desafio_02.ipynb

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        "<a href=\"https://colab.research.google.com/github/barviz/inmersion-datos/blob/main/desafio_02.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "markdown",
      "source": [
        "1. **Estudiar mejor el histograma de valores, seleccionar 3 tipos de inmuebles (Refinar el gráfico: Títulos, aumentar el tamaño de labels, colores, conclusión de la información)**\n",
        "Precio del m2 por barrio y hacer el gráfico más adecuado para esta nueva variable.\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "ChtzPwTamlAS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive')"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
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      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "inmuebles = pd.read_csv('/content/drive/MyDrive/inmersion_datos/inmuebles_bogota.csv') \n",
        "inmuebles.head()"
      ],
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      "execution_count": 3,
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              "          Tipo                                 Descripcion  Habitaciones  \\\n",
              "0  Apartamento  Apartamento en venta en Zona Noroccidental             3   \n",
              "1         Casa                   Casa en venta en Castilla             4   \n",
              "2  Apartamento     Apartamento en venta en Chico Reservado             3   \n",
              "3  Apartamento             Apartamento en venta en Usaquén             3   \n",
              "4  Apartamento         Apartamento en venta en Bella Suiza             2   \n",
              "\n",
              "   Baños  Área              Barrio                                    UPZ  \\\n",
              "0      2    70  Zona Noroccidental     CHAPINERO: Pardo Rubio + Chapinero   \n",
              "1      3   170            Castilla            KENNEDY: Castilla + Bavaria   \n",
              "2      3   144     Chico Reservado     CHAPINERO: Chicó Lago + El Refugio   \n",
              "3      2   154             Usaquén                                Usaquén   \n",
              "4      3   128         Bella Suiza  USAQUÉN: Country Club + Santa Bárbara   \n",
              "\n",
              "             Valor  \n",
              "0    $ 360.000.000  \n",
              "1    $ 670.000.000  \n",
              "2  $ 1.120.000.000  \n",
              "3    $ 890.000.000  \n",
              "4    $ 970.000.000  "
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              "      <th>Tipo</th>\n",
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              "      <th>Baños</th>\n",
              "      <th>Área</th>\n",
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              "      <th>UPZ</th>\n",
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              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Zona Noroccidental</td>\n",
              "      <td>3</td>\n",
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              "      <td>70</td>\n",
              "      <td>Zona Noroccidental</td>\n",
              "      <td>CHAPINERO: Pardo Rubio + Chapinero</td>\n",
              "      <td>$ 360.000.000</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Casa</td>\n",
              "      <td>Casa en venta en Castilla</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>170</td>\n",
              "      <td>Castilla</td>\n",
              "      <td>KENNEDY: Castilla + Bavaria</td>\n",
              "      <td>$ 670.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Chico Reservado</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>144</td>\n",
              "      <td>Chico Reservado</td>\n",
              "      <td>CHAPINERO: Chicó Lago + El Refugio</td>\n",
              "      <td>$ 1.120.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Usaquén</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>154</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 890.000.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Apartamento</td>\n",
              "      <td>Apartamento en venta en Bella Suiza</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>128</td>\n",
              "      <td>Bella Suiza</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 970.000.000</td>\n",
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    {
      "cell_type": "code",
      "source": [
        "columnas = {'Área':'Area'}\n",
        "inmuebles = inmuebles.rename(columns=columnas)"
      ],
      "metadata": {
        "id": "uFS6pA9j15kW"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "valor = inmuebles.Valor.str.split(expand=True)\n",
        "inmuebles['Moneda'] = valor[0]\n",
        "inmuebles['Precio'] = valor[1]\n",
        "inmuebles.sample(3)"
      ],
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            "text/plain": [
              "             Tipo                           Descripcion  Habitaciones  Baños  \\\n",
              "1401  Apartamento  Apartamento en venta en San Patricio             3      4   \n",
              "8147         Casa             Casa en venta en Engativa             4      3   \n",
              "490   Apartamento       Apartamento en venta en Usaquén             2      2   \n",
              "\n",
              "      Área        Barrio                                    UPZ  \\\n",
              "1401   290  San Patricio  USAQUÉN: Country Club + Santa Bárbara   \n",
              "8147   109      Engativa                               Engativá   \n",
              "490     71       Usaquén                                Usaquén   \n",
              "\n",
              "                Valor Moneda         Precio  \n",
              "1401  $ 2.200.000.000      $  2.200.000.000  \n",
              "8147    $ 540.000.000      $    540.000.000  \n",
              "490     $ 476.500.000      $    476.500.000  "
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              "      <th>1401</th>\n",
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              "      <td>Apartamento en venta en San Patricio</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>290</td>\n",
              "      <td>San Patricio</td>\n",
              "      <td>USAQUÉN: Country Club + Santa Bárbara</td>\n",
              "      <td>$ 2.200.000.000</td>\n",
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              "      <th>8147</th>\n",
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              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>109</td>\n",
              "      <td>Engativa</td>\n",
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              "      <td>$ 540.000.000</td>\n",
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              "      <td>Apartamento en venta en Usaquén</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>71</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>Usaquén</td>\n",
              "      <td>$ 476.500.000</td>\n",
              "      <td>$</td>\n",
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    {
      "cell_type": "code",
      "source": [
        "inmuebles['Precio'] = inmuebles['Precio'].str.replace('.','',regex=True)"
      ],
      "metadata": {
        "id": "NLoQTKL7yio5"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles.info()"
      ],
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      "execution_count": 10,
      "outputs": [
        {
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9520 entries, 0 to 9519\n",
            "Data columns (total 8 columns):\n",
            " #   Column        Non-Null Count  Dtype \n",
            "---  ------        --------------  ----- \n",
            " 0   Tipo          9520 non-null   object\n",
            " 1   Descripcion   9520 non-null   object\n",
            " 2   Habitaciones  9520 non-null   int64 \n",
            " 3   Baños         9520 non-null   int64 \n",
            " 4   Área          9520 non-null   int64 \n",
            " 5   Barrio        9520 non-null   object\n",
            " 6   UPZ           9478 non-null   object\n",
            " 7   Valor         9520 non-null   object\n",
            "dtypes: int64(3), object(5)\n",
            "memory usage: 595.1+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "dtAeVPrAmbeJ"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles['Precio_Millon'] = inmuebles.Precio.astype('float')/1000000\n",
        "inmuebles.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "blKmhLvexw5l",
        "outputId": "c9e0186f-f6f7-423a-b4a3-965332812b65"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9520 entries, 0 to 9519\n",
            "Data columns (total 11 columns):\n",
            " #   Column         Non-Null Count  Dtype  \n",
            "---  ------         --------------  -----  \n",
            " 0   Tipo           9520 non-null   object \n",
            " 1   Descripcion    9520 non-null   object \n",
            " 2   Habitaciones   9520 non-null   int64  \n",
            " 3   Baños          9520 non-null   int64  \n",
            " 4   Área           9520 non-null   int64  \n",
            " 5   Barrio         9520 non-null   object \n",
            " 6   UPZ            9478 non-null   object \n",
            " 7   Valor          9520 non-null   object \n",
            " 8   Moneda         9520 non-null   object \n",
            " 9   Precio         9520 non-null   object \n",
            " 10  Precio_Millon  9520 non-null   float64\n",
            "dtypes: float64(1), int64(3), object(7)\n",
            "memory usage: 818.2+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles['Tipo'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i0uQtNW8zM-w",
        "outputId": "24acd2a1-5317-4398-f789-60141d1a2082"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Apartamento            7327\n",
              "Casa                   2043\n",
              "Oficina/Consultorio      60\n",
              "Local                    38\n",
              "Edificio                 22\n",
              "Bodega                   13\n",
              "Finca                    11\n",
              "Lote                      6\n",
              "Name: Tipo, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles_filtrados = inmuebles.query(\"Tipo in ['Casa', 'Apartamento', 'Oficina/Consultorio']\")\n",
        "plt.figure(figsize=(10,6))\n",
        "grafica = sns.histplot(data=inmuebles_filtrados, x='Precio_Millon', kde=True, hue='Tipo' )\n",
        "grafica.set_title('Distribución de valor de inmuebles', fontsize=20, color='red')\n",
        "plt.xlim((50,1000))\n",
        "plt.ylim((0,700))\n",
        "plt.xlabel('Rangos de precios por millón', fontsize = 15, color='blue')\n",
        "plt.ylabel('Inmuebles por tipos', fontsize = 15, color= 'green')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 415
        },
        "id": "q2ry0IOgxiul",
        "outputId": "343938b2-7837-405b-8895-bb3d11cb3b06"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "2. **Precio del m2 por barrio y hacer el gráfico más adecuado para esta nueva variable.**\n",
        "\n",
        "---\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "VIH_pEGA0ae_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "inmuebles['Valor_m2'] = inmuebles['Precio_Millon']/inmuebles['Area']\n",
        "valor_m2_barrio = inmuebles.groupby('Barrio')['Valor_m2'].mean().reset_index()\n",
        "barrios_mas_baratos = valor_m2_barrio.sort_values(by='Valor_m2', ascending=True).head(10)"
      ],
      "metadata": {
        "id": "-QV9454A0Z-s"
      },
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,6))\n",
        "sns.barplot(data=barrios_mas_baratos, x='Barrio', y='Valor_m2', palette='pastel')\n",
        "plt.xticks(rotation=90)\n",
        "plt.xlabel('Barrios', fontsize=16, color='blue')\n",
        "plt.ylabel('Valor m2', fontsize=16, color='blue')\n",
        "plt.title('Valor de Barrios por metro cuadrado', fontsize=18, color='red')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "5uFg-T8v20Rf",
        "outputId": "b4342654-273c-4a8b-e243-995d74989c82"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
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            "needs_background": "light"
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      ]
    }
  ]
}