INMERSION_DATOS_AULA_1.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ahcamachod/inmersion-en-datos/blob/aula-1/INMERSION_DATOS_AULA_1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Bienvenido a nuestro primer encuentro de inmersión de datos."
      ],
      "metadata": {
        "id": "qGW8k7mWhP7O"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "Y2BMxIBqhcl7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f5567dfb-4052-41ec-a38a-6b936e29174f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "inmuebles = pd.read_csv('/content/drive/MyDrive/inmersion_datos/inmuebles_bogota.csv') \n",
        "inmuebles.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "id": "S73Bs_z6j2QX",
        "outputId": "4b831b26-43ba-4a3d-ce12-4323cf30379b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fe107a71-70fa-4fdf-a264-9418ac20ff46\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fe107a71-70fa-4fdf-a264-9418ac20ff46')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fe107a71-70fa-4fdf-a264-9418ac20ff46 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-fe107a71-70fa-4fdf-a264-9418ac20ff46');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qkcJjAQrmyfN",
        "outputId": "70d24523-058c-49fb-ca74-e4e9526e33cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(9520, 8)"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K-4LMluEnha_",
        "outputId": "41397e9d-34f1-4146-eead-7aa085322789"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Tipo', 'Descripcion', 'Habitaciones', 'Baños', 'Área', 'Barrio', 'UPZ',\n",
              "       'Valor'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "columnas = {'Baños':'Banos','Área':'Area'}\n",
        "inmuebles = inmuebles.rename(columns=columnas)\n",
        "inmuebles.sample(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "X2nLnlFIn2EM",
        "outputId": "707d8466-e0a9-419e-f499-96c7a348a7c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Tipo                                Descripcion  Habitaciones  \\\n",
              "582          Casa                  Casa en venta en Engativa             3   \n",
              "341   Apartamento  Apartamento en venta en Chapinero Central             3   \n",
              "5582  Apartamento          Apartamento en venta en Chapinero             3   \n",
              "6856  Apartamento      Apartamento en venta en Santa Barbara             3   \n",
              "3482  Apartamento            Apartamento en venta en Venecia             3   \n",
              "6649  Apartamento      Apartamento en venta en Santa Barbara             2   \n",
              "4564         Casa                  Casa en venta en Engativa             4   \n",
              "5686  Apartamento               Apartamento en venta en Niza             3   \n",
              "8853  Apartamento      Apartamento en venta en Santa Barbara             1   \n",
              "6657  Apartamento         Apartamento en venta en Cantagallo             3   \n",
              "\n",
              "      Banos  Area             Barrio                                    UPZ  \\\n",
              "582       3    73           Engativa                               Engativá   \n",
              "341       2    59  Chapinero Central              Localidad Chapinero resto   \n",
              "5582      5   342          Chapinero     CHAPINERO: Pardo Rubio + Chapinero   \n",
              "6856      5   171      Santa Barbara  USAQUÉN: Country Club + Santa Bárbara   \n",
              "3482      2    56            Venecia                                Venecia   \n",
              "6649      3    91      Santa Barbara  USAQUÉN: Country Club + Santa Bárbara   \n",
              "4564      2   177           Engativa                               Engativá   \n",
              "5686      2   132               Niza                                   Niza   \n",
              "8853      2    66      Santa Barbara  USAQUÉN: Country Club + Santa Bárbara   \n",
              "6657      2    68         Cantagallo                               Britalia   \n",
              "\n",
              "                Valor  \n",
              "582     $ 360.000.000  \n",
              "341     $ 180.000.000  \n",
              "5582  $ 3.500.000.000  \n",
              "6856    $ 820.000.000  \n",
              "3482    $ 210.000.000  \n",
              "6649    $ 700.000.000  \n",
              "4564    $ 639.000.000  \n",
              "5686    $ 490.000.000  \n",
              "8853    $ 453.500.000  \n",
              "6657    $ 455.000.000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3dc8ecea-ee20-48ed-834a-84d30bf03608\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>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>341</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chapinero Central</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>59</td>\n",
              "      <td>Chapinero Central</td>\n",
              "      <td>Localidad Chapinero resto</td>\n",
              "      <td>$ 180.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5582</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chapinero</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>342</td>\n",
              "      <td>Chapinero</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 3.500.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6856</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Santa Barbara</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>171</td>\n",
              "      <td>Santa Barbara</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 820.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3482</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Venecia</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>56</td>\n",
              "      <td>Venecia</td>\n",
              "      <td>Venecia</td>\n",
              "      <td>$ 210.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6649</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Santa Barbara</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>91</td>\n",
              "      <td>Santa Barbara</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 700.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4564</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Engativa</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>177</td>\n",
              "      <td>Engativa</td>\n",
              "      <td>Engativá</td>\n",
              "      <td>$ 639.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5686</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Niza</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>132</td>\n",
              "      <td>Niza</td>\n",
              "      <td>Niza</td>\n",
              "      <td>$ 490.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8853</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Santa Barbara</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>66</td>\n",
              "      <td>Santa Barbara</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 453.500.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6657</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Cantagallo</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>68</td>\n",
              "      <td>Cantagallo</td>\n",
              "      <td>Britalia</td>\n",
              "      <td>$ 455.000.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3dc8ecea-ee20-48ed-834a-84d30bf03608')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-3dc8ecea-ee20-48ed-834a-84d30bf03608 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-3dc8ecea-ee20-48ed-834a-84d30bf03608');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KJT8oyJgo2hU",
        "outputId": "ab8a3065-0528-42fd-caba-f8862ead60cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "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"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.iloc[300]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eyrj-ItzplxW",
        "outputId": "327a14b3-831f-4714-b37b-9c18f77d8528"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.iloc[300:305]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "id": "NiK43WPcr0GG",
        "outputId": "26a4823d-a49d-4f20-83eb-227a207493cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9b1b806a-34a1-41c7-8552-792c69cfca85\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-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",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles['Valor'][300]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "65he94kAsMXL",
        "outputId": "c5f4c8d9-668e-45f8-d900-055b21d147fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'$ 116.100.000'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(inmuebles['Valor'][300:305])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iFH5bi8EsbRe",
        "outputId": "ec6920f5-1f96-4831-ecaa-35f96a1673ed"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.series.Series"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "601xMJ2ashKu",
        "outputId": "0f16ac4f-11c8-4a46-9aa9-96c265d78dd4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Tipo', 'Descripcion', 'Habitaciones', 'Banos', 'Area', 'Barrio', 'UPZ',\n",
              "       'Valor'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.Area.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I1pyNc9Xs85S",
        "outputId": "f95e05eb-5f6f-4728-83c8-3db7ee90f890"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "146.66470588235293"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.sample(100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 641
        },
        "id": "iYqOIwb_tPfj",
        "outputId": "963f5ee5-c95a-4066-c3dc-3edd6a4866fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e2bad7e0-5684-480d-a14f-03a757c5e784\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>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",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e2bad7e0-5684-480d-a14f-03a757c5e784 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-e2bad7e0-5684-480d-a14f-03a757c5e784');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "(inmuebles.Barrio == 'Chico Reservado')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YY-zAytFuBsA",
        "outputId": "8c08827a-e7dd-4f56-a74e-5b6d0c6354f2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sum((inmuebles.Barrio == 'Chico Reservado'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3OJg8M1TuwcZ",
        "outputId": "4e4becb5-55bb-44a7-968a-e4d33de6bf9f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "225"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles_chico = (inmuebles.Barrio == 'Chico Reservado')\n",
        "type(inmuebles_chico)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HtT_ZLvGu_CP",
        "outputId": "e1a40547-8f08-4d93-9514-c1c21cec437c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.series.Series"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chico_reservado = inmuebles[inmuebles_chico]\n",
        "chico_reservado"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 641
        },
        "id": "mQJesAi_vLbs",
        "outputId": "c498cb6e-df9d-42ae-f07d-2fc194d62433"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5c1c1984-adaa-4149-81ba-c70e64f37eae\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>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>39</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>1</td>\n",
              "      <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",
              "      <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>126</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <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",
              "      <th>9472</th>\n",
              "      <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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9506</th>\n",
              "      <td>Apartamento</td>\n",
              "      <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",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5c1c1984-adaa-4149-81ba-c70e64f37eae')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5c1c1984-adaa-4149-81ba-c70e64f37eae 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-5c1c1984-adaa-4149-81ba-c70e64f37eae');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chico_reservado.Area.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j3IYReywvf26",
        "outputId": "db4a79a6-9ba4-44f6-824f-7faf39b6115f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "142.78666666666666"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.Area.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P7V5_WzXxCDl",
        "outputId": "9c69cd96-1c1e-4dfa-f3b2-05b0d8c192b3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "146.66470588235293"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(inmuebles.Barrio.value_counts())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "54SeSdSFxZ9v",
        "outputId": "c0c7c971-a08e-4b23-e3fe-e7abdfa8be42"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "149"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.Barrio.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aJz7RkSBxpVf",
        "outputId": "a57555c8-8cf6-48ff-807e-4cf9bd46c1e6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(inmuebles.UPZ.value_counts())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eN0cDITxxtvH",
        "outputId": "e32ef258-5506-4e7f-f9ad-b57535ccad2b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "63"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles_barrio = inmuebles.Barrio.value_counts()\n",
        "inmuebles_barrio.plot.bar()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 389
        },
        "id": "BcKfcc3nx9fg",
        "outputId": "b2c6f105-715e-4843-bdc8-0ab0f111668d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe758b604f0>"
            ]
          },
          "metadata": {},
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles_barrio.head(10).plot.bar()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 371
        },
        "id": "EXzn-YDLybRx",
        "outputId": "060c6792-90b6-4bee-b637-5dec6614b6f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe7590b21f0>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "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."
      ],
      "metadata": {
        "id": "owP_SeWgzaYR"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Aula 2**"
      ],
      "metadata": {
        "id": "YFNuHdUZJJtL"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "VtMPWPRHs4ys"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}