clase 01 de nuestra inmersión datos con Python.ipynb

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        "<a href=\"https://colab.research.google.com/github/sheilidi/Inmersi-n-de-Datos-con-Python/blob/main/clase%2001%20de%20nuestra%20inmersi%C3%B3n%20datos%20con%20Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
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      "source": [
        "Bienvenido a nuestro primer ecuentro de inmersion de datos\n"
      ],
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        "id": "-zwu2rbWoGeL"
      }
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          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount(\"/content/drive\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "inmuebles = pd.read_csv (\"/inmuebles_bogota.csv\")\n",
        "\n",
        "inmuebles.head()"
      ],
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              "          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  "
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              "      <td>$ 1.120.000.000</td>\n",
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              "      <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",
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        "inmuebles.shape"
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            "text/plain": [
              "(9520, 8)"
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        "inmuebles.columns"
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        "id": "HmVaMMkOvm14",
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      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Tipo', 'Descripcion', 'Habitaciones', 'Baños', 'Área', 'Barrio', 'UPZ',\n",
              "       'Valor'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "columnas = {\"Baños\":\"Banos\", \"Área\": \"Area\"}\n",
        "inmuebles = inmuebles.rename(columns=columnas)\n",
        "inmuebles.sample(10)"
      ],
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      "execution_count": 28,
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            "text/plain": [
              "             Tipo                                 Descripcion  Habitaciones  \\\n",
              "5996         Casa             Casa en venta en Ciudad Bolívar             2   \n",
              "9266         Casa                   Casa en venta en Fontibón             5   \n",
              "5601  Apartamento  Apartamento en venta en Zona Noroccidental             3   \n",
              "5918         Casa         Casa en venta en Zona Noroccidental             5   \n",
              "7641  Apartamento         Apartamento en venta en El Castillo             3   \n",
              "1523  Apartamento       Apartamento en venta en Santa Barbara             2   \n",
              "5099  Apartamento         Apartamento en venta en Bella Suiza             2   \n",
              "7395  Apartamento  Apartamento en venta en Zona Noroccidental             2   \n",
              "2500  Apartamento      Apartamento en venta en Barrios Unidos             2   \n",
              "2596  Apartamento                Apartamento en venta en Suba             3   \n",
              "\n",
              "      Banos  Area              Barrio  \\\n",
              "5996      1    53      Ciudad Bolívar   \n",
              "9266      5   326            Fontibón   \n",
              "5601      2    78  Zona Noroccidental   \n",
              "5918      6   550  Zona Noroccidental   \n",
              "7641      5   200         El Castillo   \n",
              "1523      3    91       Santa Barbara   \n",
              "5099      2    95         Bella Suiza   \n",
              "7395      2    58  Zona Noroccidental   \n",
              "2500      2    53      Barrios Unidos   \n",
              "2596      3   121                Suba   \n",
              "\n",
              "                                                    UPZ            Valor  \n",
              "5996  CIUDAD BOLÍVAR: Monteblanco + El Tesoro + El M...    $ 140.000.000  \n",
              "9266                                           Fontibón    $ 650.000.000  \n",
              "5601                 CHAPINERO: Pardo Rubio + Chapinero    $ 232.000.000  \n",
              "5918                 CHAPINERO: Pardo Rubio + Chapinero  $ 3.850.000.000  \n",
              "7641                                             Lucero  $ 1.900.000.000  \n",
              "1523              USAQUÉN: Country Club + Santa Bárbara    $ 840.000.000  \n",
              "5099              USAQUÉN: Country Club + Santa Bárbara    $ 580.000.000  \n",
              "7395                 CHAPINERO: Pardo Rubio + Chapinero    $ 309.000.000  \n",
              "2500                                          Los Andes    $ 150.500.000  \n",
              "2596                                               Suba    $ 850.000.000  "
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              "      <th>5996</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Ciudad Bolívar</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>53</td>\n",
              "      <td>Ciudad Bolívar</td>\n",
              "      <td>CIUDAD BOLÍVAR: Monteblanco + El Tesoro + El M...</td>\n",
              "      <td>$ 140.000.000</td>\n",
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              "      <th>9266</th>\n",
              "      <td>Casa</td>\n",
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              "      <th>5601</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Zona Noroccidental</td>\n",
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              "      <td>Zona Noroccidental</td>\n",
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              "      <td>$ 232.000.000</td>\n",
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              "      <th>5918</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Zona Noroccidental</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>550</td>\n",
              "      <td>Zona Noroccidental</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 3.850.000.000</td>\n",
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              "    <tr>\n",
              "      <th>7641</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en El Castillo</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>200</td>\n",
              "      <td>El Castillo</td>\n",
              "      <td>Lucero</td>\n",
              "      <td>$ 1.900.000.000</td>\n",
              "    </tr>\n",
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              "      <th>1523</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>$ 840.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5099</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Bella Suiza</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>95</td>\n",
              "      <td>Bella Suiza</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 580.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7395</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Zona Noroccidental</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>58</td>\n",
              "      <td>Zona Noroccidental</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 309.000.000</td>\n",
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              "      <th>2500</th>\n",
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              "      <td>Apartamento en venta en Barrios Unidos</td>\n",
              "      <td>2</td>\n",
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              "      <td>53</td>\n",
              "      <td>Barrios Unidos</td>\n",
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              "      <td>$ 150.500.000</td>\n",
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              "      <th>2596</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Suba</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>121</td>\n",
              "      <td>Suba</td>\n",
              "      <td>Suba</td>\n",
              "      <td>$ 850.000.000</td>\n",
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          "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"
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              "            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  "
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        "inmuebles[\"Valor\"][300]"
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      "execution_count": 31,
      "outputs": [
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          "data": {
            "text/plain": [
              "'$ 116.100.000'"
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          "execution_count": 31
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        "outputId": "56bfae9f-db1c-41dc-ccb6-3a3e852b8ddd"
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      "execution_count": 32,
      "outputs": [
        {
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          "data": {
            "text/plain": [
              "pandas.core.series.Series"
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          "metadata": {},
          "execution_count": 32
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            "text/plain": [
              "             Tipo                                  Descripcion  Habitaciones  \\\n",
              "3696  Apartamento              Apartamento en venta en Tintala             3   \n",
              "6248  Apartamento             Apartamento en venta en El Batán             2   \n",
              "6663         Casa                    Casa en venta en Cedritos             4   \n",
              "1536  Apartamento       Apartamento en venta en Barrios Unidos             2   \n",
              "4035  Apartamento            Apartamento en venta en Chapinero             2   \n",
              "...           ...                                          ...           ...   \n",
              "4990  Apartamento  Apartamento en venta en Nicolas De Federman             3   \n",
              "9343  Apartamento           Apartamento en venta en La Calleja             2   \n",
              "7148  Apartamento             Apartamento en venta en Fontibón             3   \n",
              "1446  Apartamento       Apartamento en venta en Nueva Zelandia             2   \n",
              "1112  Apartamento             Apartamento en venta en El Chicó             5   \n",
              "\n",
              "      Banos  Area               Barrio  \\\n",
              "3696      1    47              Tintala   \n",
              "6248      3    75             El Batán   \n",
              "6663      4   161             Cedritos   \n",
              "1536      3    75       Barrios Unidos   \n",
              "4035      3    79            Chapinero   \n",
              "...     ...   ...                  ...   \n",
              "4990      3   106  Nicolas De Federman   \n",
              "9343      3    68           La Calleja   \n",
              "7148      2   109             Fontibón   \n",
              "1446      1    40       Nueva Zelandia   \n",
              "1112      4   200             El Chicó   \n",
              "\n",
              "                                                    UPZ            Valor  \n",
              "3696                                            Tintala    $ 152.000.000  \n",
              "6248                                        La Alhambra    $ 411.000.000  \n",
              "6663                                            Usaquén    $ 620.000.000  \n",
              "1536                                          Los Andes    $ 260.000.000  \n",
              "4035                 CHAPINERO: Pardo Rubio + Chapinero    $ 680.000.000  \n",
              "...                                                 ...              ...  \n",
              "4990                                        Teusaquillo    $ 570.000.000  \n",
              "9343              USAQUÉN: Country Club + Santa Bárbara    $ 535.000.000  \n",
              "7148                                           Fontibón    $ 490.000.000  \n",
              "1446  SUBA: La Academia + Guaymaral + San José de Ba...    $ 213.000.000  \n",
              "1112                 CHAPINERO: Chicó Lago + El Refugio  $ 1.800.000.000  \n",
              "\n",
              "[100 rows x 8 columns]"
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              "    <tr>\n",
              "      <th>4035</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chapinero</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>79</td>\n",
              "      <td>Chapinero</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 680.000.000</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>4990</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Nicolas De Federman</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>106</td>\n",
              "      <td>Nicolas De Federman</td>\n",
              "      <td>Teusaquillo</td>\n",
              "      <td>$ 570.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9343</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en La Calleja</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>68</td>\n",
              "      <td>La Calleja</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 535.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7148</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Fontibón</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>109</td>\n",
              "      <td>Fontibón</td>\n",
              "      <td>Fontibón</td>\n",
              "      <td>$ 490.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1446</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Nueva Zelandia</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>40</td>\n",
              "      <td>Nueva Zelandia</td>\n",
              "      <td>SUBA: La Academia + Guaymaral + San José de Ba...</td>\n",
              "      <td>$ 213.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1112</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en El Chicó</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>200</td>\n",
              "      <td>El Chicó</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 1.800.000.000</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-e03baf7c-47cd-4360-b1c3-4fbd8a43f121')\"\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-e03baf7c-47cd-4360-b1c3-4fbd8a43f121 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-e03baf7c-47cd-4360-b1c3-4fbd8a43f121');\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": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "(inmuebles.Barrio == \"Chico Reservado\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rLqBDZJF2d8P",
        "outputId": "b15d57aa-67e9-4644-a7a0-ef1766da9230"
      },
      "execution_count": 35,
      "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": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sum((inmuebles.Barrio == \"Chico Reservado\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QZjdYvLP2yj0",
        "outputId": "ca4f735b-3e40-4e85-c167-d9fd66dc175b"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "225"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles_chico = (inmuebles.Barrio == \"Chico Reservado\")\n",
        "inmuebles_chico\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OjUdYpsx3Gux",
        "outputId": "e7c6d227-07c6-427c-ce57-9705685e5806"
      },
      "execution_count": 37,
      "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": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles_barrio = inmuebles.Barrio.value_counts()\n",
        "inmuebles_barrio.plot.bar()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        },
        "id": "gPTSmEH-5QFD",
        "outputId": "9cbc14e6-3f07-492a-cc6b-9da5cd1aa47f"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 38
        },
        {
          "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": [
        "1.Promedio de área de todos los inmubles en los barrios en dataset.El top 10\n",
        " "
      ],
      "metadata": {
        "id": "Y9xYCT7P7I3R"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "promedio_area = inmuebles.groupby('Barrio').Area.mean()\n",
        "promedio_area"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9sZcNY_p8nKU",
        "outputId": "1a89148a-16f7-4d39-97f2-30a9f8c1c084"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Barrio\n",
              "Alameda                97.000000\n",
              "Alhambra              190.411765\n",
              "Andes Norte           124.857143\n",
              "Antonio Nariño        163.062500\n",
              "Barrancas              70.200000\n",
              "                         ...    \n",
              "Villa Maria           207.153846\n",
              "Villas De Granada      86.590909\n",
              "Villemar               76.888889\n",
              "Zona Franca            54.000000\n",
              "Zona Noroccidental    135.785633\n",
              "Name: Area, Length: 149, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles_barrio.head(10).plot.bar()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 370
        },
        "id": "HJIDIwpz560z",
        "outputId": "3f812a99-b063-430d-d577-d6f108058f56"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 47
        },
        {
          "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": [
        "2. Consultar otros datos estadisticos, conteo, mediana, valores minimos y máximo "
      ],
      "metadata": {
        "id": "itFkcRMF7ujS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "promedio_habitaciones = inmuebles.groupby('Barrio').Habitaciones.mean()\n",
        "promedio_habitaciones"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5OaoJ2-o81ym",
        "outputId": "dbd0e721-cc80-438b-e46e-6162d9d0e8be"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Barrio\n",
              "Alameda               3.000000\n",
              "Alhambra              3.000000\n",
              "Andes Norte           3.000000\n",
              "Antonio Nariño        4.312500\n",
              "Barrancas             2.866667\n",
              "                        ...   \n",
              "Villa Maria           4.692308\n",
              "Villas De Granada     3.454545\n",
              "Villemar              2.944444\n",
              "Zona Franca           2.000000\n",
              "Zona Noroccidental    3.167617\n",
              "Name: Habitaciones, Length: 149, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "promedio_habitaciones.sort_values(ascending=False).head(10).plot.bar()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "id": "t78UmsgV9AOc",
        "outputId": "d871e023-b9d2-47ed-ed34-c7fbe6f728ba"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Barrio'>"
            ]
          },
          "metadata": {},
          "execution_count": 51
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}