ex8fDwMAAZmZmeXKv69ev49SpU2jcuDFevXqFsLAwXLp0SWbohZCQELi4uMDKygoZGRnYu3cv1q1bh4iIiHLfv4qiWIWpyMjIsopDYQwMDODp6YklS5Zg1KhReRKO169fyx0csygcHR1x8OBBud2scwYlj42Nhbm5OYAP3dtPnz4t0xW+IEpKSggJCUHnzp3z9Jqys7NDbGysTDIcGxuLOnXqFLjOnLOAOeNgAUCdOnWgpqaGxMREuZftERFR4cLDwxEUFIThw4fj6dOnMDExwZAhQzB58mSxTVJSkswd9bKzsxEYGIg7d+5AWVkZVlZWCA0NxZAhQ8Q2Dx48QI8ePfDixQtUqVIFTZs2xcmTJ2W6m5NiVcT8CfiQH+zcuRPAh15D2dnZmDdvnnhGuSTjnKmqqsrkIABw4sQJmJubY+LEieK0e/fulTzwfCQmJuLRo0cwMTEBAJw8eRJKSkriIOfyXL16FS9evMDs2bPF3kpnzpyRaWNnZydzs5ycdecWGxuLDh06iEXL7OxsXL9+vdC8jYiICnbmzBmZoWxyepr6+fkhKioqT+6VlZWFefPm4dq1a1BRUUGLFi1w4sQJmY4gaWlpGD58OB48eACpVApbW1usX78e3bp1K7f9qmiKfSlfRbRkyRK4ubmhUaNGmDZtGhwdHfH+/XvExMQgIiKiSJfWyRMYGAgHBwcMHz4cQ4cOhaqqKg4dOoQuXbqgcuXKGDZsGMaNGydWa+fMmYP09HQMGDCgyNto164dGjdujN9++w1Vq1YVp48bNw5du3aFs7MzWrVqhT///BPbt2/HgQMHClyfubk5JBIJdu/ejbZt20IqlUJbWxtjx47Fjz/+iOzsbDRt2hTJycmIjY2Fjo5OoWOjEBHRh0EyFyxYgAULFuTbJioqSub5yJEjMXLkyALXu2nTplKIjih/L168QJcuXdC/f384OjpCW1sbZ86cwZw5c9ChQwcAgLW1NTIzMxEeHg4fHx/ExsZi2bJlxd6WhYUF9u3bh2vXrsHQ0BC6urqwsbFBYmIiNm3ahIYNG2LPnj3YsWNHkdaXc2Y8NxsbG7lt1dXV4efnh7lz5yIlJQWjRo1C165d84x3lZuZmRlUVVURHh6OoUOH4tKlS5g+fbpMm6FDh2LevHkYN24cBg4ciLNnz+Z5r9vY2OCPP/7AiRMnoK+vj7CwMDx58oSFKSKiT+Th4VFgz9yPP4/t7OwQFxdX4DpnzJiBGTNmlEZ49P8V6658FVXNmjVx7tw5tGjRAj/99BPq1q2L1q1b4+DBg5/UHa9WrVrYv38/zp8/j0aNGqFJkyb43//+B2XlD/XA2bNnw9fXF3369EH9+vVx8+ZN7Nu3T+ZOPUURGhqKt2/fykzr2LEjFi5ciLlz58Le3h6//fYbIiMjCx2MrXr16pg6dSomTJiAqlWrIiAgAAAwffp0BAUFISQkBHZ2dvDy8sKePXvEAXmJiIioYtLS0kLjxo0xf/58NG/eHHXr1kVQUBAGDRqExYsXAwCcnJwQFhaG0NBQ1K1bFxs2bEBISEixtzVo0CDUrl0bLi4uqFKlCmJjY/Hdd9/hxx9/REBAAOrVq4cTJ07IvfGLPGPGjIGzs7PMI78fHNbW1ujcuTPatm2LNm3awNHRUWbgdnmqVKmCqKgobN26FXXq1MHs2bMxd+5cmTZmZmbYtm0bdu7cCScnJyxbtgyzZs2SaTNp0iTUr18fnp6e8PDwgLGxMTp27FikfSQiIvrSSYTijv5NVAIpKSnQ1dUFJgBQV3Q0RETlS5jCr9rykvN9k5ycXOqDYxN9zsRcC8kA+Nonoq8bqxxlpyxyLfaYIiIiIiIiIiIihWBhioiIiIiIiIiIFIKFKSIiIiIiIiIiUggWpoiIiIiIiIiISCFYmCIiIiIiIiIiIoVgYYqIiIiIiIiIiBSChSkiIiIiIiIiIlIIFqaIiIiIiIiIiEghlBUdAH1dkgOToaOjo+gwiIiIiCqk5GSAqRYREX1J2GOKiIiIiIiIiIgUgoUpIiIiIiIiIiJSCBamiIiIiIiIiIhIIViYIiIiIiIiIiIihWBhioiIiIiIiIiIFIKFKSIiIiIiIiIiUggWpoiIiIiIiIiISCGUFR0AfV10Q3QBdUVHQURUNoQpgqJDIKKvnK6uoiMgIvq8CEzPPnvsMUVERERERERERArBwhQRERERERERESkEC1NERERERERERKQQLEwREREREREREZFCsDBFREREREREREQKwcIUEREREREREREpBAtTRERERERERESkECxMERERERERERGRQrAw9RWTSCTYuXOnosMgIqpQsrKyEBQUBEtLS0ilUlhZWWH69OkQBCHfZbZv347WrVujSpUq0NHRQZMmTbBv3z6ZNkePHoWPjw9MTEz4+U1fpeDgYNSrV0987u/vj44dO4rPPTw8MHr06HKPqyQ+3hciIipbJcmjlixZAjs7O0ilUtSuXRtr167Nt+2mTZsgkUhkvpeo6FiY+v8+Tm7K0t27dyGRSMSHgYEB3N3dcezYsXLZPhERlZ3Q0FBERERg8eLFSEhIQGhoKObMmYPw8PB8lzl69Chat26NvXv34uzZs2jRogV8fHwQFxcntklLS4OT0/9r787jcsr7/4G/rkr7Hm1EUmmVCKPGjRuVJctYZugOwz2GCg1ZGluEso69GVlyz1hnrIPJJLJkS7QY2SJhagwzooxKnd8ffp2vS4tKdYrX8/E4j8dc53zO57zPmUvX+3qfz/lcTli7dm1tnAZRrfHy8oKnp2ep206dOgWZTIbk5GQEBgYiJiamRmPp0qULZDIZwsLCSmzr3bs3ZDIZgoOD3/k4tXEuRET0fyqbR4WHhyMoKAjBwcH47bffMHfuXPj5+eHnn38u0TY9PR2BgYHo1KlTdYf9wVCSOoAP2dGjR2Fvb49Hjx5hwYIF6NOnD27cuAEjIyOpQyMioio6c+YM+vXrh969ewMAzM3NsX37dly4cKHMfVasWCH3euHChdi/fz9+/vlnODs7AwB69uyJnj171ljcRFIZPXo0Bg4ciPv376NJkyZy2zZv3gwXFxe0atUKAKCpqVnj8ZiZmSEyMhLTp08X1z148AAxMTEwMTF5p74FQUBhYSE0NTVr5VyIiOiVyuZR33//Pb788kt8+umnAAALCwvEx8dj0aJF8PLyEtsVFhbC29sbc+fOxalTp/DkyZPqDv2DwBFTFXTixAm0b98eKioqMDExwfTp0/Hy5Utx+08//QRHR0eoqanBwMAA3bt3R25ubrl9GhgYwNjYGA4ODvj666/x9OlTnD9/vlqOGR8fjx49eqBhw4bQ0dFB586dcenSpXLjuXfvHoYMGQJdXV3o6+ujX79+SE9PF7fHxsaiffv20NDQgK6uLtzc3HD37t3KXEYioveeq6srYmJicOPGDQBAUlISTp8+XalkqKioCM+ePYO+vn5NhUlUZ/Tp0weNGjVCZGSk3PqcnBz8+OOPGD16NIDKP/72/fffw8XFBVpaWjA2NsawYcPw8OHDCsXz6NEjxMXFieu2bNkCd3d3GBoaVuoYsbGxkMlk+OWXX9C2bVuoqKjg9OnTJc6lKnkbERHVnLy8PKiqqsqtU1NTw4ULF1BQUCCumzdvHgwNDcXPKqoaFqYq4MGDB+jVqxfatWuHpKQkhIeHY+PGjZg/fz4AIDMzE0OHDsWoUaOQmpqK2NhYfPLJJ+XOJ/K6f/75R3xeVVlZuVqO+ezZM4wYMQKnT5/GuXPnYGVlhV69euHZs2elxlBQUAAPDw9oaWnh1KlTiIuLg6amJjw9PZGfn4+XL1+if//+6Ny5M5KTk3H27FmMGTMGMpnsna4tEdH7Zvr06fjss89gY2ODBg0awNnZGQEBAfD29q5wH0uXLkVOTg6GDBlSg5ES1Q1KSkoYPnw4IiMj5XKnH3/8EYWFhRg6dGiV+i0oKEBISAiSkpKwb98+pKenY+TIkW/dT1lZGd7e3ti8ebO4LjIyEqNGjaryMaZPn46wsDCkpqaKo79eV9m8jYiIapaHhwc2bNiAhIQECIKAixcvYsOGDSgoKMCjR48AAKdPn8bGjRsREREhcbT1Hx/lq4B169bBzMwMa9asgUwmg42NDX7//XdMmzYNs2fPRmZmJl6+fIlPPvkEzZo1AwA4Ojq+tV9XV1coKCjg+fPnEAQBbdu2Rbdu3arlmP/+97/ljrV+/Xro6urixIkT6NOnT4lYdu7ciaKiImzYsEEsNm3evBm6urqIjY2Fi4sLsrOz0adPH7Ro0QIAYGtrW+a55eXlIS8vT3z99OnTt14PIqL3wa5du7B161Zs27YN9vb2SExMREBAAExNTTFixIi37r9t2zbMnTsX+/fvLzE6g+h9NWrUKCxZsgQnTpxAly5dALzKQwYOHAgdHZ0q91nMwsICq1atQrt27ZCTk/PWx+hGjRqFTp06YeXKlUhISBBzoDfnl6roMebNm4cePXqUebzK5m0Acy0iopo0a9YsZGVl4aOPPoIgCDAyMsKIESOwePFiKCgo4NmzZ/Dx8UFERAQaNmwodbj1HkdMVUBqaio6duwoNzrIzc0NOTk5uH//PpycnNCtWzc4Ojpi8ODBiIiIwN9///3Wfnfu3InLly9j9+7dsLS0RGRkJBo0aFAtx/zjjz/wxRdfwMrKCjo6OtDW1kZOTg4yMjJKjSUpKQm3bt2ClpaWOO+Bvr4+Xrx4gbS0NOjr62PkyJHw8PCAl5cXVq5ciczMzDLPLTQ0FDo6OuJiZmb21utBRPQ+mDJlijhqytHRET4+Pvjqq68QGhr61n137NiB//73v9i1axe6d+9eC9ES1Q02NjZwdXXFpk2bAAC3bt3CqVOn3unRiISEBHh5eaFp06bQ0tJC586dAaDMXOh1Tk5OsLKywk8//YRNmzbBx8cHSkol7+dW9BguLi7lHq+yeRvAXIuIqCapqalh06ZNeP78OdLT05GRkQFzc3NoaWmhUaNGSEtLQ3p6Ory8vKCkpAQlJSX873//w4EDB6CkpIS0tDSpT6FeYWGqGigqKiI6Ohq//PIL7OzssHr1arRs2RJ37twpdz8zMzNYWVlhwIABWLhwIQYMGCB35+tdjjlixAgkJiZi5cqVOHPmDBITE2FgYID8/PxS+8vJyUHbtm2RmJgot9y4cQPDhg0D8OrO5dmzZ+Hq6oqdO3fC2toa586dK7W/oKAgZGdni8u9e/cqdF5ERPXd8+fPoaAg//GqqKiIoqKicvfbvn07Pv/8c2zfvl2cOJ3oQzJ69Gjs3r0bz549w+bNm9GiRQux0FNZubm58PDwgLa2NrZu3Yr4+Hjs3bsXAMrMhd40atQorF27Fj/99FOpj/FV5hgaGhrlHquyeRvAXIuIqDY0aNAATZo0gaKiInbs2IE+ffpAQUEBNjY2SElJkfvu3LdvX3Tt2hWJiYm8WVBJLExVgK2tLc6ePSs370FcXBy0tLTEX4+RyWRwc3PD3LlzcfnyZSgrK4vJSUUMGjQISkpKWLduXbUcMy4uDhMmTECvXr1gb28PFRUV8VnY0rRp0wY3b96EoaEhLC0t5ZbXh9A7OzsjKCgIZ86cgYODA7Zt21ZqfyoqKtDW1pZbiIg+BF5eXliwYAEOHTqE9PR07N27F8uXL8eAAQPENkFBQRg+fLj4etu2bRg+fDiWLVuGDh06ICsrC1lZWcjOzhbb5OTkiIkPANy5cweJiYkVGv1BVB8MGTIECgoK2LZtG/73v/9h1KhRVZ7L8tq1a3j8+DHCwsLQqVMn2NjYVGji89cNGzYMKSkpcHBwgJ2dXY0co1hl8zaAuRYRUWW8LY96Mze7ceMGfvjhB9y8eRMXLlzAZ599hitXrmDhwoUAAFVVVTg4OMgturq60NLSgoODgzh3NFUMC1Ovyc7OLjFi6N69e/D19cW9e/cwfvx4XLt2Dfv378ecOXMwadIkKCgo4Pz581i4cCEuXryIjIwM7NmzB3/++We5czC9SSaTYcKECQgLC8Pz58/f+ZhWVlb4/vvvkZqaivPnz8Pb2xtqamplHt/b2xsNGzZEv379cOrUKdy5cwexsbGYMGEC7t+/jzt37iAoKAhnz57F3bt38euvv+LmzZuVOkciog/B6tWrMWjQIPj6+sLW1haBgYH48ssvERISIrbJzMyUKyitX78eL1++hJ+fH0xMTMRl4sSJYpuLFy/C2dkZzs7OAIBJkybB2dkZs2fPrr2TI6pBmpqa+PTTTxEUFITMzMwKTVRelqZNm0JZWRmrV6/G7du3ceDAAbl/gxWhp6eHzMxMxMTE1NgxilU2byMiosp5Wx71Zm5WWFiIZcuWwcnJCT169MCLFy9w5swZmJubSxH+e4+Tn78mNjZWfKMWGz16NDZs2IDDhw9jypQpcHJygr6+PkaPHo2ZM2cCALS1tXHy5EmsWLECT58+RbNmzbBs2bJK/TQ48GoY94wZM7BmzRpMnTr1nY65ceNGjBkzBm3atIGZmRkWLlyIwMDAMo+trq6OkydPYtq0afjkk0/w7NkzNG7cGN26dYO2tjb++ecfXLt2DVu2bMHjx49hYmICPz8/fPnll5U6RyKi952WlhZWrFiBFStWlNkmMjJS7nVsbOxb++3SpUuFf+2VqL4aPXo0Nm7ciF69esHU1LTK/TRq1AiRkZH4+uuvsWrVKrRp0wZLly5F3759K9WPrq5ujR8DqHzeRkRElfO2POrN3MzW1haXL1+u1DHe7IMqTiYwy6Va8PTp01ePBE4HoCp1NERENUOYw49UqRV/3mRnZ/PRJvqgiLkWsgHwvU9EVIwVj+pVE7kWH+UjIiIiIiIiIiJJsDBFRERERERERESSYGGKiIiIiIiIiIgkwcIUERERERERERFJgoUpIiIiIiIiIiKSBAtTREREREREREQkCRamiIiIiIiIiIhIEixMERERERERERGRJFiYIiIiIiIiIiIiSShJHQB9WLKDsqGtrS11GERERETvpexsgKkWERHVJxwxRUREREREREREkmBhioiIiIiIiIiIJMHCFBERERERERERSYKFKSIiIiIiIiIikgQLU0REREREREREJAkWpoiIiIiIiIiISBJKUgdAHxadUB1AVeooiIiqhzBHkDoEIiI5OjpSR0BERDVJeA/TT46YIiIiIiIiIiIiSbAwRUREREREREREkmBhioiIiIiIiIiIJMHCFBERERERERERSYKFKSIiIiIiIiIikgQLU0REREREREREJAkWpoiIiIiIiIiISBIsTBERERERERERkSRYmCIiInoHhYWFmDVrFpo3bw41NTW0aNECISEhEAShzH0yMzMxbNgwWFtbQ0FBAQEBAaW2+/HHH2FjYwNVVVU4Ojri8OHDNXQWRERERFRfhIaGol27dtDS0oKhoSH69++P69evl7tPREQEOnXqBD09Pejp6aF79+64cOGCXJuRI0dCJpPJLZ6enjV5KgDqSWFKJpNh3759ZW6PjY2FTCbDkydPai2m9116ejpkMhkSExOlDoWIqE5btGgRwsPDsWbNGqSmpmLRokVYvHgxVq9eXeY+eXl5aNSoEWbOnAknJ6dS25w5cwZDhw7F6NGjcfnyZfTv3x/9+/fHlStXaupUiKiCIiMjoaurK74ODg5G69atK7z/23JbIiKi8pw4cQJ+fn44d+4coqOjUVBQAHd3d+Tm5pa5T2xsLIYOHYrjx4/j7NmzMDMzg7u7Ox48eCDXztPTE5mZmeKyffv2mj4d6QtTWVlZGD9+PCwsLKCiogIzMzN4eXkhJiamwn24uroiMzMTOjo6NRZnly5dxIqhqqoqrK2tERoaWu4dcSIiev+dOXMG/fr1Q+/evWFubo5BgwbB3d29xB2o15mbm2PlypUYPnx4mZ9dK1euhKenJ6ZMmQJbW1uEhISgTZs2WLNmTU2dCtEHISsrCxMnToSlpSVUVVVhZGQENzc3hIeH4/nz51XqMzAwsFK5a2ZmJnr27FmlYxEREUVFRWHkyJGwt7eHk5MTIiMjkZGRgYSEhDL32bp1K3x9fdG6dWvY2Nhgw4YNKCoqKvH5paKiAmNjY3HR09Or6dORtjCVnp6Otm3b4tixY1iyZAlSUlIQFRWFrl27ws/Pr8L9KCsrw9jYGDKZrAajBb744gtkZmbi+vXrCAoKwuzZs/Htt9/W6DHLk5+fL9mxiYjoFVdXV8TExODGjRsAgKSkJJw+ffqdv3SePXsW3bt3l1vn4eGBs2fPvlO/RB+y27dvw9nZGb/++isWLlyIy5cv4+zZs5g6dSoOHjyIo0ePVqlfTU1NGBgYVLi9sbExVFRUqnQsIiKiN2VnZwMA9PX1K7zP8+fPUVBQUGKf2NhYGBoaomXLlhg3bhweP35crbGWRtLClK+vL2QyGS5cuICBAwfC2toa9vb2mDRpEs6dOyfX9tGjRxgwYADU1dVhZWWFAwcOiNtKe5QvLi4OXbp0gbq6OvT09ODh4YG///4bwKtHKCZMmABDQ0Ooqqri448/Rnx8/FvjVVdXh7GxMZo1a4bPP/8crVq1QnR0tLg9Ly8PgYGBaNy4MTQ0NNChQwfExsaK2+/evQsvLy/o6elBQ0MD9vb2cvOFXLlyBT179oSmpiaMjIzg4+ODR48eidu7dOkCf39/BAQEoGHDhvDw8MCwYcPw6aefysVZUFCAhg0b4n//+x+AV9XUjz/+GLq6ujAwMECfPn2QlpYmt8+FCxfg7OwMVVVVuLi44PLlyyXO/8SJE2jfvj1UVFRgYmKC6dOn4+XLl2+9bkRE77Pp06fjs88+g42NDRo0aABnZ2cEBATA29v7nfrNysqCkZGR3DojIyNkZWW9U79EHzJfX18oKSnh4sWLGDJkCGxtbWFhYYF+/frh0KFD8PLyAgAsX74cjo6O0NDQgJmZGXx9fZGTk1Nmv6U9yrdp0ybY29uLeZO/v7+47c1H+aZNmwZra2uoq6vDwsICs2bNQkFBQbWeOxERvZ+KiooQEBAANzc3ODg4VHi/adOmwdTUVO5GqKenJ/73v/8hJiYGixYtwokTJ9CzZ08UFhbWROgiyQpTf/31F6KiouDn5wcNDY0S219/bh8A5s6diyFDhiA5ORm9evWCt7c3/vrrr1L7TkxMRLdu3WBnZ4ezZ8/i9OnT8PLyEi/m1KlTsXv3bmzZsgWXLl2CpaUlPDw8yuzvTYIg4NSpU7h27RqUlZXF9f7+/jh79ix27NiB5ORkDB48GJ6enrh58yYAwM/PD3l5eTh58iRSUlKwaNEiaGpqAgCePHmCf//733B2dsbFixcRFRWFP/74A0OGDJE79pYtW6CsrIy4uDh8++238Pb2xs8//yyXLB05cgTPnz/HgAEDAAC5ubmYNGkSLl68iJiYGCgoKGDAgAEoKioCAOTk5KBPnz6ws7NDQkICgoODERgYKHfcBw8eoFevXmjXrh2SkpIQHh6OjRs3Yv78+aVeo7y8PDx9+lRuISJ6H+3atQtbt27Ftm3bcOnSJWzZsgVLly7Fli1bpA6NiF7z+PFj/Prrr2XmngDE0fcKCgpYtWoVfvvtN2zZsgXHjh3D1KlTK3ys8PBw+Pn5YcyYMUhJScGBAwdgaWlZZnstLS1ERkbi6tWrWLlyJSIiIvDNN9+UewzmWkREBLyqM1y5cgU7duyo8D5hYWHYsWMH9u7dC1VVVXH9Z599hr59+8LR0RH9+/fHwYMHER8fLzfgpiYo1Wjv5bh16xYEQYCNjU2F2o8cORJDhw4FACxcuBCrVq3ChQsXSp0hfvHixXBxccG6devEdfb29gBeFWnCw8MRGRkpPmYRERGB6OhobNy4EVOmTCkzhnXr1mHDhg3Iz89HQUEBVFVVMWHCBABARkYGNm/ejIyMDJiamgJ4Nd9AVFQUNm/ejIULFyIjIwMDBw6Eo6MjAMDCwkLse82aNXB2dsbChQvFdZs2bYKZmRlu3LgBa2trAICVlRUWL14stmnRogU0NDSwd+9e+Pj4AAC2bduGvn37QktLCwAwcOBAufPYtGkTGjVqhKtXr8LBwQHbtm1DUVERNm7cCFVVVdjb2+P+/fsYN26c3LmbmZlhzZo1kMlksLGxwe+//45p06Zh9uzZUFCQr3GGhoZi7ty5ZV5LIqL3xZQpU8RRUwDg6OiIu3fvIjQ0FCNGjKhyv8bGxvjjjz/k1v3xxx8wNjZ+p3iJPlTFuWfLli3l1jds2BAvXrwA8Cq5X7RokdwvZZqbm2P+/PkYO3asXG5Znvnz52Py5MmYOHGiuK5du3Zltp85c6bc8QIDA7Fjx45yi2HMtYiIyN/fHwcPHsTJkyfRpEmTCu2zdOlShIWF4ejRo2jVqlW5bS0sLNCwYUPcunUL3bp1q46QSyXZiKnKThr++gXT0NCAtrY2Hj58WGrb4hFTpUlLS0NBQQHc3NzEdQ0aNED79u2Rmppabgze3t5ITExEXFwcevbsiRkzZsDV1RUAkJKSgsLCQlhbW0NTU1NcTpw4IT42N2HCBMyfPx9ubm6YM2cOkpOTxb6TkpJw/PhxuX2Li3avP3bXtm1buZiUlJQwZMgQbN26FcCrwtv+/fvlHiG5efMmhg4dCgsLC2hra8Pc3BzAq2IaAKSmpqJVq1ZyldKOHTvKHSc1NRUdO3aUm8fLzc0NOTk5uH//folrFRQUhOzsbHG5d+9eudeWiKi+ev78eYnivKKiojgqtao6duxYYjLK6OjoEn+fiejdXLhwAYmJibC3t0deXh4A4OjRo+jWrRsaN24MLS0t+Pj44PHjxxWaHP3hw4f4/fffK5XA79y5E25ubjA2NoampiZmzpwp5mllYa5FRPThEgQB/v7+2Lt3L44dO4bmzZtXaL/FixcjJCQEUVFRcHFxeWv7+/fv4/HjxzAxMXnXkMsl2YgpKysryGQyXLt2rULtGzRoIPdaJpOVmfSrqam9c3yl0dHREYdh79q1C5aWlvjoo4/QvXt35OTkQFFREQkJCVBUVJTbr/hxvf/+97/w8PDAoUOH8OuvvyI0NBTLli3D+PHjkZOTAy8vLyxatKjEcV9/E5Q29Nzb2xudO3fGw4cPER0dDTU1NbmRZF5eXmjWrBkiIiJgamqKoqIiODg41Ojk6SoqKpzUk4g+CF5eXliwYAGaNm0Ke3t7XL58GcuXL8eoUaPENkFBQXjw4IE49x/w6iYK8Opx6j///BOJiYlQVlaGnZ0dAGDixIno3Lkzli1bht69e2PHjh24ePEi1q9fX6vnR/S+sLS0hEwmw/Xr1+XWF49gL84f09PT0adPH4wbNw4LFiyAvr4+Tp8+jdGjRyM/Px/q6urlHqeyeejZs2fh7e2NuXPnwsPDAzo6OtixYweWLVtW7n7MtYiIPlx+fn7Ytm0b9u/fDy0tLXEOUh0dHfFzaPjw4WjcuDFCQ0MBAIsWLcLs2bOxbds2mJubi/sUD4zJycnB3LlzMXDgQBgbGyMtLQ1Tp04Vpz6qSZKNmNLX14eHhwfWrl2L3NzcEttfn8i8slq1alXmT/a2aNFCnKOpWEFBAeLj48UvAxWhqamJiRMnIjAwEIIgwNnZGYWFhXj48CEsLS3lltcfuzAzM8PYsWOxZ88eTJ48GREREQCANm3a4LfffoO5uXmJ/cuaB6GYq6srzMzMsHPnTmzduhWDBw8WC3mPHz/G9evXMXPmTHTr1g22trbiJPDFbG1tkZycLA5jB1Bi8nlbW1ucPXtWbqRbXFwctLS0KjxkkIjofbR69WoMGjQIvr6+sLW1RWBgIL788kuEhISIbTIzM0uMfnB2doazszMSEhKwbds2ODs7o1evXuJ2V1dXbNu2DevXr4eTkxN++ukn7Nu3r1KTWhLR/zEwMECPHj2wZs2aUnPPYgkJCSgqKsKyZcvw0UcfwdraGr///nuFj6OlpQVzc/Myc9E3nTlzBs2aNcOMGTPg4uICKysr3L17t8LHIyKiD094eDiys7PRpUsXmJiYiMvOnTvFNhkZGcjMzJTbJz8/H4MGDZLbZ+nSpQBejfhPTk5G3759YW1tjdGjR6Nt27Y4depUjd8IkWzEFACsXbsWbm5uaN++PebNm4dWrVrh5cuXiI6ORnh4+FsfrStLUFAQHB0d4evri7Fjx0JZWRnHjx/H4MGD0bBhQ4wbNw5TpkyBvr4+mjZtisWLF+P58+cYPXp0pY5T/MVj9+7dGDRoELy9vTF8+HAsW7YMzs7O+PPPPxETE4NWrVqhd+/eCAgIQM+ePWFtbY2///4bx48fh62tLYBXFc+IiAgMHToUU6dOhb6+Pm7duoUdO3Zgw4YNJUZhvWnYsGH49ttvcePGDRw/flxcr6enBwMDA6xfvx4mJibIyMjA9OnTS+w7Y8YMfPHFFwgKCkJ6err45izm6+uLFStWYPz48fD398f169cxZ84cTJo0qcQjLEREHxItLS2sWLECK1asKLNNZGRkiXUVeaR98ODBGDx48DtER0SvW7duHdzc3ODi4oLg4GC0atUKCgoKiI+Px7Vr19C2bVtYWlqioKAAq1evhpeXl/iDM5URHByMsWPHwtDQED179sSzZ88QFxeH8ePHl2hrZWWFjIwM7NixA+3atcOhQ4ewd+/e6jplIiJ6D1Ukj3xzwvL09PRy26upqeHIkSPvEFXVSVpRsLCwwKVLl9C1a1dMnjwZDg4O6NGjB2JiYhAeHl7lfq2trfHrr78iKSkJ7du3R8eOHbF//34oKb2qw4WFhWHgwIHw8fFBmzZtcOvWLRw5cgR6enqVOo6+vj6GDx+O4OBgFBUVYfPmzRg+fDgmT56Mli1bon///oiPj0fTpk0BAIWFhfDz84OtrS08PT1hbW0tTqJpamqKuLg4FBYWwt3dHY6OjggICICurm6FCj/e3t64evUqGjduLDd/loKCAnbs2IGEhAQ4ODjgq6++wpIlS+T21dTUxM8//4yUlBQ4OztjxowZJR4pbNy4MQ4fPowLFy7AyckJY8eOxejRo+Um6yQiIiKqy1q0aIHLly+je/fuCAoKgpOTE1xcXLB69WoEBgYiJCQETk5OWL58ORYtWgQHBwds3bpVfAyiokaMGIEVK1Zg3bp1sLe3R58+fcRfaX5T37598dVXX8Hf3x+tW7fGmTNnMGvWrOo4XSIionpBJlR2FnKiKnj69Cl0dHSA6QBU39qciKheEObwI7SuKf68yc7Ohra2ttThENUaMddCNgC+94mI3ldSV3BqItfiM1hERERERERERCQJFqaIiIiIiIiIiEgSLEwREREREREREZEkWJgiIiIiIiIiIiJJsDBFRERERERERESSYGGKiIiIiIiIiIgkwcIUERERERERERFJgoUpIiIiIiIiIiKShJLUAdCHJTsoG9ra2lKHQURERPReys4GmGoREVF9whFTREREREREREQkCRamiIiIiIiIiIhIEixMERERERERERGRJFiYIiIiIiIiIiIiSbAwRUREREREREREkmBhioiIiIiIiIiIJMHCFBERERERERERSUJJ6gDow6ITqgOoSh0FEREgzBGkDoGIqNrp6EgdARER1TVCHU97OWKKiIiIiIiIiIgkwcIUERERERERERFJgoUpIiIiIiIiIiKSBAtTREREREREREQkCRamiIiIiIiIiIhIEixMERERERERERGRJFiYIiIiIiIiIiIiSbAwRZX24sULLFiwALdu3ZI6FCIiIiIiIiKqx1iYqmNkMhn27dtX4/3ExsZCJpPhyZMnle57woQJuHXrFiwtLaseIBFRHWBubg6ZTFZi8fPzK3OfJ0+ewM/PDyYmJlBRUYG1tTUOHz4sbg8ODi7Rn42NTW2cDlGFCYKAMWPGQF9fHzKZDImJidXS78iRI9G/f/9q6as0wcHBaN26da0dr6pez8PS09Or9RoTERFVRWhoKNq1awctLS0YGhqif//+uH79ern77NmzBy4uLtDV1YWGhgZat26NHTt2yLUJDg6GjY0NNDQ0oKenh+7du+P8+fOVio2FqVo0cuTIUr8AeXp6VqqfrKwsjB8/HhYWFlBRUYGZmRm8vLwQExNT4T5cXV2RmZkJHR2dSh1769atSE9Px/r16yu1HxFRXRQfH4/MzExxiY6OBgAMHjy41Pb5+fno0aMH0tPT8dNPP+H69euIiIhA48aN5drZ29vL9Xv69OkaPxf6MLyeSzRo0ADNmzfH1KlT8eLFi0r1ExUVhcjISBw8eBCZmZlwcHCooYjlRUZGQldXt9RtFbk5FxgYWKl8p6rMzc2xYsWKEuvfLIyVJTMzEz179qz+wIiIiKroxIkT8PPzw7lz5xAdHY2CggK4u7sjNze3zH309fUxY8YMnD17FsnJyfj888/h6+sr18ba2hpr1qxBSkoKTp8+DXNzc7i7u+PPP/+scGxKVT4rqhJPT09s3rxZbp2KikqF909PT4ebmxt0dXWxZMkSODo6oqCgAEeOHIGfnx+uXbtWoX6UlZVhbGxcqdgBwNvbG97e3pXej4ioLmrUqJHc67CwMLRo0QKdO3cutf2mTZvw119/4cyZM2jQoAGAV19g36SkpFSlv7FEFVGcSxQUFCAhIQEjRoyATCbDokWLKtxHWloaTExM4OrqWoORVh9BEFBYWAhNTU1oampKHU6Z8vPzq5xjERER1aSoqCi515GRkTA0NERCQgL+9a9/lbpPly5d5F5PnDgRmzZtQnJysrhu2LBhcm2WL1+OjRs3Ijk5Gd26datQbBwxVctUVFRgbGwst+jp6VV4f19fX8hkMly4cAEDBw6EtbU17O3tMWnSJJw7d06u7aNHjzBgwACoq6vDysoKBw4cELeV9ihfXFwcunTpAnV1dejp6cHDwwN///03ACAvLw8TJkyAoaEhVFVV8fHHHyM+Pv7dLgYRUR2Sn5+PH374AaNGjYJMJiu1zYEDB9CxY0f4+fnByMgIDg4OWLhwIQoLC+Xa3bx5E6amprCwsIC3tzcyMjJq4xToA1GcS5iZmaF///7o3r27ONoPAB4/foyhQ4eicePGUFdXh6OjI7Zv3y5uHzlyJMaPH4+MjAzIZDKxuBoVFYWPP/4Yurq6MDAwQJ8+fZCWliZ37Hv37mHIkCHQ1dWFvr4++vXrh/T09Go/x+I85ZdffkHbtm2hoqKC06dPlzliae7cuWjUqBG0tbUxduxY5Ofni9uKiooQGhqK5s2bQ01NDU5OTvjpp5+qJc4uXbrA398fAQEBaNiwITw8PACUPvrr2rVrcHV1haqqKhwcHHDixAm57VeuXEHPnj2hqakJIyMj+Pj44NGjR9USJxER0Zuys7MBvBoVVRGCICAmJqbcuabz8/Oxfv166OjowMnJqcKxsDBVj/z111+IioqCn58fNDQ0Smx/c2j83LlzMWTIECQnJ6NXr17w9vbGX3/9VWrfiYmJ6NatG+zs7HD27FmcPn0aXl5e4petqVOnYvfu3diyZQsuXboES0tLeHh4lNkfEVF9s2/fPjx58gQjR44ss83t27fx008/obCwEIcPH8asWbOwbNkyzJ8/X2zToUMHREZGIioqCuHh4bhz5w46deqEZ8+e1cJZ0IfmypUrOHPmDJSVlcV1L168QNu2bXHo0CFcuXIFY8aMgY+PDy5cuAAAWLlyJebNm4cmTZogMzNTvNGUm5uLSZMm4eLFi4iJiYGCggIGDBiAoqIiAEBBQQE8PDygpaWFU6dOIS4uDpqamvD09JQrBFWn6dOnIywsDKmpqWjVqlWpbWJiYpCamorY2Fhs374de/bswdy5c8XtoaGh+N///odvv/0Wv/32G7766iv85z//KVEYqqotW7ZAWVkZcXFx+Pbbb8tsN2XKFEyePBmXL19Gx44d4eXlhcePHwN4NXfdv//9bzg7O+PixYuIiorCH3/8gSFDhlRLjERERK8rKipCQEAA3Nzc3vo4f3Z2NjQ1NaGsrIzevXtj8eLFJdocPHgQmpqaUFVVxTfffIPo6Gg0bNiwwvHwUb5aVvw/7HVff/01vv7667fue+vWLQiCUOFJdEeOHImhQ4cCABYuXIhVq1bhwoULpc5ptXjxYri4uGDdunXiOnt7ewCvEtXw8HBERkaK8yVEREQgOjoaGzduxJQpU0r0l5eXh7y8PPH106dPKxQzEZFUNm7ciJ49e8LU1LTMNkVFRTA0NMT69euhqKiItm3b4sGDB1iyZAnmzJkDAHLzyrRq1QodOnRAs2bNsGvXLowePbrGz4Pef8W5xMuXL5GXlwcFBQWsWbNG3N64cWMEBgaKr8ePH48jR45g165daN++PXR0dKClpQVFRUW5R84GDhwod5xNmzahUaNGuHr1KhwcHLBz504UFRVhw4YN4qjCzZs3Q1dXF7GxsXB3d6/2c503bx569OhRbhtlZWVs2rQJ6urqsLe3x7x58zBlyhSEhISgoKAACxcuxNGjR9GxY0cAgIWFBU6fPo3vvvuuzMd2K8PKyqrUJP1N/v7+4jUODw9HVFQUNm7ciKlTp2LNmjVwdnbGwoULxfabNm2CmZkZbty4AWtr6xL9MdciIqKq8vPzw5UrVyo0D6qWlhYSExORk5ODmJgYzJgxo0Sbrl27IjExEY8ePUJERASGDBmC8+fPw9DQsELxsDBVy7p27Yrw8HC5dZUZOlcZr99Z1NDQgLa2Nh4+fFhq28TExDIn+01LS0NBQQHc3NzEdQ0aNED79u2Rmppa6j6hoaFydyuJiOqyu3fv4ujRo9izZ0+57UxMTNCgQQMoKiqK62xtbZGVlSXOLfMmXV1dWFtblzvsmagyinOJ3NxcfPPNN1BSUpIrKhUWFmLhwoXYtWsXHjx4gPz8fOTl5UFdXb3cfm/evInZs2fj/PnzePTokThSKiMjAw4ODkhKSsKtW7egpaUlt9+LFy9KPPJXXVxcXN7axsnJSe7cOnbsiJycHNy7dw85OTl4/vx5ieJWfn4+nJ2dqyXGtm3bVqhdcWEMeDUPnYuLi5hHJSUl4fjx46XOn5WWllZqYYq5FhERVYW/vz8OHjyIkydPokmTJm9tr6CgAEtLSwBA69atkZSUhO+//16ujYaGBiwtLWFpaYmPPvoIVlZW2LhxI4KCgioUEwtTtaz4f1hVWFlZQSaTVXiC8+KJeYvJZDIxyXyTmppalWIqS1BQECZNmiS+fvr0KczMzKr1GERE1WXz5s0wNDRE7969y23n5uaGbdu2oaioCAoKr56Gv3HjBkxMTEotSgFATk4O0tLS4OPjU+1x04fp9Vxi06ZNcHJywsaNG8UReUuWLMHKlSuxYsUKODo6QkNDAwEBAW993M7LywvNmjVDREQETE1NUVRUBAcHB3G/nJwctG3bFlu3bi2x75s/JFAWbW1t5Obmyv0bAiDOefnmrwWXNnVBZeTk5AAADh06VOLXM8v78RltbW1x7o3XPXnypNpjLI7Ty8ur1AnsTUxMSt2HuRYREVWGIAgYP3489u7di9jYWDRv3rzK/bxNUVGR3Kjet+EcU/WIvr4+PDw8sHbt2lJ/0vH1icwrq1WrVmX+/HKLFi3EuROKFRQUID4+HnZ2dqXuo6KiAm1tbbmFiKguKioqwubNmzFixAgoKcnfrxk+fLjcnZ5x48bhr7/+wsSJE3Hjxg0cOnQICxcuhJ+fn9gmMDAQJ06cQHp6Os6cOYMBAwZAUVFRfLSaqDopKCjg66+/xsyZM/HPP/8AePVjJv369cN//vMfODk5wcLCAjdu3Ci3n8ePH+P69euYOXMmunXrBltbW/EHUIq1adMGN2/ehKGhoXhXtHh5s1hTlpYtW+Lly5dITEyUW3/p0iUAKHVk0NskJSWJ5w4A586dg6amJszMzGBnZwcVFRVkZGSUiLm8Ik7Lli2RkJBQYv2lS5eqFGNxXMVevnyJhIQE2NraAnh1bX/77TeYm5uXiLOswhdzLSIiqgw/Pz/88MMP2LZtG7S0tJCVlYWsrCy5z9A3c9/Q0FBER0fj9u3bSE1NxbJly7Bjxw5xe25uLr7++mucO3cOd+/eRUJCAkaNGoUHDx6U+URWaViYqmV5eXniG6B4qcwvrqxduxaFhYVo3749du/ejZs3byI1NRWrVq2SGyJeWUFBQYiPj4evry+Sk5Nx7do1hIeH49GjR9DQ0MC4ceMwZcoUREVF4erVq/jiiy/w/PlzzpdCRPXe0aNHkZGRgVGjRpXYlpGRgczMTPG1mZkZjhw5gvj4eLRq1QoTJkzAxIkTMX36dLHN/fv3MXToULRs2RJDhgyBgYEBzp07V+ERJUSVNXjwYCgqKmLt2rUAXo2wjo6OxpkzZ5Camoovv/wSf/zxR7l96OnpwcDAAOvXr8etW7dw7NgxudE4AODt7Y2GDRuiX79+OHXqFO7cuYPY2FhMmDAB9+/fr1Cs9vb2cHd3x6hRoxATE4M7d+4gKioKvr6++PTTT0uMaqqI/Px8jB49GlevXsXhw4cxZ84c+Pv7Q0FBAVpaWggMDMRXX32FLVu2IC0tDZcuXcLq1auxZcuWMvv86quvcOjQISxYsACpqam4cuUKZsyYgbNnz2LixImVjhF4lcPt3bsX165dg5+fH/7++2/x746fnx/++usvDB06FPHx8UhLS8ORI0fw+eefl/jVTyIioqoIDw9HdnY2unTpAhMTE3HZuXOn2ObN3Dc3Nxe+vr6wt7eHm5sbdu/ejfXr14vbFRUVce3aNQwcOBDW1tbiD3ucOnVKnLO6IvgoXy2LiooqMSS7ZcuWFX48z8LCApcuXcKCBQswefJkZGZmolGjRmjbtm2Juasqw9raGr/++iu+/vprtG/fHmpqaujQoYN4hz8sLAxFRUXw8fHBs2fP4OLigiNHjkBPT6/KxyQiqgvc3d3LHJIcGxtbYl3Hjh3lRj686fW7SES1QUlJCf7+/li8eDHGjRuHmTNn4vbt2/Dw8IC6ujrGjBmD/v37l/poWjEFBQXs2LEDEyZMgIODA1q2bIlVq1ahS5cuYht1dXWcPHkS06ZNwyeffIJnz56hcePG6NatW6VG6+zcuRNz5szBl19+id9//x1NmjTBgAEDMGvWrCqdf7du3WBlZYV//etfyMvLw9ChQxEcHCxuDwkJQaNGjRAaGorbt29DV1cXbdq0KfeHZ1xdXfHLL79g3rx5WLZsGRQUFODo6IiYmJi3/npRWcLCwhAWFobExERYWlriwIED4i8WmZqaIi4uDtOmTYO7uzvy8vLQrFkzeHp6yj3ySEREVFUVeQTvzdx3/vz5cr8+Dbx6dLz4xoqqqupb52itCJlQ2Rm1iarg6dOnr4b5TwegKnU0RESAMIcff++j4s+b7OxsPtpEHxQx10I2AL73iYjo/1Rn1acmci3egiEiIiIiIiIiIkmwMEVERERERERERJJgYYqIiIiIiIiIiCTBwhQREREREREREUmChSkiIiIiIiIiIpIEC1NERERERERERCQJFqaIiIiIiIiIiEgSLEwREREREREREZEkWJgiIiIiIiIiIiJJKEkdAH1YsoOyoa2tLXUYRERERO+l7GyAqRYREdUnHDFFRERERERERESSYGGKiIiIiIiIiIgkwcIUERERERERERFJgoUpIiIiIiIiIiKSBAtTREREREREREQkCRamiIiIiIiIiIhIEkpSB0AfFp1QHUBV6iiI6H0nzBGkDoGISBI6OlJHQEREdY1Qx1NjjpgiIiIiIiIiIiJJsDBFRERERERERESSYGGKiIiIiIiIiIgkwcIUERERERERERFJgoUpIiIiIiIiIiKSBAtTREREREREREQkCRamiIiIiIiIiIhIEixMERERERERERGRJFiYIiKi95K5uTlkMlmJxc/P76377tixAzKZDP3795dbv2fPHri7u8PAwAAymQyJiYk1EzwRERERUTUKDQ1Fu3btoKWlBUNDQ/Tv3x/Xr18vd589e/bAxcUFurq60NDQQOvWrbFjxw65NsHBwbCxsYGGhgb09PTQvXt3nD9/vlKxfVCFKZlMhn379r1TH5GRkdDV1X3nWMzNzbFixYp37qc8sbGxkMlkePLkCYDqi52IqD6Ij49HZmamuERHRwMABg8eXO5+6enpCAwMRKdOnUpsy83Nxccff4xFixbVSMxEVDeMHDmyRGG6st7Mw4iIiKR04sQJ+Pn54dy5c4iOjkZBQQHc3d2Rm5tb5j76+vqYMWMGzp49i+TkZHz++efw9fWVa2NtbY01a9YgJSUFp0+fhrm5Odzd3fHnn39WODalKp9VHZOVlYUFCxbg0KFDePDgAQwNDdG6dWsEBASgW7duAIDMzEzo6elJHGnFPH/+HCEhIdi1axcePHgALS0t2NnZYdKkSejXr1+V+vz000/Rq1cv8XVwcDD27dvHO/5E9F5q1KiR3OuwsDC0aNECnTt3LnOfwsJCeHt7Y+7cuTh16lSJL5Q+Pj4AXhWviKh+kslk5W6fM2cOVq5cCUEQ3uk4rq6uyMzMhI6Ozjv1Q0REVB2ioqLkXkdGRsLQ0BAJCQn417/+Veo+Xbp0kXs9ceJEbNq0CcnJyeK6YcOGybVZvnw5Nm7ciOTkZLEW8zbvRWEqPT0dbm5u0NXVxZIlS+Do6IiCggIcOXIEfn5+uHbtGgDA2NhY4kgrbuzYsTh//jxWr14NOzs7PH78GGfOnMHjx4+r3KeamhrU1NQqvV9BQQEaNGhQ5eMSEUktPz8fP/zwAyZNmlTul9J58+bB0NAQo0ePxqlTp2oxQiKqLZmZmeJ/79y5E7Nnz5Z7lEFTUxOamprvfBxlZeV6lXsSEdGHJTs7G8CrUVEVIQgCjh07hlu3bpXZJj8/H+vXr4eOjg6cnJwqHMt78Sifr68vZDIZLly4gIEDB8La2hr29vaYNGkSzp07J7Z7/VG+0oZXJyYmQiaTyd0Jj4yMRNOmTaGuro4BAwaUKAylpaWhX79+MDIygqamJtq1a4ejR4/KtXn48CG8vLygpqaG5s2bY+vWrW89pwMHDuDrr79Gr169YG5ujrZt22L8+PEYNWqU2Ob777+Hi4sLtLS0YGxsjGHDhuHhw4dl9vn6o3yRkZGYO3cukpKSxHlXIiMjxesUHh6Ovn37QkNDAwsWLAAA7N+/H23atIGqqiosLCwwd+5cvHz58q3nQkQktX379uHJkycYOXJkmW1Onz6NjRs3IiIiovYCI6JaZ2xsLC46OjqQyWRy6zQ1NUs8ytelSxeMHz8eAQEB0NPTg5GRESIiIpCbm4vPP/8cWlpasLS0xC+//CLu82au2aVLl1LnvSvOO5cvXw5HR0doaGjAzMwMvr6+yMnJqcUrQ0REH4qioiIEBATAzc0NDg4O5bbNzs6GpqYmlJWV0bt3byxevLhEm4MHD0JTUxOqqqr45ptvEB0djYYNG1Y4nnpfmPrrr78QFRUFPz8/aGholNj+LnMqnT9/HqNHj4a/vz8SExPRtWtXzJ8/X65NTk4OevXqhZiYGFy+fBmenp7w8vJCRkaG2GbkyJG4d+8ejh8/jp9++gnr1q0rt4AEvEqaDh8+jGfPnpXZpqCgACEhIUhKSsK+ffuQnp5e7peu13366aeYPHky7O3txflXPv30U3F7cHAwBgwYgJSUFIwaNQqnTp3C8OHDMXHiRFy9ehXfffcdIiMjxaLVm/Ly8vD06VO5hYhIKhs3bkTPnj1hampa6vZnz57Bx8cHERERlfoQJaIPx5YtW9CwYUNcuHAB48ePx7hx4zB48GC4urri0qVLcHd3h4+PD54/f17q/nv27JGb9+6TTz5By5YtYWRkBABQUFDAqlWr8Ntvv2HLli04duwYpk6dWmY8zLWIiKiq/Pz8cOXKlRITmZdGS0sLiYmJiI+Px4IFCzBjxowSbbp27YrExEScOXMGnp6eGDJkyFtrHq+r94/y3bp1C4IgwMbGptr7XrlyJTw9PcWkwNraGmfOnJF7NtPJyUluiFpISAj27t2LAwcOwN/fHzdu3MAvv/yCCxcuoF27dgBefUGytbUt99jr16+Ht7c3DAwM4OTkhI8//hiDBg2Cm5ub2Ob10VMWFhZYtWoV2rVrh5ycnLcOQVdTU4OmpiaUlJRKHWY+bNgwfP7553LHmj59OkaMGCEeLyQkBFOnTsWcOXNK7B8aGoq5c+eWGwMRUW24e/cujh49ij179pTZJi0tDenp6fDy8hLXFRUVAQCUlJRw/fp1tGjRosZjJaK6y8nJCTNnzgQABAUFISwsDA0bNsQXX3wBAJg9ezbCw8ORnJyMjz76qMT+rz8q8c033+DYsWM4f/68OM1CQECAuN3c3Bzz58/H2LFjsW7dulLjYa5FRERV4e/vj4MHD+LkyZNo0qTJW9srKCjA0tISANC6dWskJSXh+++/l2ujoaEBS0tLWFpa4qOPPoKVlRU2btyIoKCgCsVU70dMvevElOVJTU1Fhw4d5NZ17NhR7nVOTg4CAwNha2sLXV1daGpqIjU1VRwxlZqaCiUlJbRt21bcx8bG5q0juf71r3/h9u3biImJwaBBg/Dbb7+hU6dOCAkJEdskJCTAy8sLTZs2hZaWljih7+ujtarKxcVF7nVSUhLmzZsnzrugqamJL774ApmZmaXeGQwKCkJ2dra43Lt3751jIiKqis2bN8PQ0BC9e/cus42NjQ1SUlKQmJgoLn379hXv/piZmdVixERUF7Vq1Ur8b0VFRRgYGMDR0VFcVzzy6W13iH/55RdMnz4dO3fuhLW1tbj+6NGj6NatGxo3bgwtLS34+Pjg8ePHZY7AYq5FRESVIQgC/P39sXfvXhw7dgzNmzevcj9vU1RUhLy8vAr3We9HTFlZWUEmk4kTnFeUgsKrmtzrF7WgoKDSxw8MDER0dDSWLl0KS0tLqKmpYdCgQcjPz690X29q0KABOnXqhE6dOmHatGmYP38+5s2bh2nTpqGgoAAeHh7w8PDA1q1b0ahRI2RkZMDDw6Najv3mY5E5OTmYO3cuPvnkkxJtVVVVS6xTUVGBiorKO8dBRPQuioqKsHnzZowYMQJKSvIfecOHD0fjxo0RGhoKVVXVEs/XF99AeH39X3/9hYyMDPz+++8AIE6YXDw3DRG9v978IRiZTCa3rviHFYpHW5bm6tWr+OyzzxAWFgZ3d3dxfXp6Ovr06YNx48ZhwYIF0NfXx+nTpzF69Gjk5+dDXV29RF/MtYiIqDL8/Pywbds27N+/H1paWsjKygIA6OjoiKN3X8+PgVejc11cXNCiRQvk5eXh8OHDco//5ebmYsGCBejbty9MTEzw6NEjrF27Fg8ePMDgwYMrHFu9L0zp6+vDw8MDa9euxYQJE0oUVJ48eVLq6KTinxHPzMyEnp4egFeTn7/O1tYW58+fl1v3+mTqABAXF4eRI0diwIABAF4VcF6fPN3GxgYvX75EQkKC+Cjf9evXS/wEeUXY2dnh5cuXePHiBW7evInHjx8jLCxMvJN/8eLFSvWnrKyMwsLCCrVt06YNrl+/Lg7hIyKqD44ePYqMjAy5R5+LZWRkiDcpKurAgQNyjzl/9tlnAF79vHxwcPA7xUpE77dHjx7By8sLAwcOxFdffSW3LSEhAUVFRVi2bJn4d2nXrl1ShElERO+p8PBwAK9+jON1mzdvFueqfjM/zs3Nha+vL+7fvw81NTXY2Nhg/fr1Ym6tqKiIa9euYcuWLXj06BEMDAzQrl07nDp1Cvb29hWOrd4XpgBg7dq1cHNzQ/v27TFv3jy0atUKL1++RHR0NMLDw5GamlpiH0tLS5iZmSE4OBgLFizAjRs3sGzZMrk2EyZMgJubG5YuXYp+/frhyJEjcvNLAa9GbO3ZswdeXl6QyWSYNWuW3J2yli1bwtPTE19++SXCw8OhpKSEgIAAsSJZli5dumDo0KFwcXGBgYEBrl69iq+//hpdu3aFtrY2mjZtCmVlZaxevRpjx47FlStX5B7zqwhzc3PcuXMHiYmJaNKkCbS0tMq88zZ79mz06dMHTZs2xaBBg6CgoICkpCRcuXKlxITwRER1hbu7e5nDjWNjY8vdt/iXSl83cuTICv/IBBHR6wYOHAh1dXUEBweLd6mBVzdLLS0tUVBQgNWrV8PLywtxcXH49ttvJYyWiIjeNxV5BO/N/Hj+/Pklvu8/ffpULEypqqqWO49rRdX7OaaAVxNxX7p0CV27dsXkyZPh4OCAHj16ICYmRqwKvqlBgwbYvn07rl27hlatWmHRokUlLvhHH32EiIgIrFy5Ek5OTvj111/FSS+LLV++HHp6enB1dYWXlxc8PDzQpk0buTabN2+GqakpOnfujE8++QRjxoyBoaFhuefk4eGBLVu2wN3dHba2thg/fjw8PDzEu2eNGjVCZGQkfvzxR9jZ2SEsLAxLly6t1HUbOHAgPD090bVrVzRq1Ajbt28vN56DBw/i119/Rbt27fDRRx/hm2++QbNmzSp1TCIiIqIP0cmTJ3HlyhU0a9YMJiYm4nLv3j04OTlh+fLlWLRoERwcHLB161bxMQoiIqL3nUyoydnDif6/p0+fQkdHB5gOoOSUVERE1UqYw4+2D1Xx5012dja0tbWlDoeo1oi5FrIB8L1PRET/pzqrPjWRa70XI6aIiIiIiIiIiKj+YWGKiIiIiIiIiIgkwcIUERERERERERFJgoUpIiIiIiIiIiKSBAtTREREREREREQkCRamiIiIiIiIiIhIEixMERERERERERGRJFiYIiIiIiIiIiIiSShJHQB9WLKDsqGtrS11GERERETvpexsgKkWERHVJxwxRUREREREREREkmBhioiIiIiIiIiIJMHCFBERERERERERSYKFKSIiIiIiIiIikgQLU0REREREREREJAkWpoiIiIiIiIiISBIsTBERERERERERkSRYmCIiIiIiIiIiIkmwMEVERERERERERJJgYYqIiIiIiIiIiCTBwhQREREREREREUmChSkiIiIiIiIiIpIEC1NERERERERERCQJFqaIiIiIiIiIiEgSLEwREREREREREZEkWJgiIiIiIiIiIiJJsDBFRERERERERESSUJI6APowCIIAAHj69KnEkRAR0fus+HOm+HOH6EPBXIuIiGpDTeRaLExRrXj8+DEAwMzMTOJIiIjoQ/Ds2TPo6OhIHQZRrWGuRUREtak6cy0WpqhW6OvrAwAyMjL4RaGCnj59CjMzM9y7dw/a2tpSh1Pn8XpVHq9Z5fB6VZ4U10wQBDx79gympqa1cjyiuoK5VvXi3/zqxetZvXg9qxevZ+XURK7FwhTVCgWFV9OZ6ejo8B97JWlra/OaVQKvV+XxmlUOr1fl1fY145dy+hAx16oZ/JtfvXg9qxevZ/Xi9ay46s61OPk5ERERERERERFJgoUpIiIiIiIiIiKSBAtTVCtUVFQwZ84cqKioSB1KvcFrVjm8XpXHa1Y5vF6Vx2tGVHv476168XpWL17P6sXrWb14PaUnE/h7ykREREREREREJAGOmCIiIiIiIiIiIkmwMEVERERERERERJJgYYqIiIiIiIiIiCTBwhTVirVr18Lc3Byqqqro0KEDLly4IHVIdVJoaCjatWsHLS0tGBoaon///rh+/brUYdUrYWFhkMlkCAgIkDqUOuvBgwf4z3/+AwMDA6ipqcHR0REXL16UOqw6q7CwELNmzULz5s2hpqaGFi1aICQkBJyi8ZWTJ0/Cy8sLpqamkMlk2Ldvn9x2QRAwe/ZsmJiYQE1NDd27d8fNmzelCZaonqtsPvXjjz/CxsYGqqqqcHR0xOHDh2sp0vqhMtczMjISMplMblFVVa3FaOuut30OlCY2NhZt2rSBiooKLC0tERkZWeNx1ieVvaaxsbEl3p8ymQxZWVm1E3AdVtXvV/z7WbtYmKIat3PnTkyaNAlz5szBpUuX4OTkBA8PDzx8+FDq0OqcEydOwM/PD+fOnUN0dDQKCgrg7u6O3NxcqUOrF+Lj4/Hdd9+hVatWUodSZ/39999wc3NDgwYN8Msvv+Dq1atYtmwZ9PT0pA6tzlq0aBHCw8OxZs0apKamYtGiRVi8eDFWr14tdWh1Qm5uLpycnLB27dpSty9evBirVq3Ct99+i/Pnz0NDQwMeHh548eJFLUdKVL9VNp86c+YMhg4ditGjR+Py5cvo378/+vfvjytXrtRy5HVTVfJTbW1tZGZmisvdu3drMeK6622fA2+6c+cOevfuja5duyIxMREBAQH473//iyNHjtRwpPVHZa9psevXr8u9Rw0NDWsowvqjKt+v+PdTAgJRDWvfvr3g5+cnvi4sLBRMTU2F0NBQCaOqHx4+fCgAEE6cOCF1KHXes2fPBCsrKyE6Olro3LmzMHHiRKlDqpOmTZsmfPzxx1KHUa/07t1bGDVqlNy6Tz75RPD29pYooroLgLB3717xdVFRkWBsbCwsWbJEXPfkyRNBRUVF2L59uwQREtVflc2nhgwZIvTu3VtuXYcOHYQvv/yyRuOsLyp7PTdv3izo6OjUUnT115ufA6WZOnWqYG9vL7fu008/FTw8PGowsvqrItf0+PHjAgDh77//rpWY6rOKfL/i38/axxFTVKPy8/ORkJCA7t27i+sUFBTQvXt3nD17VsLI6ofs7GwAgL6+vsSR1H1+fn7o3bu33HuNSjpw4ABcXFwwePBgGBoawtnZGREREVKHVae5uroiJiYGN27cAAAkJSXh9OnT6Nmzp8SR1X137txBVlaW3L9LHR0ddOjQgZ8BRJVQlXzq7NmzJT4TPTw8+G8PVc9Pc3Jy0KxZM5iZmaFfv3747bffaiPc9w7fmzWndevWMDExQY8ePRAXFyd1OHVSRb5f8T1a+1iYohr16NEjFBYWwsjISG69kZERn3l+i6KiIgQEBMDNzQ0ODg5Sh1On7dixA5cuXUJoaKjUodR5t2/fRnh4OKysrHDkyBGMGzcOEyZMwJYtW6QOrc6aPn06PvvsM9jY2KBBgwZwdnZGQEAAvL29pQ6tziv+O8/PAKJ3U5V8Kisri//2ylCV69myZUts2rQJ+/fvxw8//ICioiK4urri/v37tRHye6Ws9+bTp0/xzz//SBRV/WZiYoJvv/0Wu3fvxu7du2FmZoYuXbrg0qVLUodWp1T0+xX/ftY+JakDIKLS+fn54cqVKzh9+rTUodRp9+7dw8SJExEdHc1JSCugqKgILi4uWLhwIQDA2dkZV65cwbfffosRI0ZIHF3dtGvXLmzduhXbtm2Dvb29OB+GqakprxkR0QeiY8eO6Nixo/ja1dUVtra2+O677xASEiJhZESvCqctW7YUX7u6uiItLQ3ffPMNvv/+ewkjq1v4/aru4ogpqlENGzaEoqIi/vjjD7n1f/zxB4yNjSWKqu7z9/fHwYMHcfz4cTRp0kTqcOq0hIQEPHz4EG3atIGSkhKUlJRw4sQJrFq1CkpKSigsLJQ6xDrFxMQEdnZ2cutsbW2RkZEhUUR135QpU8RRU46OjvDx8cFXX33FEXoVUPx3np8BRO+mKvmUsbEx/+2VoTry0+IRtLdu3aqJEN9rZb03tbW1oaamJlFU75/27dvz/fmayny/4t/P2sfCFNUoZWVltG3bFjExMeK6oqIixMTEyN11olcEQYC/vz/27t2LY8eOoXnz5lKHVOd169YNKSkpSExMFBcXFxd4e3sjMTERioqKUodYp7i5uZX4idwbN26gWbNmEkVU9z1//hwKCvIfl4qKiigqKpIoovqjefPmMDY2lvsMePr0Kc6fP8/PAKJKqEo+1bFjR7n2ABAdHc1/e6ie/LSwsBApKSkwMTGpqTDfW3xv1o7ExES+P1G171d8j0pA6tnX6f23Y8cOQUVFRYiMjBSuXr0qjBkzRtDV1RWysrKkDq3OGTdunKCjoyPExsYKmZmZ4vL8+XOpQ6tX+Kt8Zbtw4YKgpKQkLFiwQLh586awdetWQV1dXfjhhx+kDq3OGjFihNC4cWPh4MGDwp07d4Q9e/YIDRs2FKZOnSp1aHXCs2fPhMuXLwuXL18WAAjLly8XLl++LNy9e1cQBEEICwsTdHV1hf379wvJyclCv379hObNmwv//POPxJET1S9vy6d8fHyE6dOni+3j4uIEJSUlYenSpUJqaqowZ84coUGDBkJKSopUp1CnVPZ6zp07Vzhy5IiQlpYmJCQkCJ999pmgqqoq/Pbbb1KdQp3xts+B6dOnCz4+PmL727dvC+rq6sKUKVOE1NRUYe3atYKioqIQFRUl1SnUOZW9pt98842wb98+4ebNm0JKSoowceJEQUFBQTh69KhUp1BnVOT7Ff9+So+FKaoVq1evFpo2bSooKysL7du3F86dOyd1SHUSgFKXzZs3Sx1avcLCVPl+/vlnwcHBQVBRURFsbGyE9evXSx1Snfb06VNh4sSJQtOmTQVVVVXBwsJCmDFjhpCXlyd1aHVC8U9Uv7mMGDFCEARBKCoqEmbNmiUYGRkJKioqQrdu3YTr169LGzRRPVVePtW5c2fx312xXbt2CdbW1oKysrJgb28vHDp0qJYjrtsqcz0DAgLEtkZGRkKvXr2ES5cuSRB13fO2z4ERI0YInTt3LrFP69atBWVlZcHCwoK57hsqe00XLVoktGjRQlBVVRX09fWFLl26CMeOHZMm+DqmIt+v+PdTejJBEITaGJlFRERERERERET0Os4xRUREREREREREkmBhioiIiIiIiIiIJMHCFBERERERERERSYKFKSIiIiIiIiIikgQLU0REREREREREJAkWpoiIiIiIiIiISBIsTBERERERERERkSRYmCIiIiIiIiIiIkmwMEVEVEUymQz79u2TOgxJpaenQyaTITExEQAQGxsLmUyGJ0+eSBoXERER1X/MtZhr0YeBhSkiqvdGjhwJmUwGmUwGZWVlWFpaYt68eXj58mWNHjczMxM9e/as8v7FiUbxYmBgAHd3d1y+fLkao6xdrq6uyMzMhI6OjtShEBERUTVhrlV3MNei9xELU0T0XvD09ERmZiZu3ryJyZMnIzg4GEuWLCm1bX5+frUc09jYGCoqKu/cz9GjR5GZmYkjR44gJycHPXv2LPMuWEFBwTsfryYpKyvD2NgYMplM6lCIiIioGjHXqhuYa9H7iIUpInovqKiowNjYGM2aNcO4cePQvXt3HDhwAMCru3z9+/fHggULYGpqipYtWwIA7t27hyFDhkBXVxf6+vro168f0tPT5frdtGkT7O3toaKiAhMTE/j7+4vb3hxenpKSgn//+99QU1ODgYEBxowZg5ycnLfGbmBgAGNjY7i4uGDp0qX4448/cP78efEu386dO9G5c2eoqqpi69atKCoqwrx589CkSROoqKigdevWiIqKEvsr3m/Xrl3o1KkT1NTU0K5dO9y4cQPx8fFwcXGBpqYmevbsiT///FMulg0bNsDW1haqqqqwsbHBunXr5LZfuHABzs7OUFVVhYuLS4k7jqUNL9+9e7d4Dc3NzbFs2bK3XhMiIiKqW5hrMdciqiksTBHRe0lNTU3ubl1MTAyuX7+O6OhoHDx4EAUFBfDw8ICWlhZOnTqFuLg4aGpqwtPTU9wvPDwcfn5+GDNmDFJSUnDgwAFYWlqWerzc3Fx4eHhAT08P8fHx+PHHH3H06FG55KqicQPydxqnT5+OiRMnIjU1FR4eHli5ciWWLVuGpUuXIjk5GR4eHujbty9u3rwp19ecOXMwc+ZMXLp0CUpKShg2bBimTp2KlStX4tSpU7h16xZmz54ttt+6dStmz56NBQsWIDU1FQsXLsSsWbOwZcsWAEBOTg769OkDOzs7JCQkIDg4GIGBgeWeT0JCAoYMGYLPPvsMKSkpCA4OxqxZsxAZGVmp60JERER1C3Mt5lpE1UYgIqrnRowYIfTr108QBEEoKioSoqOjBRUVFSEwMFDcbmRkJOTl5Yn7fP/990LLli2FoqIicV1eXp6gpqYmHDlyRBAEQTA1NRVmzJhR5nEBCHv37hUEQRDWr18v6OnpCTk5OeL2Q4cOCQoKCkJWVlap+9+5c0cAIFy+fFkQBEH4+++/hQEDBgiamppCVlaWuH3FihVy+5mamgoLFiyQW9euXTvB19dXrt8NGzaI27dv3y4AEGJiYsR1oaGhQsuWLcXXLVq0ELZt2ybXb0hIiNCxY0dBEAThu+++EwwMDIR//vlH3B4eHi53DsePHxcACH///bcgCIIwbNgwoUePHnJ9TpkyRbCzsyv1mhAREVHdw1yLuRZRTVKSohhGRFTdDh48CE1NTRQUFKCoqAjDhg1DcHCwuN3R0RHKysri66SkJNy6dQtaWlpy/bx48QJpaWl4+PAhfv/9d3Tr1q1Cx09NTYWTkxM0NDTEdW5ubigqKsL169dhZGRU5r6urq5QUFBAbm4uLCwssHPnThgZGYlD3V1cXMS2T58+xe+//w43Nze5Ptzc3JCUlCS3rlWrVuJ/Fx/f0dFRbt3Dhw8BvLoLmZaWhtGjR+OLL74Q27x8+VKcXDM1NRWtWrWCqqqquL1jx45vvS79+vUrEeuKFStQWFgIRUXFcvcnIiKiuoG5FnMtoprCwhQRvRe6du2K8PBwKCsrw9TUFEpK8n/eXk9igFdDpdu2bYutW7eW6KtRo0ZQUKi9J5137twJOzs7GBgYQFdXt8T2N2OvqAYNGoj/XTxB5pvrioqKAECcnyEiIgIdOnSQ64cJDRERETHXKom5FlH14BxTRPRe0NDQgKWlJZo2bVoiUSpNmzZtcPPmTRgaGsLS0lJu0dHRgZaWFszNzRETE1Oh49va2iIpKQm5ubniuri4OCgoKIgTgJbFzMwMLVq0KDVRepO2tjZMTU0RFxcntz4uLg52dnYVirU0RkZGMDU1xe3bt0tcj+bNmwN4dY7Jycl48eKFuN+5c+fK7dfW1rbUWK2trZmEERER1SPMtZhrEdUUFqaI6IPk7e2Nhg0bol+/fjh16hTu3LmD2NhYTJgwAffv3wcABAcHY9myZVi1ahVu3ryJS5cuYfXq1WX2p6qqihEjRuDKlSs4fvw4xo8fDx8fn3KHllfFlClTsGjRIuzcuRPXr1/H9OnTkZiYiIkTJ75Tv3PnzkVoaChWrVqFGzduICUlBZs3b8by5csBAMOGDYNMJsMXX3yBq1ev4vDhw1i6dGm5fU6ePBkxMTEICQnBjRs3sGXLFqxZs+atE3kSERFR/cZcqyTmWkSl46N8RPRBUldXx8mTJzFt2jR88sknePbsGRo3boxu3bpBW1sbADBixAi8ePEC33zzDQIDA9GwYUMMGjSozP6OHDmCiRMnol27dlBXV8fAgQPFRKM6TZgwAdnZ2Zg8eTIePnwIOzs7HDhwAFZWVu/U73//+1+oq6tjyZIlmDJlCjQ0NODo6IiAgAAAgKamJn7++WeMHTsWzs7OsLOzw6JFizBw4MAy+2zTpg127dqF2bNnIyQkBCYmJpg3bx5Gjhz5TrESERFR3cZcqyTmWkSlkwmCIEgdBBERERERERERfXj4KB8REREREREREUmChSkiIiIiIiIiIpIEC1NERERERERERCQJFqaIiIiIiIiIiEgSLEwREREREREREZEkWJgiIiIiIiIiIiJJsDBFRERERERERESSYGGKiIiIiIiIiIgkwcIUERERERERERFJgoUpIiIiIiIiIiKSBAtTREREREREREQkCRamiIiIiIiIiIhIEv8P7oIdGnKRJrIAAAAASUVORK5CYII=",
            "text/plain": [
              "<Figure size 1200x500 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "inmuebles_mayor_precio = BarrioValorMetroCuadrado.sort_values(by=['Precio por Metro Cuadrado'], ascending=False).head(10)\n",
        "\n",
        "inmuebles_menor_precio = BarrioValorMetroCuadrado.sort_values(by=['Precio por Metro Cuadrado']).head(10)\n",
        "\n",
        "fig, axs = plt.subplots(1, 2, figsize=(12, 5))\n",
        "\n",
        "# Primer gráfico: Top 10 de barrios con mayor precio promedio\n",
        "axs[0].barh(inmuebles_mayor_precio['Barrio'], inmuebles_mayor_precio['Precio por Metro Cuadrado'], color='green')\n",
        "axs[0].invert_yaxis()\n",
        "axs[0].set_xlabel('Precio Promedio')\n",
        "axs[0].set_ylabel('Barrio')\n",
        "axs[0].set_title('Top 10 Barrios con Mayor Precio Promedio',fontweight='bold')\n",
        "for valor, categoria in zip(inmuebles_mayor_precio['Precio por Metro Cuadrado'], inmuebles_mayor_precio['Barrio']):\n",
        "    axs[0].text(valor, categoria, str('%.2f' %valor), ha='left', va='center')\n",
        "\n",
        "# Segundo gráfico: Top 10 de barrios con menor precio promedio\n",
        "axs[1].barh(inmuebles_menor_precio['Barrio'], inmuebles_menor_precio['Precio por Metro Cuadrado'], color='blue')\n",
        "axs[1].invert_yaxis()\n",
        "axs[1].set_xlabel('Precio Promedio')\n",
        "axs[1].set_ylabel('Barrio')\n",
        "axs[1].set_title('Top 10 Barrios con Menor Precio Promedio',fontweight='bold')\n",
        "for valor, categoria in zip(inmuebles_menor_precio['Precio por Metro Cuadrado'], inmuebles_menor_precio['Barrio']):\n",
        "    axs[1].text(valor, categoria, str('%.2f' %valor), ha='left', va='center')\n",
        "\n",
        "# Ajustar el espacio entre subgráficos\n",
        "plt.tight_layout()\n",
        "\n",
        "# Mostrar la figura con los dos gráficos\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "id": "l7IujydcVLW0"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Frecuencia')"
            ]
          },
          "execution_count": 41,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(10,6))\n",
        "grafica1 = sns.histplot(data=inmuebles[inmuebles['Tipo']=='Casa'], x='PrecioMillon', kde=True, hue='Tipo')\n",
        "grafica1.set(title='Distribución de Precio en Millones de los inmuebles tipo Casa en Bogotá')\n",
        "plt.xlabel('Precio en Millones de $ Colombianos')\n",
        "plt.ylabel('Frecuencia')\n",
        "#plt.xlim((50,1000))\n",
        "#plt.savefig('./valor_inmuebles.png',format='png')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Apartamento            7327\n",
              "Casa                   2043\n",
              "Oficina/Consultorio      60\n",
              "Local                    38\n",
              "Edificio                 22\n",
              "Bodega                   13\n",
              "Finca                    11\n",
              "Lote                      6\n",
              "Name: Tipo, dtype: int64"
            ]
          },
          "execution_count": 43,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "inmuebles.Tipo.value_counts()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1500x500 with 3 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "arrayTipo=['Apartamento','Casa','Finca']\n",
        "colores = ['blue', 'green', 'red']\n",
        "fig, axs = plt.subplots(1, 3, figsize=(15, 5))\n",
        "for i, tipo in enumerate(arrayTipo):\n",
        "    datos_tipo = inmuebles[inmuebles['Tipo'] == tipo]\n",
        "    sns.histplot(data=datos_tipo, x='PrecioMillon', bins=20, kde=True, ax=axs[i],color=colores[i])\n",
        "    axs[i].set_xlabel('Precio en Millones')\n",
        "    axs[i].set_ylabel('Frecuencia')\n",
        "    axs[i].set_title(f'Histograma de Precios de {tipo}', fontweight='bold', color=colores[i])\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "**Comparación Apartamento versus Casa**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 127,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "DataCasaApartamento=inmuebles[inmuebles['Tipo'].isin(['Casa','Apartamento'])]\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "grafica=sns.histplot(data=DataCasaApartamento,x='PrecioMillon',kde=True,hue='Tipo')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 130,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "DataCasaApartamento=inmuebles[inmuebles['Tipo'].isin(['Casa','Apartamento'])]\n",
        "plt.figure(figsize=(10,5))\n",
        "plt.xlim((2000,12000))\n",
        "plt.ylim((0,500))\n",
        "grafica=sns.histplot(data=DataCasaApartamento,x='PrecioMillon',kde=True,hue='Tipo',bins=20)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 129,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(0.0, 100.0)"
            ]
          },
          "execution_count": 129,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x800 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "DataCasaFinca=inmuebles[inmuebles['Tipo'].isin(['Finca','Apartamento'])]\n",
        "plt.figure(figsize=(10,8))\n",
        "grafica=sns.histplot(data=DataCasaFinca,x='PrecioMillon',hue='Tipo',bins=10)\n",
        "plt.ylim((0,100))\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## **Conclusiones:**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        " Al comparar las casas, apartamentos y fincas se observa que la cantidad de apartamentos es por lejos lo que mayor se presenta. Para los tres tipos se observa que la concentración de frecuencia se presenta en los precios menores. Para el caso de las casas y apartementos se observa una cierta continuidad de precios lo que significa que la oferta es diversa que cubre varios segmentos de clientes. Para el caso de las fincas, se observa que los precios son más discretos y la frecuencia es marcada y notoriamente menor frente a los apartamentos y las casas. Por último, se observa que para precios altos, aproximadamente, sobre los 2000 Millones la frecuencia de las casas y apartamentos se comporta de manera similar."
      ]
    }
  ],
  "metadata": {
    "colab": {
      "include_colab_link": true,
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.6"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}