LIMPIEZA FINAL.ipynb

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    {
      "cell_type": "markdown",
      "source": [
        "#IMPORTACION DE BIBLIOTECAS"
      ],
      "metadata": {
        "id": "lQ3Sd6y4IJ26"
      }
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    {
      "cell_type": "code",
      "execution_count": 123,
      "metadata": {
        "id": "6Jx4ufWsULP9"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "from bs4 import BeautifulSoup\n",
        "import numpy as np\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#LECTURA DEL DATAFRAME\n",
        "df = pd.read_csv('/content/[2023-9-10]propiedades_argenprop.csv')\n",
        "df"
      ],
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        "id": "hVXKmXRcisP-",
        "outputId": "d9b940a5-d43c-42c8-997c-c0343a430488"
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      "execution_count": 124,
      "outputs": [
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            "text/plain": [
              "                                                    URL  \\\n",
              "0     https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "1     https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "2     https://www.argenprop.com/departamento-en-alqu...   \n",
              "3     https://www.argenprop.com/departamento-en-alqu...   \n",
              "4     https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "...                                                 ...   \n",
              "9319  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "9320  https://www.argenprop.com/cochera-en-alquiler-...   \n",
              "9321  https://www.argenprop.com/local-en-alquiler-en...   \n",
              "9322  https://www.argenprop.com/departamento-en-alqu...   \n",
              "9323  https://www.argenprop.com/departamento-en-alqu...   \n",
              "\n",
              "                    Ubicación  Precio ARS  Precio USD  Expensas  \\\n",
              "0     Honorio Pueyrredón 5500         NaN      1400.0       NaN   \n",
              "1          Barrio Los Pilares         NaN      1000.0       NaN   \n",
              "2            Av. Balbin  2400         NaN      1100.0       NaN   \n",
              "3           Juramento al 1400         NaN       250.0   17500.0   \n",
              "4       Village Golf & Tennis         NaN      4000.0       NaN   \n",
              "...                       ...         ...         ...       ...   \n",
              "9319          Centeno al 3200    130000.0         NaN       NaN   \n",
              "9320  ESPAÑA 1300 COCH SUB 05     23000.0         NaN       NaN   \n",
              "9321         Av. Uriburu 2000    180000.0         NaN       NaN   \n",
              "9322   Avenida Pellegrini 600     80000.0         NaN   14000.0   \n",
              "9323   Av. Portugal , Piso 04    100000.0         NaN       NaN   \n",
              "\n",
              "      Sup. cubierta [m²] Dormitorios  Baños Ambientes  Cocheras  ...  \\\n",
              "0                  160.0           3    2.0         4       4.0  ...   \n",
              "1                    NaN           2    2.0         3       2.0  ...   \n",
              "2                   76.0           2    2.0         3       1.0  ...   \n",
              "3                   35.0         NaN    1.0         0       NaN  ...   \n",
              "4                  330.0           4    2.0         6       1.0  ...   \n",
              "...                  ...         ...    ...       ...       ...  ...   \n",
              "9319               160.0           3    2.0         4       1.0  ...   \n",
              "9320                 NaN         NaN    NaN       NaN       NaN  ...   \n",
              "9321                 NaN         NaN    1.0       NaN       1.0  ...   \n",
              "9322                35.0         NaN    1.0         0       NaN  ...   \n",
              "9323                40.0           1    1.0         2       NaN  ...   \n",
              "\n",
              "      Tipo de coche Tipo de acceso  Superficie cubierta Cantidad baños FOT  \\\n",
              "0               NaN            NaN                  NaN            NaN NaN   \n",
              "1               NaN            NaN                  NaN            NaN NaN   \n",
              "2               NaN            NaN                  NaN            NaN NaN   \n",
              "3               NaN            NaN                  NaN            NaN NaN   \n",
              "4               NaN            NaN                  NaN            NaN NaN   \n",
              "...             ...            ...                  ...            ...  ..   \n",
              "9319            NaN            NaN                  NaN            NaN NaN   \n",
              "9320            NaN            NaN                  NaN            NaN NaN   \n",
              "9321            NaN            NaN                  NaN            NaN NaN   \n",
              "9322            NaN            NaN                  NaN            NaN NaN   \n",
              "9323            NaN            NaN                  NaN            NaN NaN   \n",
              "\n",
              "      Toilletes Sup. Cubierta Pileta  Habitaciones Descripción  \n",
              "0           NaN           NaN    NaN           NaN         NaN  \n",
              "1           NaN           NaN    NaN           NaN         NaN  \n",
              "2           NaN           NaN    NaN           NaN         NaN  \n",
              "3           NaN           NaN    NaN           NaN         NaN  \n",
              "4           NaN           NaN    NaN           NaN         NaN  \n",
              "...         ...           ...    ...           ...         ...  \n",
              "9319        NaN           NaN    NaN           NaN         NaN  \n",
              "9320        NaN           NaN    NaN           NaN         NaN  \n",
              "9321        NaN           NaN    NaN           NaN         NaN  \n",
              "9322        NaN           NaN    NaN           NaN         NaN  \n",
              "9323        NaN           NaN    NaN           NaN         NaN  \n",
              "\n",
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              "      <th></th>\n",
              "      <th>URL</th>\n",
              "      <th>Ubicación</th>\n",
              "      <th>Precio ARS</th>\n",
              "      <th>Precio USD</th>\n",
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              "      <th>Cocheras</th>\n",
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              "      <th>Tipo de coche</th>\n",
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              "      <th>Cantidad baños</th>\n",
              "      <th>FOT</th>\n",
              "      <th>Toilletes</th>\n",
              "      <th>Sup. Cubierta</th>\n",
              "      <th>Pileta</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Honorio Pueyrredón 5500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1400.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>160.0</td>\n",
              "      <td>3</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4</td>\n",
              "      <td>4.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Barrio Los Pilares</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3</td>\n",
              "      <td>2.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Av. Balbin  2400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1100.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>76.0</td>\n",
              "      <td>2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Juramento al 1400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>250.0</td>\n",
              "      <td>17500.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Village Golf &amp; Tennis</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>330.0</td>\n",
              "      <td>4</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6</td>\n",
              "      <td>1.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>9319</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Centeno al 3200</td>\n",
              "      <td>130000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>160.0</td>\n",
              "      <td>3</td>\n",
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              "      <td>4</td>\n",
              "      <td>1.0</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>9320</th>\n",
              "      <td>https://www.argenprop.com/cochera-en-alquiler-...</td>\n",
              "      <td>ESPAÑA 1300 COCH SUB 05</td>\n",
              "      <td>23000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>9321</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>Av. Uriburu 2000</td>\n",
              "      <td>180000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>1.0</td>\n",
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              "      <td>1.0</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>9322</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Avenida Pellegrini 600</td>\n",
              "      <td>80000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>14000.0</td>\n",
              "      <td>35.0</td>\n",
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              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
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              "      <th>9323</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Av. Portugal , Piso 04</td>\n",
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              "      <td>1.0</td>\n",
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              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-97e720f4-38c1-46d7-b335-8edf31a3b88d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#DATAFRAME BASE"
      ],
      "metadata": {
        "id": "jEeif8VpIkTa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fOLxHEQvkuFi",
        "outputId": "556f7258-64f9-4021-e5d6-7743e9d59e7c"
      },
      "execution_count": 125,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['URL', 'Ubicación', 'Precio ARS', 'Precio USD', 'Expensas',\n",
              "       'Sup. cubierta [m²]', 'Dormitorios', 'Baños', 'Ambientes', 'Cocheras',\n",
              "       'Sup. terreno [m²]', 'Antigüedad [años]', 'Antiguedad [años]', 'Estado',\n",
              "       'Disposición', 'Toilettes', 'Orientación', 'Apto profesional',\n",
              "       'Sup. total [m²]', 'Seguridad', 'Permite mascota', 'Plantas',\n",
              "       'Superficie Total', 'Longitud del Frente', 'Longitud del Fondo',\n",
              "       'Altura Techo', 'Tipo de Baño', 'Tipo de local', 'En Edificio',\n",
              "       'Longitud del frente', 'Longitud del fondo', 'Tipo de Terreno',\n",
              "       'Sup. Total', 'Sup. descubierta [m²]', 'Galería/Shopping',\n",
              "       'Agua corriente', 'Tipo de cochera', 'Tipo de cobertura',\n",
              "       'Tipo de coche', 'Tipo de acceso', 'Superficie cubierta',\n",
              "       'Cantidad baños', 'FOT', 'Toilletes', 'Sup. Cubierta', 'Pileta',\n",
              "       'Habitaciones', 'Descripción'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 125
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mb-X96mawLwC",
        "outputId": "d254af01-3014-4c1b-a3c5-e0b9ea6ec642"
      },
      "execution_count": 126,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9324 entries, 0 to 9323\n",
            "Data columns (total 48 columns):\n",
            " #   Column                 Non-Null Count  Dtype  \n",
            "---  ------                 --------------  -----  \n",
            " 0   URL                    9324 non-null   object \n",
            " 1   Ubicación              9324 non-null   object \n",
            " 2   Precio ARS             2441 non-null   float64\n",
            " 3   Precio USD             6570 non-null   float64\n",
            " 4   Expensas               3412 non-null   float64\n",
            " 5   Sup. cubierta [m²]     7694 non-null   float64\n",
            " 6   Dormitorios            7014 non-null   object \n",
            " 7   Baños                  8334 non-null   float64\n",
            " 8   Ambientes              7512 non-null   object \n",
            " 9   Cocheras               4607 non-null   float64\n",
            " 10  Sup. terreno [m²]      2587 non-null   float64\n",
            " 11  Antigüedad [años]      3898 non-null   object \n",
            " 12  Antiguedad [años]      4004 non-null   float64\n",
            " 13  Estado                 2451 non-null   object \n",
            " 14  Disposición            1317 non-null   object \n",
            " 15  Toilettes              484 non-null    float64\n",
            " 16  Orientación            1347 non-null   object \n",
            " 17  Apto profesional       693 non-null    object \n",
            " 18  Sup. total [m²]        542 non-null    float64\n",
            " 19  Seguridad              111 non-null    object \n",
            " 20  Permite mascota        107 non-null    object \n",
            " 21  Plantas                207 non-null    object \n",
            " 22  Superficie Total       30 non-null     object \n",
            " 23  Longitud del Frente    20 non-null     object \n",
            " 24  Longitud del Fondo     19 non-null     object \n",
            " 25  Altura Techo           12 non-null     object \n",
            " 26  Tipo de Baño           17 non-null     object \n",
            " 27  Tipo de local          81 non-null     object \n",
            " 28  En Edificio            120 non-null    object \n",
            " 29  Longitud del frente    72 non-null     object \n",
            " 30  Longitud del fondo     71 non-null     object \n",
            " 31  Tipo de Terreno        2 non-null      object \n",
            " 32  Sup. Total             1 non-null      object \n",
            " 33  Sup. descubierta [m²]  26 non-null     float64\n",
            " 34  Galería/Shopping       6 non-null      object \n",
            " 35  Agua corriente         30 non-null     object \n",
            " 36  Tipo de cochera        6 non-null      object \n",
            " 37  Tipo de cobertura      6 non-null      object \n",
            " 38  Tipo de coche          4 non-null      object \n",
            " 39  Tipo de acceso         6 non-null      object \n",
            " 40  Superficie cubierta    3 non-null      object \n",
            " 41  Cantidad baños         1 non-null      object \n",
            " 42  FOT                    2 non-null      float64\n",
            " 43  Toilletes              2 non-null      object \n",
            " 44  Sup. Cubierta          1 non-null      object \n",
            " 45  Pileta                 1 non-null      object \n",
            " 46  Habitaciones           1 non-null      object \n",
            " 47  Descripción            1 non-null      object \n",
            "dtypes: float64(12), object(36)\n",
            "memory usage: 3.4+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "seleccionC= ['URL', 'Ubicación', 'Precio ARS', 'Precio USD','Sup. cubierta [m²]', 'Dormitorios', 'Baños', 'Ambientes',\n",
        "        'Antigüedad [años]', 'Antiguedad [años]', 'Estado',\n",
        "       'Toilettes']"
      ],
      "metadata": {
        "id": "mRmYrhoiwrwC"
      },
      "execution_count": 127,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nuevo_df = df[seleccionC]\n",
        "nuevo_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 738
        },
        "id": "oLH3CPepcXuT",
        "outputId": "3388c1aa-73c5-405c-ad97-b1d9bd3d6d72"
      },
      "execution_count": 128,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    URL  \\\n",
              "0     https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "1     https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "2     https://www.argenprop.com/departamento-en-alqu...   \n",
              "3     https://www.argenprop.com/departamento-en-alqu...   \n",
              "4     https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "...                                                 ...   \n",
              "9319  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "9320  https://www.argenprop.com/cochera-en-alquiler-...   \n",
              "9321  https://www.argenprop.com/local-en-alquiler-en...   \n",
              "9322  https://www.argenprop.com/departamento-en-alqu...   \n",
              "9323  https://www.argenprop.com/departamento-en-alqu...   \n",
              "\n",
              "                    Ubicación  Precio ARS  Precio USD  Sup. cubierta [m²]  \\\n",
              "0     Honorio Pueyrredón 5500         NaN      1400.0               160.0   \n",
              "1          Barrio Los Pilares         NaN      1000.0                 NaN   \n",
              "2            Av. Balbin  2400         NaN      1100.0                76.0   \n",
              "3           Juramento al 1400         NaN       250.0                35.0   \n",
              "4       Village Golf & Tennis         NaN      4000.0               330.0   \n",
              "...                       ...         ...         ...                 ...   \n",
              "9319          Centeno al 3200    130000.0         NaN               160.0   \n",
              "9320  ESPAÑA 1300 COCH SUB 05     23000.0         NaN                 NaN   \n",
              "9321         Av. Uriburu 2000    180000.0         NaN                 NaN   \n",
              "9322   Avenida Pellegrini 600     80000.0         NaN                35.0   \n",
              "9323   Av. Portugal , Piso 04    100000.0         NaN                40.0   \n",
              "\n",
              "     Dormitorios  Baños Ambientes Antigüedad [años]  Antiguedad [años]  \\\n",
              "0              3    2.0         4               NaN                NaN   \n",
              "1              2    2.0         3                14                NaN   \n",
              "2              2    2.0         3               NaN               11.0   \n",
              "3            NaN    1.0         0               NaN               40.0   \n",
              "4              4    2.0         6        A Estrenar                NaN   \n",
              "...          ...    ...       ...               ...                ...   \n",
              "9319           3    2.0         4        A Estrenar                NaN   \n",
              "9320         NaN    NaN       NaN               NaN                NaN   \n",
              "9321         NaN    1.0       NaN                30                NaN   \n",
              "9322         NaN    1.0         0               NaN               55.0   \n",
              "9323           1    1.0         2               NaN                7.0   \n",
              "\n",
              "         Estado  Toilettes  \n",
              "0           NaN        NaN  \n",
              "1           NaN        NaN  \n",
              "2     Muy Bueno        NaN  \n",
              "3           NaN        NaN  \n",
              "4           NaN        NaN  \n",
              "...         ...        ...  \n",
              "9319        NaN        NaN  \n",
              "9320        NaN        NaN  \n",
              "9321        NaN        NaN  \n",
              "9322        NaN        NaN  \n",
              "9323        NaN        NaN  \n",
              "\n",
              "[9324 rows x 12 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1ee6dc2f-b848-4099-a773-f99b9b1f156a\" 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>URL</th>\n",
              "      <th>Ubicación</th>\n",
              "      <th>Precio ARS</th>\n",
              "      <th>Precio USD</th>\n",
              "      <th>Sup. cubierta [m²]</th>\n",
              "      <th>Dormitorios</th>\n",
              "      <th>Baños</th>\n",
              "      <th>Ambientes</th>\n",
              "      <th>Antigüedad [años]</th>\n",
              "      <th>Antiguedad [años]</th>\n",
              "      <th>Estado</th>\n",
              "      <th>Toilettes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Honorio Pueyrredón 5500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1400.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>3</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Barrio Los Pilares</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3</td>\n",
              "      <td>14</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Av. Balbin  2400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1100.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11.0</td>\n",
              "      <td>Muy Bueno</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Juramento al 1400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>250.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Village Golf &amp; Tennis</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4000.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>4</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6</td>\n",
              "      <td>A Estrenar</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9319</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Centeno al 3200</td>\n",
              "      <td>130000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>160.0</td>\n",
              "      <td>3</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4</td>\n",
              "      <td>A Estrenar</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9320</th>\n",
              "      <td>https://www.argenprop.com/cochera-en-alquiler-...</td>\n",
              "      <td>ESPAÑA 1300 COCH SUB 05</td>\n",
              "      <td>23000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9321</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>Av. Uriburu 2000</td>\n",
              "      <td>180000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>30</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9322</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Avenida Pellegrini 600</td>\n",
              "      <td>80000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>35.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>55.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9323</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Av. Portugal , Piso 04</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.0</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9324 rows × 12 columns</p>\n",
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              "  @keyframes spin {\n",
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              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-62b19300-1501-4d70-afce-84d23bb8c89c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 128
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nuevo_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r02BLItvdad2",
        "outputId": "7e847060-af64-4094-e711-b3b216b5bca7"
      },
      "execution_count": 129,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(9324, 12)"
            ]
          },
          "metadata": {},
          "execution_count": 129
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nuevo_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0NPvgFgWdapx",
        "outputId": "756e96f1-5be2-48cc-957e-5b59227822e9"
      },
      "execution_count": 130,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9324 entries, 0 to 9323\n",
            "Data columns (total 12 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 9324 non-null   object \n",
            " 1   Ubicación           9324 non-null   object \n",
            " 2   Precio ARS          2441 non-null   float64\n",
            " 3   Precio USD          6570 non-null   float64\n",
            " 4   Sup. cubierta [m²]  7694 non-null   float64\n",
            " 5   Dormitorios         7014 non-null   object \n",
            " 6   Baños               8334 non-null   float64\n",
            " 7   Ambientes           7512 non-null   object \n",
            " 8   Antigüedad [años]   3898 non-null   object \n",
            " 9   Antiguedad [años]   4004 non-null   float64\n",
            " 10  Estado              2451 non-null   object \n",
            " 11  Toilettes           484 non-null    float64\n",
            "dtypes: float64(6), object(6)\n",
            "memory usage: 874.2+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#ANALISIS Y LIMPIEZA"
      ],
      "metadata": {
        "id": "e9AJdx6cI3Lc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#LUEGO DE LA SELECCION DE LAS COLUMNAS, COMENZAMOS LA LIMPIEZA DE DATOS DENTRO DE CADA COLUMNA.\n",
        "#EN PRIMER LUGAR QUITAREMOS DE LA COLUMNA 'URL' TODAS LAS FILAS QUE CONTENGAN LAS PALABRAS 'LOCAL, COCHERA, NEGOCIO Y OFICINA'\n",
        "\n",
        "localyoficina = nuevo_df.loc[nuevo_df['URL'].str.contains('local|oficina|cochera-en-alquiler|negocio')]\n",
        "localyoficina"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 721
        },
        "id": "_4YKBIFje8HI",
        "outputId": "8dbed6dc-f7cb-4315-fd3e-579bbdf53fbc"
      },
      "execution_count": 131,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    URL  \\\n",
              "6     https://www.argenprop.com/local-en-alquiler-en...   \n",
              "11    https://www.argenprop.com/oficina-en-alquiler-...   \n",
              "14    https://www.argenprop.com/local-en-alquiler-en...   \n",
              "20    https://www.argenprop.com/local-en-alquiler-en...   \n",
              "22    https://www.argenprop.com/oficina-en-alquiler-...   \n",
              "...                                                 ...   \n",
              "9299  https://www.argenprop.com/local-en-alquiler-en...   \n",
              "9306  https://www.argenprop.com/local-en-alquiler-en...   \n",
              "9309  https://www.argenprop.com/local-en-alquiler-en...   \n",
              "9320  https://www.argenprop.com/cochera-en-alquiler-...   \n",
              "9321  https://www.argenprop.com/local-en-alquiler-en...   \n",
              "\n",
              "                     Ubicación  Precio ARS  Precio USD  Sup. cubierta [m²]  \\\n",
              "6          AV DEL ROSARIO  800    180000.0         NaN                 NaN   \n",
              "11           Rioja  1418 01-01     60000.0         NaN                40.0   \n",
              "14          HIRIGOYEN  al 1900    120000.0         NaN                 NaN   \n",
              "20            Dean Funes  3000     60000.0         NaN                 NaN   \n",
              "22    La Voz del Interior 8800    525000.0         NaN               144.0   \n",
              "...                        ...         ...         ...                 ...   \n",
              "9299             Oroño al 5600         NaN      3000.0                 NaN   \n",
              "9306     3 de Febrero  al 1700    180000.0         NaN                 NaN   \n",
              "9309              Zeballos 700    100000.0         NaN                 NaN   \n",
              "9320   ESPAÑA 1300 COCH SUB 05     23000.0         NaN                 NaN   \n",
              "9321          Av. Uriburu 2000    180000.0         NaN                 NaN   \n",
              "\n",
              "     Dormitorios  Baños Ambientes Antigüedad [años]  Antiguedad [años]  \\\n",
              "6            NaN    NaN       NaN        A Estrenar                NaN   \n",
              "11           NaN    1.0       NaN                40                NaN   \n",
              "14           NaN    1.0       NaN        A Estrenar                NaN   \n",
              "20           NaN    1.0       NaN               NaN                NaN   \n",
              "22           NaN    1.0       NaN                 8                NaN   \n",
              "...          ...    ...       ...               ...                ...   \n",
              "9299         NaN    NaN       NaN        A Estrenar                NaN   \n",
              "9306         NaN    1.0       NaN                55                NaN   \n",
              "9309         NaN    1.0       NaN                53                NaN   \n",
              "9320         NaN    NaN       NaN               NaN                NaN   \n",
              "9321         NaN    1.0       NaN                30                NaN   \n",
              "\n",
              "         Estado  Toilettes  \n",
              "6           NaN        NaN  \n",
              "11          NaN        NaN  \n",
              "14          NaN        NaN  \n",
              "20          NaN        NaN  \n",
              "22    Excelente        NaN  \n",
              "...         ...        ...  \n",
              "9299        NaN        NaN  \n",
              "9306        NaN        NaN  \n",
              "9309        NaN        NaN  \n",
              "9320        NaN        NaN  \n",
              "9321        NaN        NaN  \n",
              "\n",
              "[1346 rows x 12 columns]"
            ],
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              "\n",
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>URL</th>\n",
              "      <th>Ubicación</th>\n",
              "      <th>Precio ARS</th>\n",
              "      <th>Precio USD</th>\n",
              "      <th>Sup. cubierta [m²]</th>\n",
              "      <th>Dormitorios</th>\n",
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              "      <th>Ambientes</th>\n",
              "      <th>Antigüedad [años]</th>\n",
              "      <th>Antiguedad [años]</th>\n",
              "      <th>Estado</th>\n",
              "      <th>Toilettes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>AV DEL ROSARIO  800</td>\n",
              "      <td>180000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>A Estrenar</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>https://www.argenprop.com/oficina-en-alquiler-...</td>\n",
              "      <td>Rioja  1418 01-01</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>HIRIGOYEN  al 1900</td>\n",
              "      <td>120000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>A Estrenar</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>Dean Funes  3000</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>https://www.argenprop.com/oficina-en-alquiler-...</td>\n",
              "      <td>La Voz del Interior 8800</td>\n",
              "      <td>525000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>144.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Excelente</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9299</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>Oroño al 5600</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>A Estrenar</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9306</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>3 de Febrero  al 1700</td>\n",
              "      <td>180000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>55</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9309</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>Zeballos 700</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>53</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9320</th>\n",
              "      <td>https://www.argenprop.com/cochera-en-alquiler-...</td>\n",
              "      <td>ESPAÑA 1300 COCH SUB 05</td>\n",
              "      <td>23000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9321</th>\n",
              "      <td>https://www.argenprop.com/local-en-alquiler-en...</td>\n",
              "      <td>Av. Uriburu 2000</td>\n",
              "      <td>180000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>30</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1346 rows × 12 columns</p>\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
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              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 131
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#TENEMOS VARIAS FILAS QUE CONTIENEN LA PALABRA 'local|oficina|cochera-en-alquiler|negocio', PROCEDEMOS A ELIMINARLAS.\n",
        "\n",
        "nuevo_df = nuevo_df.drop(nuevo_df[nuevo_df['URL'].str.contains('local|oficina|cochera-en-alquiler|negocio|galpon|comercio')].index)\n",
        "\n",
        "nuevo_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k8ogT3vze8Mr",
        "outputId": "ee77c2c3-fc7a-4b98-d409-94106d8b1ae5"
      },
      "execution_count": 132,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7832 entries, 0 to 9323\n",
            "Data columns (total 12 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 7832 non-null   object \n",
            " 1   Ubicación           7832 non-null   object \n",
            " 2   Precio ARS          1533 non-null   float64\n",
            " 3   Precio USD          6106 non-null   float64\n",
            " 4   Sup. cubierta [m²]  7050 non-null   float64\n",
            " 5   Dormitorios         7014 non-null   object \n",
            " 6   Baños               7425 non-null   float64\n",
            " 7   Ambientes           7272 non-null   object \n",
            " 8   Antigüedad [años]   2814 non-null   object \n",
            " 9   Antiguedad [años]   4003 non-null   float64\n",
            " 10  Estado              2210 non-null   object \n",
            " 11  Toilettes           467 non-null    float64\n",
            "dtypes: float64(6), object(6)\n",
            "memory usage: 795.4+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#SEGUIDAMENTE PROCEDEMOS A ELIMINAR LAS FILAS QUE SU PRECIO EN PESOS NO ALCANZAN LOS 20.000\n",
        "menos20000 = nuevo_df.loc[nuevo_df['Precio ARS'] < 20000]\n",
        "menos20000.info()\n",
        "\n",
        "#ELIMINAMOS\n",
        "nuevo_df = nuevo_df.drop(nuevo_df[nuevo_df['Precio ARS'] < 20000].index)\n",
        "\n",
        "nuevo_df.info()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rV_wWYUWe8Pg",
        "outputId": "38b18fb5-e09d-47fe-b1f0-1f8c06a0106a"
      },
      "execution_count": 133,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 18 entries, 268 to 8675\n",
            "Data columns (total 12 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 18 non-null     object \n",
            " 1   Ubicación           18 non-null     object \n",
            " 2   Precio ARS          18 non-null     float64\n",
            " 3   Precio USD          0 non-null      float64\n",
            " 4   Sup. cubierta [m²]  16 non-null     float64\n",
            " 5   Dormitorios         15 non-null     object \n",
            " 6   Baños               16 non-null     float64\n",
            " 7   Ambientes           18 non-null     object \n",
            " 8   Antigüedad [años]   7 non-null      object \n",
            " 9   Antiguedad [años]   5 non-null      float64\n",
            " 10  Estado              7 non-null      object \n",
            " 11  Toilettes           1 non-null      float64\n",
            "dtypes: float64(6), object(6)\n",
            "memory usage: 1.8+ KB\n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7814 entries, 0 to 9323\n",
            "Data columns (total 12 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 7814 non-null   object \n",
            " 1   Ubicación           7814 non-null   object \n",
            " 2   Precio ARS          1515 non-null   float64\n",
            " 3   Precio USD          6106 non-null   float64\n",
            " 4   Sup. cubierta [m²]  7034 non-null   float64\n",
            " 5   Dormitorios         6999 non-null   object \n",
            " 6   Baños               7409 non-null   float64\n",
            " 7   Ambientes           7254 non-null   object \n",
            " 8   Antigüedad [años]   2807 non-null   object \n",
            " 9   Antiguedad [años]   3998 non-null   float64\n",
            " 10  Estado              2203 non-null   object \n",
            " 11  Toilettes           466 non-null    float64\n",
            "dtypes: float64(6), object(6)\n",
            "memory usage: 793.6+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#CREAMOS UN DATAFRAME DE RESPALDO CON LAS PUBLICACIONES SIN PRECIO\n",
        "df_vacias = nuevo_df.loc[(nuevo_df['Precio ARS'].isnull()) & (nuevo_df['Precio USD'].isnull())]\n",
        "\n",
        "df_vacias"
      ],
      "metadata": {
        "id": "a4AXW8O-oIxd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 894
        },
        "outputId": "22130c56-5612-47f9-f032-03d815656eec"
      },
      "execution_count": 134,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    URL  \\\n",
              "25    https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "74    https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "307   https://www.argenprop.com/departamento-en-alqu...   \n",
              "342   https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "405   https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "...                                                 ...   \n",
              "9151  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "9173  https://www.argenprop.com/departamento-en-alqu...   \n",
              "9177  https://www.argenprop.com/departamento-en-alqu...   \n",
              "9207  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "9300  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "\n",
              "                                           Ubicación  Precio ARS  Precio USD  \\\n",
              "25                                  Bvd Oroño 35 bis         NaN         NaN   \n",
              "74                               Consultar dirección         NaN         NaN   \n",
              "307                           Castaños, Nordelta 100         NaN         NaN   \n",
              "342                             Martin Fierro al 900         NaN         NaN   \n",
              "405                                    Junin al 1600         NaN         NaN   \n",
              "...                                              ...         ...         ...   \n",
              "9151                                     French 8500         NaN         NaN   \n",
              "9173                  Marta Garrone 2100 - 1º Piso B         NaN         NaN   \n",
              "9177              Marta Garrone 2100 - Planta Baja B         NaN         NaN   \n",
              "9207             Rio cuarto e/ Pilcomayo y Rio Dulce         NaN         NaN   \n",
              "9300  Av. Real 9191 - Rosario Golf Country Club '193         NaN         NaN   \n",
              "\n",
              "      Sup. cubierta [m²] Dormitorios  Baños Ambientes Antigüedad [años]  \\\n",
              "25                 430.0           6    4.0        10                90   \n",
              "74                   NaN           4    3.0         5               NaN   \n",
              "307                 96.0           3    2.0         5               NaN   \n",
              "342                  NaN           3    1.0         5                40   \n",
              "405                160.0           2    1.0         6                35   \n",
              "...                  ...         ...    ...       ...               ...   \n",
              "9151               300.0           4    3.0        11                30   \n",
              "9173                55.0           2    1.0         3               NaN   \n",
              "9177                55.0           1    1.0         2               NaN   \n",
              "9207                 NaN           1    1.0         2        A Estrenar   \n",
              "9300               540.0           4    6.0         8                 5   \n",
              "\n",
              "      Antiguedad [años]     Estado  Toilettes  \n",
              "25                  NaN        NaN        NaN  \n",
              "74                  NaN  Excelente        NaN  \n",
              "307                 0.0  Muy Bueno        NaN  \n",
              "342                 NaN        NaN        NaN  \n",
              "405                 NaN        NaN        NaN  \n",
              "...                 ...        ...        ...  \n",
              "9151                NaN  Muy Bueno        NaN  \n",
              "9173                0.0        NaN        NaN  \n",
              "9177                0.0        NaN        NaN  \n",
              "9207                NaN        NaN        NaN  \n",
              "9300                NaN        NaN        NaN  \n",
              "\n",
              "[193 rows x 12 columns]"
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              "      <th></th>\n",
              "      <th>URL</th>\n",
              "      <th>Ubicación</th>\n",
              "      <th>Precio ARS</th>\n",
              "      <th>Precio USD</th>\n",
              "      <th>Sup. cubierta [m²]</th>\n",
              "      <th>Dormitorios</th>\n",
              "      <th>Baños</th>\n",
              "      <th>Ambientes</th>\n",
              "      <th>Antigüedad [años]</th>\n",
              "      <th>Antiguedad [años]</th>\n",
              "      <th>Estado</th>\n",
              "      <th>Toilettes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Bvd Oroño 35 bis</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>430.0</td>\n",
              "      <td>6</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10</td>\n",
              "      <td>90</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Consultar dirección</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Excelente</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>307</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Castaños, Nordelta 100</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>96.0</td>\n",
              "      <td>3</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Muy Bueno</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>342</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Martin Fierro al 900</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>5</td>\n",
              "      <td>40</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>405</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Junin al 1600</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>160.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>6</td>\n",
              "      <td>35</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9151</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>French 8500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>300.0</td>\n",
              "      <td>4</td>\n",
              "      <td>3.0</td>\n",
              "      <td>11</td>\n",
              "      <td>30</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Muy Bueno</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9173</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Marta Garrone 2100 - 1º Piso B</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>55.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9177</th>\n",
              "      <td>https://www.argenprop.com/departamento-en-alqu...</td>\n",
              "      <td>Marta Garrone 2100 - Planta Baja B</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>55.0</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9207</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Rio cuarto e/ Pilcomayo y Rio Dulce</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2</td>\n",
              "      <td>A Estrenar</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9300</th>\n",
              "      <td>https://www.argenprop.com/casa-en-alquiler-en-...</td>\n",
              "      <td>Av. Real 9191 - Rosario Golf Country Club '193</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>540.0</td>\n",
              "      <td>4</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8</td>\n",
              "      <td>5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>193 rows × 12 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d8f6ac9f-ccdf-4ead-91cc-e0369b6f3e21')\"\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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-d8f6ac9f-ccdf-4ead-91cc-e0369b6f3e21 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-d8f6ac9f-ccdf-4ead-91cc-e0369b6f3e21');\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",
              "\n",
              "\n",
              "<div id=\"df-6cabc074-c0db-46db-8a0b-1a11c9bba9af\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6cabc074-c0db-46db-8a0b-1a11c9bba9af')\"\n",
              "            title=\"Suggest charts.\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6cabc074-c0db-46db-8a0b-1a11c9bba9af button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 134
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#ELIMINAMOS LAS PUBLICACIONES SIN PRECIO DEL DATAFRAME nuevo_df\n",
        "\n",
        "nuevo_df = nuevo_df.drop(nuevo_df.loc[(nuevo_df['Precio ARS'].isnull()) & (nuevo_df['Precio USD'].isnull())].index)\n",
        "\n",
        "\n",
        "nuevo_df.info()"
      ],
      "metadata": {
        "id": "bsg0atq1r-2B",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "66da2f05-86ab-47c9-b1f6-115914e60e1e"
      },
      "execution_count": 135,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7621 entries, 0 to 9323\n",
            "Data columns (total 12 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 7621 non-null   object \n",
            " 1   Ubicación           7621 non-null   object \n",
            " 2   Precio ARS          1515 non-null   float64\n",
            " 3   Precio USD          6106 non-null   float64\n",
            " 4   Sup. cubierta [m²]  6906 non-null   float64\n",
            " 5   Dormitorios         6847 non-null   object \n",
            " 6   Baños               7252 non-null   float64\n",
            " 7   Ambientes           7112 non-null   object \n",
            " 8   Antigüedad [años]   2715 non-null   object \n",
            " 9   Antiguedad [años]   3955 non-null   float64\n",
            " 10  Estado              2137 non-null   object \n",
            " 11  Toilettes           460 non-null    float64\n",
            "dtypes: float64(6), object(6)\n",
            "memory usage: 774.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# CONVERTIMOS LAS COLUMNAS VALUADAS EN PESOS A SU PRECIO EN DOLAR OFICIAL DEL DIA DE LA FECHA.\n",
        "dolarhoy = 365\n",
        "nuevo_df['Precio USD'].fillna(df['Precio ARS'] / dolarhoy, inplace=True)\n",
        "nuevo_df.info()\n",
        "# TENEMOS TODAS LAS PUBLICACIONES CON SU VALOR DEL ALQUILER COTIZADO EN DOLAR BLUE.\n"
      ],
      "metadata": {
        "id": "wspWEG4nr-5j",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dcc69686-89e5-4972-dedc-b6c015725bcf"
      },
      "execution_count": 136,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7621 entries, 0 to 9323\n",
            "Data columns (total 12 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 7621 non-null   object \n",
            " 1   Ubicación           7621 non-null   object \n",
            " 2   Precio ARS          1515 non-null   float64\n",
            " 3   Precio USD          7621 non-null   float64\n",
            " 4   Sup. cubierta [m²]  6906 non-null   float64\n",
            " 5   Dormitorios         6847 non-null   object \n",
            " 6   Baños               7252 non-null   float64\n",
            " 7   Ambientes           7112 non-null   object \n",
            " 8   Antigüedad [años]   2715 non-null   object \n",
            " 9   Antiguedad [años]   3955 non-null   float64\n",
            " 10  Estado              2137 non-null   object \n",
            " 11  Toilettes           460 non-null    float64\n",
            "dtypes: float64(6), object(6)\n",
            "memory usage: 774.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#EN LA COLUMNA DORMITORIOS OBSERVAMOS QUE ES DE TIPO OBJECT, Y QUE ADEMAS ENTRE SUS VALORES SE ENCUENTRA EL valor \"Monoambiente\"\n",
        "# DEBEMOS CAMBIAR EL STRING POR  '1'.\n",
        "# LUEGO CAMBIAMOS A FLOAT LOS VALORES CONTENIDOS EN LA COLUMNA\n",
        "nuevo_df['Dormitorios'] = nuevo_df['Dormitorios'].replace('Monoambiente', \"1\")\n",
        "nuevo_df['Dormitorios'] = nuevo_df['Dormitorios'].astype(float)\n",
        "nuevo_df.info()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KOi4a50_DJpJ",
        "outputId": "c512319a-f6ea-4234-ad1b-4005253e919f"
      },
      "execution_count": 137,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7621 entries, 0 to 9323\n",
            "Data columns (total 12 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 7621 non-null   object \n",
            " 1   Ubicación           7621 non-null   object \n",
            " 2   Precio ARS          1515 non-null   float64\n",
            " 3   Precio USD          7621 non-null   float64\n",
            " 4   Sup. cubierta [m²]  6906 non-null   float64\n",
            " 5   Dormitorios         6847 non-null   float64\n",
            " 6   Baños               7252 non-null   float64\n",
            " 7   Ambientes           7112 non-null   object \n",
            " 8   Antigüedad [años]   2715 non-null   object \n",
            " 9   Antiguedad [años]   3955 non-null   float64\n",
            " 10  Estado              2137 non-null   object \n",
            " 11  Toilettes           460 non-null    float64\n",
            "dtypes: float64(7), object(5)\n",
            "memory usage: 774.0+ KB\n"
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    {
      "cell_type": "code",
      "source": [
        "#OBSERVAMOS LOS TIPOS DE VALORES CONTENIDOS EN LA COLUMNA \"Ambientes\", EN EL OBSERVAMOS QUE EXISTE UNA FILA CON EL VALOR 'ambientes ambientes'\n",
        "nuevo_df[\"Ambientes\"].value_counts()"
      ],
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        "id": "B7hQGkP0DJsa",
        "outputId": "c77324d4-c93d-41fa-ee5f-b1e71f64986f"
      },
      "execution_count": 138,
      "outputs": [
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          "data": {
            "text/plain": [
              "4                      1583\n",
              "2                      1392\n",
              "3                      1228\n",
              "5                      1078\n",
              "0                       652\n",
              "6                       570\n",
              "7                       273\n",
              "8                       180\n",
              "10                       55\n",
              "9                        47\n",
              "12                       18\n",
              "1                        11\n",
              "13                        5\n",
              "15                        5\n",
              "11                        4\n",
              "17                        4\n",
              "18                        2\n",
              "20                        2\n",
              "56                        1\n",
              "ambientes ambientes       1\n",
              "14                        1\n",
              "Name: Ambientes, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 138
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        "nuevo_df.loc[nuevo_df[\"Ambientes\"] == 'ambientes ambientes']"
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              "                                                    URL  \\\n",
              "4820  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "\n",
              "                              Ubicación  Precio ARS  Precio USD  \\\n",
              "4820  Blvd. de Todos los Santos al 6000         NaN      1200.0   \n",
              "\n",
              "      Sup. cubierta [m²]  Dormitorios  Baños            Ambientes  \\\n",
              "4820               220.0          NaN    2.0  ambientes ambientes   \n",
              "\n",
              "     Antigüedad [años]  Antiguedad [años] Estado  Toilettes  \n",
              "4820                10                NaN    NaN        NaN  "
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    {
      "cell_type": "code",
      "source": [
        "#ELIMINAMOS\n",
        "nuevo_df = nuevo_df.drop(nuevo_df[nuevo_df[\"Ambientes\"] == 'ambientes ambientes'].index)\n",
        "#CONVERTIMOS LA COLUMNA A FLOAT:\n",
        "\n",
        "nuevo_df[\"Ambientes\"] = nuevo_df[\"Ambientes\"].astype(float)"
      ],
      "metadata": {
        "id": "Anuaa1yUdaOK"
      },
      "execution_count": 140,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nuevo_df.loc[nuevo_df[\"Ambientes\"]>20]"
      ],
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              "                                                    URL  \\\n",
              "4759  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "\n",
              "                       Ubicación  Precio ARS  Precio USD  Sup. cubierta [m²]  \\\n",
              "4759  SAN GABRIEL VILLANUEVA 100         NaN      1500.0               170.0   \n",
              "\n",
              "      Dormitorios  Baños  Ambientes Antigüedad [años]  Antiguedad [años]  \\\n",
              "4759          4.0    4.0       56.0                 5                NaN   \n",
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              "                                                    [key], {});\n",
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              "\n",
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    },
    {
      "cell_type": "code",
      "source": [
        "# CON RESPECTO A LA COLUMNA \"Antiguedad[Años]\" LA COMBINAMOS CON LA DE NOMBRE SIMILAR, RELLENANDO LOS\n",
        "# VALORES VACIOS DE UNA CON LOS DE LA OTRA COLUMNA SI ES QUE TIENE VALORES\n",
        "nuevo_df['Antiguedad [años]'].fillna(df['Antigüedad [años]'], inplace=True)\n",
        "nuevo_df['Antiguedad [años]'].value_counts()"
      ],
      "metadata": {
        "id": "Ej1USIEZcbRb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d89fbf8d-1923-4019-ab6c-163b8866b012"
      },
      "execution_count": 142,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0           922\n",
              "A Estrenar    729\n",
              "40.0          285\n",
              "10.0          276\n",
              "10            209\n",
              "             ... \n",
              "31.0            1\n",
              "27              1\n",
              "2008            1\n",
              "2015            1\n",
              "1970.0          1\n",
              "Name: Antiguedad [años], Length: 175, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 142
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#OBSERVAMOS QUE EN LUGAR DE ANTIGUEDAD TENEMOS EL AÑO DE CREACION, Y ADEMAS QUE HAY 756 FILAS CON EL VALOR \"A Estrenar\"\n",
        "#PRIMERO REEMPLAZAMOS EL VALOR \"A estrenar\" por \"0\"\n",
        "#ELIMINAMOS LA COLUMNA 'Antigüedad [años]'\n",
        "nuevo_df['Antiguedad [años]'] = nuevo_df['Antiguedad [años]'].replace('A Estrenar', \"0\")\n",
        "nuevo_df['Antiguedad [años]'] = nuevo_df['Antiguedad [años]'].astype(float)\n",
        "nuevo_df= nuevo_df.drop('Antigüedad [años]', axis=1)"
      ],
      "metadata": {
        "id": "MdmAi90FcbwJ"
      },
      "execution_count": 143,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nuevo_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p14x9FQshbRs",
        "outputId": "7f36d8ba-feed-4bb7-be71-81d732804af8"
      },
      "execution_count": 144,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7620 entries, 0 to 9323\n",
            "Data columns (total 11 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 7620 non-null   object \n",
            " 1   Ubicación           7620 non-null   object \n",
            " 2   Precio ARS          1515 non-null   float64\n",
            " 3   Precio USD          7620 non-null   float64\n",
            " 4   Sup. cubierta [m²]  6905 non-null   float64\n",
            " 5   Dormitorios         6847 non-null   float64\n",
            " 6   Baños               7251 non-null   float64\n",
            " 7   Ambientes           7111 non-null   float64\n",
            " 8   Antiguedad [años]   6669 non-null   float64\n",
            " 9   Estado              2137 non-null   object \n",
            " 10  Toilettes           460 non-null    float64\n",
            "dtypes: float64(8), object(3)\n",
            "memory usage: 714.4+ KB\n"
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#COMO MUCHOS VALORES TIENEN EL AÑO DE CREACION, VAMOS A CORREGIR ESOS VALORES, FILTRANDO CON LOS REGISTREN UN VALOR MAYOR A 500\n",
        "#LUEGO RESTAMOS EL VALOR DE LA FILA POR EL AÑO ACTUAL (2023)\n",
        "# Filtrar los valores mayores a 500\n",
        "\n",
        "nuevo_df['Antiguedad [años]'] = nuevo_df['Antiguedad [años]'].apply(lambda x: 2023 - x if x > 400 else x)\n",
        "nuevo_df.info()\n"
      ],
      "metadata": {
        "id": "ZOMlsdQLda2u",
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          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d2f7c838-75f0-45c7-fd89-686d9e733fe9"
      },
      "execution_count": 145,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7620 entries, 0 to 9323\n",
            "Data columns (total 11 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
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            " 1   Ubicación           7620 non-null   object \n",
            " 2   Precio ARS          1515 non-null   float64\n",
            " 3   Precio USD          7620 non-null   float64\n",
            " 4   Sup. cubierta [m²]  6905 non-null   float64\n",
            " 5   Dormitorios         6847 non-null   float64\n",
            " 6   Baños               7251 non-null   float64\n",
            " 7   Ambientes           7111 non-null   float64\n",
            " 8   Antiguedad [años]   6669 non-null   float64\n",
            " 9   Estado              2137 non-null   object \n",
            " 10  Toilettes           460 non-null    float64\n",
            "dtypes: float64(8), object(3)\n",
            "memory usage: 714.4+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#JUNTO LAS TABLAS BAÑOS Y TOILETTES\n",
        "nuevo_df['Baños'].fillna(df['Toilettes'], inplace=True)\n",
        "nuevo_df= nuevo_df.drop('Toilettes', axis=1)"
      ],
      "metadata": {
        "id": "rkZQH3B1x9h6"
      },
      "execution_count": 146,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Completo los valores vacios en baños, con 1 baño.\n",
        "nuevo_df['Baños'].fillna(1, inplace=True)\n",
        "nuevo_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "md10ETfY0dte",
        "outputId": "d6fdd46a-ff27-4888-883e-0db365a22331"
      },
      "execution_count": 147,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7620 entries, 0 to 9323\n",
            "Data columns (total 10 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 7620 non-null   object \n",
            " 1   Ubicación           7620 non-null   object \n",
            " 2   Precio ARS          1515 non-null   float64\n",
            " 3   Precio USD          7620 non-null   float64\n",
            " 4   Sup. cubierta [m²]  6905 non-null   float64\n",
            " 5   Dormitorios         6847 non-null   float64\n",
            " 6   Baños               7620 non-null   float64\n",
            " 7   Ambientes           7111 non-null   float64\n",
            " 8   Antiguedad [años]   6669 non-null   float64\n",
            " 9   Estado              2137 non-null   object \n",
            "dtypes: float64(7), object(3)\n",
            "memory usage: 654.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#REVISO LOS VALORES DE LA COLUMNA\n",
        "nuevo_df['Baños'].value_counts()"
      ],
      "metadata": {
        "id": "pEtlcF6vcb0z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4329c3cf-3a16-463a-f40f-174c1779d06e"
      },
      "execution_count": 148,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.0     3018\n",
              "2.0     1928\n",
              "3.0     1432\n",
              "4.0      726\n",
              "5.0      306\n",
              "6.0      126\n",
              "7.0       50\n",
              "8.0       22\n",
              "9.0        9\n",
              "10.0       2\n",
              "13.0       1\n",
              "Name: Baños, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 148
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#REVISO LAS FILAS CON MAS DE 8 baños, observamos que los valores elevados corresponden a casas por ende los dejamos.\n",
        "nuevo_df.loc[nuevo_df[\"Baños\"]>8]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 703
        },
        "id": "w7M4p3ewx9k2",
        "outputId": "7a070235-2162-4712-b394-2d5cac443518"
      },
      "execution_count": 149,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    URL  \\\n",
              "2362  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "2623  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "2654  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "2865  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "2869  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "3387  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "5091  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "6030  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "6331  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "6766  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "8119  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "8163  https://www.argenprop.com/casa-en-alquiler-en-...   \n",
              "\n",
              "                              Ubicación  Precio ARS    Precio USD  \\\n",
              "2362    Ruta 88 Otamendi, Mar del Plata         NaN   1200.000000   \n",
              "2623                   Cabrera  al 5100         NaN   5000.000000   \n",
              "2654                   Cabrera  al 5100         NaN   5000.000000   \n",
              "2865                   Cabrera  al 5100         NaN   5000.000000   \n",
              "2869                   Cabrera  al 5100         NaN   5000.000000   \n",
              "3387                Mariscal Ramón  100         NaN   9800.000000   \n",
              "5091                  Panamericana Km46         NaN   3500.000000   \n",
              "6030    Ruta 88 Otamendi, Mar del Plata         NaN   1200.000000   \n",
              "6331                Mariscal Ramón  100         NaN   9800.000000   \n",
              "6766                    AYRES DE PIALAR         NaN   4200.000000   \n",
              "8119  Rivadavia al 300 esquina Belgrano         NaN  11500.000000   \n",
              "8163          Av. Del Libertador al 600    600000.0   1643.835616   \n",
              "\n",
              "      Sup. cubierta [m²]  Dormitorios  Baños  Ambientes  Antiguedad [años]  \\\n",
              "2362                 1.0          9.0   10.0       13.0               50.0   \n",
              "2623               305.0          7.0    9.0       10.0               10.0   \n",
              "2654               305.0          7.0    9.0       10.0               10.0   \n",
              "2865               305.0          7.0    9.0       10.0               10.0   \n",
              "2869               305.0          7.0    9.0       10.0               10.0   \n",
              "3387               500.0          4.0    9.0        5.0                NaN   \n",
              "5091               823.0          6.0    9.0        NaN               15.0   \n",
              "6030                 1.0          9.0   10.0       13.0               50.0   \n",
              "6331               500.0          4.0    9.0        5.0                NaN   \n",
              "6766               610.0          6.0    9.0        7.0               10.0   \n",
              "8119                 1.0          NaN   13.0        NaN               10.0   \n",
              "8163               350.0          9.0    9.0       12.0               50.0   \n",
              "\n",
              "     Estado  \n",
              "2362    NaN  \n",
              "2623    NaN  \n",
              "2654    NaN  \n",
              "2865    NaN  \n",
              "2869    NaN  \n",
              "3387    NaN  \n",
              "5091    NaN  \n",
              "6030    NaN  \n",
              "6331    NaN  \n",
              "6766    NaN  \n",
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              "      <th>2362</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>9800.000000</td>\n",
              "      <td>500.0</td>\n",
              "      <td>4.0</td>\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-ca703020-0383-4637-b058-7286a6db9f24 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 149
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nuevo_df[\"Estado\"].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5WMf6fhpx9oN",
        "outputId": "f66d25a9-f612-4640-af15-52b10f2ffd40"
      },
      "execution_count": 150,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Excelente        1275\n",
              "Muy Bueno         677\n",
              "Bueno             175\n",
              "A Refaccionar       6\n",
              "Regular             4\n",
              "Name: Estado, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 150
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nuevo_df['Estado'].fillna(\"Bueno\", inplace=True)\n",
        "nuevo_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nol3rJUYx9vk",
        "outputId": "f012dec9-86bd-4cea-d8cb-25eab58039fd"
      },
      "execution_count": 151,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7620 entries, 0 to 9323\n",
            "Data columns (total 10 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   URL                 7620 non-null   object \n",
            " 1   Ubicación           7620 non-null   object \n",
            " 2   Precio ARS          1515 non-null   float64\n",
            " 3   Precio USD          7620 non-null   float64\n",
            " 4   Sup. cubierta [m²]  6905 non-null   float64\n",
            " 5   Dormitorios         6847 non-null   float64\n",
            " 6   Baños               7620 non-null   float64\n",
            " 7   Ambientes           7111 non-null   float64\n",
            " 8   Antiguedad [años]   6669 non-null   float64\n",
            " 9   Estado              7620 non-null   object \n",
            "dtypes: float64(7), object(3)\n",
            "memory usage: 654.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Convertir la columna 'Precios Usd' a enteros usando .loc\n",
        "nuevo_df.loc[:, 'Precio USD'] = nuevo_df['Precio USD'].astype(int)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7a--ewDKH4eK",
        "outputId": "e2b8acd5-6fa7-4885-de6c-0c1086f3f1ce"
      },
      "execution_count": 152,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-152-a9c3322eca12>:2: DeprecationWarning: In a future version, `df.iloc[:, i] = newvals` will attempt to set the values inplace instead of always setting a new array. To retain the old behavior, use either `df[df.columns[i]] = newvals` or, if columns are non-unique, `df.isetitem(i, newvals)`\n",
            "  nuevo_df.loc[:, 'Precio USD'] = nuevo_df['Precio USD'].astype(int)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#OBSERVAMOS LOS VALORES DE LA COLUMNA\n",
        "unique_values = nuevo_df['Precio USD'].unique()\n",
        "\n",
        "print(unique_values)\n"
      ],
      "metadata": {
        "id": "BlFBN-G9KYqk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "723c94b4-e2a0-4534-d02c-0f5fb6ec4b54"
      },
      "execution_count": 153,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[   1400    1000    1100     250    4000     420    5000    4500    2000\n",
            "    1643     500     794     650     600    2800    3500     700    1700\n",
            "     821     684     900    1041    1300     800    1200    6500     480\n",
            "    2100   13000    1800    2200     120    1095   10000    1208    1500\n",
            "    1600     850    7500     547    1232    6000    1378     356    4200\n",
            "     493    2500    3000     540    1250    7000     958   15000     350\n",
            "     602     575    2684     630     550    4800    1900     950     876\n",
            "     450     750     460     400    3700     657     840     438    8000\n",
            "     410    2700    2300     986    2400     153     320     370     465\n",
            "    1150    2900    1178    3300    3200    3800     520    1750    3100\n",
            "     680    1950    5500     490    1850     990     383    1534    1980\n",
            "    8500    1369    1350     652    3250    3600     150    2465     301\n",
            "    2191    1401    1917    2600     730    1890     739    1760    3900\n",
            "     670     760     767  350000     380    4300   11500  304414    5499\n",
            "     654     890    1450    1972     712     690    2850    2054     390\n",
            "    1068    1342    1479    2950    4400    5800    2328     699     219\n",
            "     849     430    9000    1050     328     904     232     300     315\n",
            "     931     561     260     452    4700    1424     123    8400    1438\n",
            "     205     589    9800     156    1287   12000     506    3400     197\n",
            "     980     740   16000     221    2750     340   11000     136    2438\n",
            "     246    5900   14000    2250     755    2120    3287    1190    2450\n",
            "    1616    6800     405   35000    1780    4600    1990    1460     616\n",
            "     391     273     835    1161     671    1356     753     620     770\n",
            "     216    1821     191     880    1506   17000     842     287     534\n",
            "     726    9500    7600     145    1013     580     158     202  115000\n",
            "     790     816     178     164    2602     542    6200    9900   10500\n",
            "     808    4109    7800    1301     780    1399   18000    2185    2410\n",
            "     470     810     545    3325     256     330    2330    1753      76\n",
            "     960    1650     268     424     397    2739    1863     624    1380\n",
            "     479     271      95    7900     425    2587     224    5200    5100\n",
            "    1602    3480  119400     399     570     640     161     265     280\n",
            "    1390     195   20000     369     999    1499     361     720    4900\n",
            "    1315     698   90000     200    9700     643    3479    5400    1790\n",
            "    1175      82    3750     440     342     230     213    3698     169\n",
            "      86  210000     590     270    1599    2499    8600    1480    3150\n",
            "     201    2350 1100000    1027    7700     360     435     530    2050\n",
            "    1870  148000     525    1440    1320     186    1430     323    1220\n",
            "    1999    1210     284     572  164874     279     239      60     227\n",
            "     210     252     243     175]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ELIMINAMOS LAS FILAS CON PRECIO USD MAYOR A 15.000...\n",
        "nuevo_df = nuevo_df.drop(nuevo_df[nuevo_df['Precio USD'] > 15000].index)"
      ],
      "metadata": {
        "id": "XI7YMWgIIc4f"
      },
      "execution_count": 154,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# ELIMINAMOS LAS FILAS CON Sup Cubierta MENOR A 5\n",
        "nuevo_df = nuevo_df.drop(nuevo_df[nuevo_df['Sup. cubierta [m²]'] < 5].index)"
      ],
      "metadata": {
        "id": "Eyd_dM3tVeyZ"
      },
      "execution_count": 155,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#COMPLETAMOS DATOS NULOS"
      ],
      "metadata": {
        "id": "b-qLbQpmf1d3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#ANTES DE COMPLETAR LOS DATOS NULOS PRIMERO OBSERVAREMOS LOS VALORES ESTADISTICOS DEL DATASET\n",
        "nuevo_df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "g2ckl6WFJFB-",
        "outputId": "096ed187-c935-4d68-e320-e052aba4b868"
      },
      "execution_count": 156,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Precio ARS    Precio USD  Sup. cubierta [m²]  Dormitorios  \\\n",
              "count  1.499000e+03   7553.000000         6847.000000  6790.000000   \n",
              "mean   2.607754e+05   1904.685820          166.817292     2.667452   \n",
              "std    1.973163e+05   1964.090456          143.992817     1.316534   \n",
              "min    2.200000e+04     60.000000            6.000000     1.000000   \n",
              "25%    1.300000e+05    684.000000           55.000000     2.000000   \n",
              "50%    2.000000e+05   1232.000000          122.000000     3.000000   \n",
              "75%    3.000000e+05   2400.000000          232.000000     4.000000   \n",
              "max    1.500000e+06  15000.000000          996.000000    18.000000   \n",
              "\n",
              "            Baños    Ambientes  Antiguedad [años]  \n",
              "count  7553.00000  7059.000000        6614.000000  \n",
              "mean      2.21978     3.719649          17.731932  \n",
              "std       1.35302     2.222728          20.073469  \n",
              "min       1.00000     0.000000          -1.000000  \n",
              "25%       1.00000     2.000000           0.000000  \n",
              "50%       2.00000     4.000000          10.000000  \n",
              "75%       3.00000     5.000000          30.000000  \n",
              "max       9.00000    56.000000         150.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a7e6ace4-92e9-4581-aed0-b85266705e1f\" 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>Precio ARS</th>\n",
              "      <th>Precio USD</th>\n",
              "      <th>Sup. cubierta [m²]</th>\n",
              "      <th>Dormitorios</th>\n",
              "      <th>Baños</th>\n",
              "      <th>Ambientes</th>\n",
              "      <th>Antiguedad [años]</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1.499000e+03</td>\n",
              "      <td>7553.000000</td>\n",
              "      <td>6847.000000</td>\n",
              "      <td>6790.000000</td>\n",
              "      <td>7553.00000</td>\n",
              "      <td>7059.000000</td>\n",
              "      <td>6614.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2.607754e+05</td>\n",
              "      <td>1904.685820</td>\n",
              "      <td>166.817292</td>\n",
              "      <td>2.667452</td>\n",
              "      <td>2.21978</td>\n",
              "      <td>3.719649</td>\n",
              "      <td>17.731932</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.973163e+05</td>\n",
              "      <td>1964.090456</td>\n",
              "      <td>143.992817</td>\n",
              "      <td>1.316534</td>\n",
              "      <td>1.35302</td>\n",
              "      <td>2.222728</td>\n",
              "      <td>20.073469</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>2.200000e+04</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.300000e+05</td>\n",
              "      <td>684.000000</td>\n",
              "      <td>55.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2.000000e+05</td>\n",
              "      <td>1232.000000</td>\n",
              "      <td>122.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.00000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.000000e+05</td>\n",
              "      <td>2400.000000</td>\n",
              "      <td>232.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>3.00000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>30.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.500000e+06</td>\n",
              "      <td>15000.000000</td>\n",
              "      <td>996.000000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>9.00000</td>\n",
              "      <td>56.000000</td>\n",
              "      <td>150.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a7e6ace4-92e9-4581-aed0-b85266705e1f')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-a7e6ace4-92e9-4581-aed0-b85266705e1f 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-a7e6ace4-92e9-4581-aed0-b85266705e1f');\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",
              "\n",
              "\n",
              "<div id=\"df-d879e0d5-dbf6-4cfc-b82a-0724e8acf3dc\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d879e0d5-dbf6-4cfc-b82a-0724e8acf3dc')\"\n",
              "            title=\"Suggest charts.\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d879e0d5-dbf6-4cfc-b82a-0724e8acf3dc button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 156
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#OBSERVADOS LOS DATOS SE PROCEDERA A:\n",
        "#COMPLETAR VALORES NULOS DE LA COLUMNA DORMITORIOS CON EL VALOR '2'\n",
        "nuevo_df[\"Dormitorios\"].fillna(2, inplace=True)\n",
        "\n",
        "#COMPLETAR LOS VALORES NULOS DE LA COLUMNA AMBIENTES CON EL VALOR '4'\n",
        "nuevo_df[\"Ambientes\"].fillna(4, inplace= True)\n",
        "#COMPLETAR VALORES NULOS DE LA COLUMNA Sup. cubierta [m²] CON EL VALOR '167'\n",
        "nuevo_df['Sup. cubierta [m²]'].fillna (167, inplace = True)\n",
        "\n",
        "#COMPLETAR VALORES NULOS DE LA COLUMNA Antiguedad CON EL VALOR '17'\n",
        "nuevo_df['Antiguedad [años]'].fillna (17, inplace= True)"
      ],
      "metadata": {
        "id": "2Mc0BEXmJGGF"
      },
      "execution_count": 157,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nuevo_df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "lA7Xc3_HMkKO",
        "outputId": "c743a230-39e3-4d40-96a1-63d5e00ec979"
      },
      "execution_count": 158,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Precio ARS    Precio USD  Sup. cubierta [m²]  Dormitorios  \\\n",
              "count  1.499000e+03   7553.000000         7553.000000  7553.000000   \n",
              "mean   2.607754e+05   1904.685820          166.834370     2.600026   \n",
              "std    1.973163e+05   1964.090456          137.097116     1.264360   \n",
              "min    2.200000e+04     60.000000            6.000000     1.000000   \n",
              "25%    1.300000e+05    684.000000           60.000000     2.000000   \n",
              "50%    2.000000e+05   1232.000000          149.000000     3.000000   \n",
              "75%    3.000000e+05   2400.000000          220.000000     3.000000   \n",
              "max    1.500000e+06  15000.000000          996.000000    18.000000   \n",
              "\n",
              "            Baños    Ambientes  Antiguedad [años]  \n",
              "count  7553.00000  7553.000000        7553.000000  \n",
              "mean      2.21978     3.737985          17.640937  \n",
              "std       1.35302     2.149918          18.785666  \n",
              "min       1.00000     0.000000          -1.000000  \n",
              "25%       1.00000     2.000000           2.000000  \n",
              "50%       2.00000     4.000000          14.000000  \n",
              "75%       3.00000     5.000000          25.000000  \n",
              "max       9.00000    56.000000         150.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ead70775-dec5-4dd8-b10d-c5df510eb1b2\" 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>Precio ARS</th>\n",
              "      <th>Precio USD</th>\n",
              "      <th>Sup. cubierta [m²]</th>\n",
              "      <th>Dormitorios</th>\n",
              "      <th>Baños</th>\n",
              "      <th>Ambientes</th>\n",
              "      <th>Antiguedad [años]</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1.499000e+03</td>\n",
              "      <td>7553.000000</td>\n",
              "      <td>7553.000000</td>\n",
              "      <td>7553.000000</td>\n",
              "      <td>7553.00000</td>\n",
              "      <td>7553.000000</td>\n",
              "      <td>7553.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2.607754e+05</td>\n",
              "      <td>1904.685820</td>\n",
              "      <td>166.834370</td>\n",
              "      <td>2.600026</td>\n",
              "      <td>2.21978</td>\n",
              "      <td>3.737985</td>\n",
              "      <td>17.640937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.973163e+05</td>\n",
              "      <td>1964.090456</td>\n",
              "      <td>137.097116</td>\n",
              "      <td>1.264360</td>\n",
              "      <td>1.35302</td>\n",
              "      <td>2.149918</td>\n",
              "      <td>18.785666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>2.200000e+04</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.300000e+05</td>\n",
              "      <td>684.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2.000000e+05</td>\n",
              "      <td>1232.000000</td>\n",
              "      <td>149.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.00000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>14.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.000000e+05</td>\n",
              "      <td>2400.000000</td>\n",
              "      <td>220.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.00000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.500000e+06</td>\n",
              "      <td>15000.000000</td>\n",
              "      <td>996.000000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>9.00000</td>\n",
              "      <td>56.000000</td>\n",
              "      <td>150.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ead70775-dec5-4dd8-b10d-c5df510eb1b2')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-ead70775-dec5-4dd8-b10d-c5df510eb1b2 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-ead70775-dec5-4dd8-b10d-c5df510eb1b2');\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",
              "\n",
              "\n",
              "<div id=\"df-48428f63-c30c-4d49-9c9e-d0e1041cb4de\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-48428f63-c30c-4d49-9c9e-d0e1041cb4de')\"\n",
              "            title=\"Suggest charts.\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-48428f63-c30c-4d49-9c9e-d0e1041cb4de button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 158
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# CSV PARCIAL... DESCARGA\n",
        "nuevo_df.to_csv('df_v3.csv', index=False)"
      ],
      "metadata": {
        "id": "t7x_3KyMKKzV"
      },
      "execution_count": 159,
      "outputs": []
    }
  ]
}