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    "colab": {
      "name": "Sesion_07_Ejemplo_practico_I.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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      "name": "python"
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    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "<a href=\"https://colab.research.google.com/github/hernansalinas/Curso_aprendizaje_estadistico/blob/main/Sesiones/Sesion_01a_pandas.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ],
      "metadata": {
        "id": "azyA1p6SPCPB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Solución a un problema general de machine learning\n",
        "\n",
        "En esta sesión se trabajará con las datos de los precios de las casas de california para dar solución a un problema real\n",
        "\n",
        "Referencia: Basado del libro  [hand on machine learning](https://github.com/ageron/handson-ml) y [Kaggle](https://www.kaggle.com/camnugent/california-housing-prices)\n",
        "\n"
      ],
      "metadata": {
        "id": "3zYMMsFjPFv_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Generar una visión general del problema\n",
        "2. Obtener los datos \n",
        "3. Explorar los datos\n",
        "4. Descubrir y visualizar los datos\n",
        "5. Preparar los datos para un algoritmo de machinine learning\n",
        "6. Selecccionar los modelos \n",
        "7. Elegir el mejor modelo tuneando los parametros de ajuste\n",
        "8. Presentar la solucion \n",
        "9. Moniterar y analizar los datos.\n",
        "\n",
        "https://www.kaggle.com/rahulallakonda/california-housing"
      ],
      "metadata": {
        "id": "hRsuchX9b6mV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "# Data.\n",
        "\n",
        "1. Leer los datos\n",
        "2. Analizar el estado de los datos\n",
        "3. Limpiar los datos.\n",
        "4. Analizar los datos.\n",
        "\n",
        "\n",
        "```\n",
        "\n",
        "import pandas as pd\n",
        "\n",
        "# Read data\n",
        "df.read_csv(\"\")\n",
        "df.read_excel(\")\n",
        "\n",
        "# Entender los datos\n",
        "df.head()\n",
        "df.info()\n",
        "df.describe()\n",
        "df[\"name_columns\"].unique()\n",
        "df.isnull().sum()\n",
        "df.isnan().sum()\n",
        "df.groupby(by=[\"name_cols\"]).mean()\n",
        "df.groupby(by=[\"name_cols\"]).count()\n",
        "df.groupby(by=[\"name_cols\"]).sum()\n",
        "df.hist()\n",
        "\n",
        "```"
      ],
      "metadata": {
        "id": "xO0w1PReQE5E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pylab as plt\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "SKPwdPERb50S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Si no recuerda los comandos de pandas, puede ver una cheat sheet \n",
        "#https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf\n",
        "\n",
        "data_link = \"https://raw.githubusercontent.com/hernansalinas/Curso_aprendizaje_estadistico/main/datasets/Sesion_07_housing.csv\"\n",
        "df = pd.read_csv(data_link)"
      ],
      "metadata": {
        "id": "Lc9VTRYPQGyY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
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        "id": "rkD4GW1ORDsx",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "      <th>ocean_proximity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-122.23</td>\n",
              "      <td>37.88</td>\n",
              "      <td>41.0</td>\n",
              "      <td>880.0</td>\n",
              "      <td>129.0</td>\n",
              "      <td>322.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>8.3252</td>\n",
              "      <td>452600.0</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-122.22</td>\n",
              "      <td>37.86</td>\n",
              "      <td>21.0</td>\n",
              "      <td>7099.0</td>\n",
              "      <td>1106.0</td>\n",
              "      <td>2401.0</td>\n",
              "      <td>1138.0</td>\n",
              "      <td>8.3014</td>\n",
              "      <td>358500.0</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-122.24</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1467.0</td>\n",
              "      <td>190.0</td>\n",
              "      <td>496.0</td>\n",
              "      <td>177.0</td>\n",
              "      <td>7.2574</td>\n",
              "      <td>352100.0</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-122.25</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1274.0</td>\n",
              "      <td>235.0</td>\n",
              "      <td>558.0</td>\n",
              "      <td>219.0</td>\n",
              "      <td>5.6431</td>\n",
              "      <td>341300.0</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-122.25</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1627.0</td>\n",
              "      <td>280.0</td>\n",
              "      <td>565.0</td>\n",
              "      <td>259.0</td>\n",
              "      <td>3.8462</td>\n",
              "      <td>342200.0</td>\n",
              "      <td>NEAR BAY</td>\n",
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              "  "
            ],
            "text/plain": [
              "   longitude  latitude  ...  median_house_value  ocean_proximity\n",
              "0    -122.23     37.88  ...            452600.0         NEAR BAY\n",
              "1    -122.22     37.86  ...            358500.0         NEAR BAY\n",
              "2    -122.24     37.85  ...            352100.0         NEAR BAY\n",
              "3    -122.25     37.85  ...            341300.0         NEAR BAY\n",
              "4    -122.25     37.85  ...            342200.0         NEAR BAY\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
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        },
        "id": "TllKMFOvTWa_",
        "outputId": "27be16b6-b3a1-4619-ccaf-d33357916b0c"
      },
      "execution_count": null,
      "outputs": [
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 20640 entries, 0 to 20639\n",
            "Data columns (total 10 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   longitude           20640 non-null  float64\n",
            " 1   latitude            20640 non-null  float64\n",
            " 2   housing_median_age  20640 non-null  float64\n",
            " 3   total_rooms         20640 non-null  float64\n",
            " 4   total_bedrooms      20433 non-null  float64\n",
            " 5   population          20640 non-null  float64\n",
            " 6   households          20640 non-null  float64\n",
            " 7   median_income       20640 non-null  float64\n",
            " 8   median_house_value  20640 non-null  float64\n",
            " 9   ocean_proximity     20640 non-null  object \n",
            "dtypes: float64(9), object(1)\n",
            "memory usage: 1.6+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
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          "height": 364
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        "id": "cbGw20v9RFYU",
        "outputId": "10f8906e-8a32-47f1-f9fb-169722188f03"
      },
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          "data": {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
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              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
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              "      <th>count</th>\n",
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              "      <td>20640.000000</td>\n",
              "      <td>20640.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>-119.569704</td>\n",
              "      <td>35.631861</td>\n",
              "      <td>28.639486</td>\n",
              "      <td>2635.763081</td>\n",
              "      <td>537.870553</td>\n",
              "      <td>1425.476744</td>\n",
              "      <td>499.539680</td>\n",
              "      <td>3.870671</td>\n",
              "      <td>206855.816909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.003532</td>\n",
              "      <td>2.135952</td>\n",
              "      <td>12.585558</td>\n",
              "      <td>2181.615252</td>\n",
              "      <td>421.385070</td>\n",
              "      <td>1132.462122</td>\n",
              "      <td>382.329753</td>\n",
              "      <td>1.899822</td>\n",
              "      <td>115395.615874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-124.350000</td>\n",
              "      <td>32.540000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.499900</td>\n",
              "      <td>14999.000000</td>\n",
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              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-121.800000</td>\n",
              "      <td>33.930000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>1447.750000</td>\n",
              "      <td>296.000000</td>\n",
              "      <td>787.000000</td>\n",
              "      <td>280.000000</td>\n",
              "      <td>2.563400</td>\n",
              "      <td>119600.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-118.490000</td>\n",
              "      <td>34.260000</td>\n",
              "      <td>29.000000</td>\n",
              "      <td>2127.000000</td>\n",
              "      <td>435.000000</td>\n",
              "      <td>1166.000000</td>\n",
              "      <td>409.000000</td>\n",
              "      <td>3.534800</td>\n",
              "      <td>179700.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>-118.010000</td>\n",
              "      <td>37.710000</td>\n",
              "      <td>37.000000</td>\n",
              "      <td>3148.000000</td>\n",
              "      <td>647.000000</td>\n",
              "      <td>1725.000000</td>\n",
              "      <td>605.000000</td>\n",
              "      <td>4.743250</td>\n",
              "      <td>264725.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>-114.310000</td>\n",
              "      <td>41.950000</td>\n",
              "      <td>52.000000</td>\n",
              "      <td>39320.000000</td>\n",
              "      <td>6445.000000</td>\n",
              "      <td>35682.000000</td>\n",
              "      <td>6082.000000</td>\n",
              "      <td>15.000100</td>\n",
              "      <td>500001.000000</td>\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a1abcc0e-7236-4f4c-b4ea-be7f957f026b');\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",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "          longitude      latitude  ...  median_income  median_house_value\n",
              "count  20640.000000  20640.000000  ...   20640.000000        20640.000000\n",
              "mean    -119.569704     35.631861  ...       3.870671       206855.816909\n",
              "std        2.003532      2.135952  ...       1.899822       115395.615874\n",
              "min     -124.350000     32.540000  ...       0.499900        14999.000000\n",
              "25%     -121.800000     33.930000  ...       2.563400       119600.000000\n",
              "50%     -118.490000     34.260000  ...       3.534800       179700.000000\n",
              "75%     -118.010000     37.710000  ...       4.743250       264725.000000\n",
              "max     -114.310000     41.950000  ...      15.000100       500001.000000\n",
              "\n",
              "[8 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3blxIYKsLBzH",
        "outputId": "fd4550d8-3818-474f-9f72-2de0ae787bee"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "longitude               0\n",
              "latitude                0\n",
              "housing_median_age      0\n",
              "total_rooms             0\n",
              "total_bedrooms        207\n",
              "population              0\n",
              "households              0\n",
              "median_income           0\n",
              "median_house_value      0\n",
              "ocean_proximity         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4X8oSI10LbUg",
        "outputId": "77d22231-90c1-4522-f5d0-4df779c63360"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "longitude               0\n",
              "latitude                0\n",
              "housing_median_age      0\n",
              "total_rooms             0\n",
              "total_bedrooms        207\n",
              "population              0\n",
              "households              0\n",
              "median_income           0\n",
              "median_house_value      0\n",
              "ocean_proximity         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"ocean_proximity\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sEiCopJVRzyG",
        "outputId": "94a6e50e-4cc7-402d-be41-b8aabac34d50"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['NEAR BAY', '<1H OCEAN', 'INLAND', 'NEAR OCEAN', 'ISLAND'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cols = [\"housing_median_age\",\t\"total_rooms\",\t\"total_bedrooms\",\t\"population\",\t\"households\",\t\"median_income\",\t\"median_house_value\",\"ocean_proximity\"]\n",
        "df[cols].groupby(by=[\"ocean_proximity\"]).mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        },
        "id": "A4u7hNz_L73o",
        "outputId": "26257d8d-3ab0-48f1-9d6c-a7def03ac285"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ocean_proximity</th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>&lt;1H OCEAN</th>\n",
              "      <td>29.279225</td>\n",
              "      <td>2628.343586</td>\n",
              "      <td>546.539185</td>\n",
              "      <td>1520.290499</td>\n",
              "      <td>517.744965</td>\n",
              "      <td>4.230682</td>\n",
              "      <td>240084.285464</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>INLAND</th>\n",
              "      <td>24.271867</td>\n",
              "      <td>2717.742787</td>\n",
              "      <td>533.881619</td>\n",
              "      <td>1391.046252</td>\n",
              "      <td>477.447565</td>\n",
              "      <td>3.208996</td>\n",
              "      <td>124805.392001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ISLAND</th>\n",
              "      <td>42.400000</td>\n",
              "      <td>1574.600000</td>\n",
              "      <td>420.400000</td>\n",
              "      <td>668.000000</td>\n",
              "      <td>276.600000</td>\n",
              "      <td>2.744420</td>\n",
              "      <td>380440.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NEAR BAY</th>\n",
              "      <td>37.730131</td>\n",
              "      <td>2493.589520</td>\n",
              "      <td>514.182819</td>\n",
              "      <td>1230.317467</td>\n",
              "      <td>488.616157</td>\n",
              "      <td>4.172885</td>\n",
              "      <td>259212.311790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NEAR OCEAN</th>\n",
              "      <td>29.347254</td>\n",
              "      <td>2583.700903</td>\n",
              "      <td>538.615677</td>\n",
              "      <td>1354.008653</td>\n",
              "      <td>501.244545</td>\n",
              "      <td>4.005785</td>\n",
              "      <td>249433.977427</td>\n",
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              "  </tbody>\n",
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              "          const element = document.querySelector('#df-6b317221-7a3f-422d-92ea-3ba85c448437');\n",
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              "            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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "                 housing_median_age  ...  median_house_value\n",
              "ocean_proximity                      ...                    \n",
              "<1H OCEAN                 29.279225  ...       240084.285464\n",
              "INLAND                    24.271867  ...       124805.392001\n",
              "ISLAND                    42.400000  ...       380440.000000\n",
              "NEAR BAY                  37.730131  ...       259212.311790\n",
              "NEAR OCEAN                29.347254  ...       249433.977427\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.ocean_proximity.value_counts().plot(kind=\"bar\")\n",
        "plt.title('Number of houses')\n",
        "plt.xlabel(\"Ocean proximity\")\n",
        "plt.ylabel('Count')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "id": "kFZ2OHgmM5wk",
        "outputId": "ac15489b-6ce9-48d1-84b0-144fbbf44573"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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rYREREbUSFhERUSthERERtRIWERFRK2ERERG1EhYREVErYREREbUSFhERUSthERERtRIWERFRK2ERERG1EhYREVErYREREbUSFhERUSthERERtRIWERFRK2ERERG1EhYREVErYREREbUmN11AxHgy7cgfN10Cc4/ZqekSYgDlyCIiImolLCIiolbCIiIiaiUsIiKiVsIiIiJqJSwiIqJWwiIiImrlPouIWCq552Sw5MgiIiJqJSwiIqJW18JC0nqSrpB0u6TbJH2itK8u6RJJd5Z/VyvtkvQ1SXMk3Sxpi5bnOqA8/k5JB3Sr5oiIaK+bRxaLgL+3vQnwFuBQSZsARwKX2d4QuKysA7wL2LD8HAKcCFW4AEcBbwbeBBw1FDAREdEbXQsL2/fbvr4sPwbMBtYBdgbOLA87E9ilLO8MfNuVa4BVJa0FvBO4xPZC2w8DlwA7dqvuiIh4oZ6cs5A0DXgjcC0w1fb9ZdMDwNSyvA5wX8tu80rbSO0REdEjXQ8LSSsDPwAOt/1o6zbbBtyh1zlE0kxJMxcsWNCJp4yIiKKrYSFpWaqgONv2eaX5d6V7ifLvg6V9PrBey+7rlraR2p/H9sm2p9uePmXKlM6+kYiIAdfNq6EEnArMtv3/WjZdCAxd0XQAcEFL+/7lqqi3AH8o3VUXAztIWq2c2N6htEVERI908w7ubYD9gFsk3Vja/gE4Bpgh6SDgHmCPsu0nwLuBOcCfgA8B2F4o6YvAdeVxX7C9sIt1R0TEMF0LC9tXAxph8/ZtHm/g0BGe6zTgtM5VFxERSyJ3cEdERK2ERURE1EpYRERErYRFRETUSlhERESthEVERNRKWERERK2ERURE1EpYRERErYRFRETUSlhERESthEVERNRKWERERK2ERURE1EpYRERErYRFRETUSlhERESthEVERNRKWERERK2ERURE1EpYRERErYRFRETUSlhERESthEVERNRKWERERK2ERURE1EpYRERErYRFRETUSlhERESthEVERNRKWERERK2ERURE1EpYRERErYRFRETUSlhERESthEVERNRKWERERK1xExaSdpR0h6Q5ko5sup6IiEEyLsJC0iTgG8C7gE2AvSVt0mxVERGDY1yEBfAmYI7tu2w/BZwD7NxwTRERA0O2m66hlqTdgB1tH1zW9wPebPtjLY85BDikrG4E3NHzQl9oTeD3TRfRJ/JZLJbPYrF8Fov1w2fxKttT2m2Y3OtKusX2ycDJTdfRStJM29ObrqMf5LNYLJ/FYvksFuv3z2K8dEPNB9ZrWV+3tEVERA+Ml7C4DthQ0vqSlgP2Ai5suKaIiIExLrqhbC+S9DHgYmAScJrt2xouayz6qlusYfksFstnsVg+i8X6+rMYFye4IyKiWeOlGyoiIhqUsIiIiFoJi4joOkl7Nl1DvDg5Z9EBkv55lM22/cWeFRPRhyRdRHVBzd/avqvpemLJJSw6QNLft2leETgYWMP2yj0uqXGS1gD2AV5bmmYD37P9UHNV9Zaku4HWL5ha1m371b2vqjmSdgH+DfgucCLw7NA22wubqqtJkjaj5Tti+9Ym6xlNwqLDJK0CfAI4CJgBHG/7wWar6i1JGwOXU13qfAPVL8k3An8DbGf71w2W1zMlMFstA+wBfAq43vYHel9VsyS9Afg58DDPD86/aK6q3pP0MuACqpuNb6b6jmwG3AvsbPvRBstrK2HRIZJWBz4J7AucCZxg++Fmq2qGpHOBGbZnDGv/ALDPoP2SlLQMsB9wBHAj8K+2b2+2qt6StDzwj8BuwBG2L2q4pEZJ+hrwFPBp28+WtmWAY4AVbB/WZH3tJCw6QNK/A++nuqnmG7b/2HBJjZJ0h+2NlnTbRCNpWeDDwN8BVwPH2J7TbFXNkHQH8APgi7b/PGzbVNu/a6ayZki6HXi97UXD2icDt9jeuJnKRpaw6ABJzwJPAoto00dt+6WNFNYQSdfb3mJJt000kuZR/T/xVaruheexfV7Pi2qIpE1aj6YkrQp8gOq81sa2126suAZIutH25ku6rUnjYriPfmc7lyA/38slfbJNu4C2wx9PUJdS/fHwhvLTysDAhIXt2yWtQDUPzT5U57BWAXahOocxaF4i6Y1U34lWApZvoJ5aObLoEkkrAbsCe9veqel6eknSUaNtt/35XtXSrwat60XSd4G/BH5GNXnZ5VQTmq3faGENkXQlz++FeB7bb+9dNWOTI4sOKiPi7kT1l9M7qfpoT2q0qAYkDNob3vUCDFLXyyZUV0DNprpE9BlJA/uXqu23NV3DkkpYdICkHYC9gR2AK4BvA1vZ/lCjhTUkNykulq6Xiu3NJb2W6ntyqaTfA6sM2hHWEEl/Ndp22333/0e6oTqgnOD+BXCg7btL212Ddu34kBFuUlyJ6t6TgblJMV0vI5O0JVWA7g7Ms711wyX1lKQftWk28HpgPduTelxSrRxZdMYWVBMyXSrpLqpfDH33H7tXbB8/tNxyk+KHqD6X40fabwJK18sIbM8CZkn6FFWgDhTb721dl7QN1X0oDwB9d48F5Mii4yRtTXWo/QHgJuD8Mj/4QMlNipWWrpc9gd8DGwGbDlrXi6SXUH0GDwM/Aj5NFRK/obr34vcNltcYSdsD/0R1VPGvti9puKQRJSy6pNyN+Q5gT9sHNV1PL+UmxfZK18veVEN+DFTXi6QZwNNU3ZGrAbdShca2wOa239NgeT0naSfgc8AfgKNtX91wSbUSFh0g6YO2zyrL29j+Zcu2j9n+j+aq673cpDg6SQL+sh9PYnaLpFttb1ruUJ5n+xUt226yPfw+lAmtfEfmUfU+vOCXsO339byoGjln0RmfBM4qy1+nOocx5MPAQIVFblKsSJphe4+yfKztz0CVlpL+kerquUHxFIDtRZJ+O2zbMw3U07S+u4+iTsKiMzTCcrv1gTSgNylu2LL8N8BnWtYH6U52gHXL4HlqWaasr9NcWc2wfVW7dknrUV0s03Z7kxIWneERltutD4zcpDjqf/tB+//iiJblmcO2DV8fKJKmUF1CvDfVjZrnN1tRewmLznitpKEx6V9dlinrA3evRW5SfM6KZfyfZYAVWsYCErBCo5X1mO0zm66hn5RLyt9P9YfUa6jGCVvf9rqNFjaKnODuAEmvGm277Xt6VUs/yE2KlfE4/k/0hqQ/A7+iurfi6nIeq6+/Izmy6IxlgamtV0HBczfaPNBMSY3KTYqMz/F/omc+S/Ud+SbwPUnfb7ieWrlqpTO+CrSbBvHRsm2g2L7R9pFljumjgM2BZSX9l6RDGi6vZyR9UNJ+bdr3k7RPEzX1o3Lxw0Cx/VXbb6EaNwzgh8Dakj4j6TUNljaidEN1gKTrbG81wrZbbG/W65r6zSDepCjpWmD74Tclll+OP7e9ZTOVNUPSOsBawM22n5L0cuBwqu7KQRqBty1Jm1Lu9re9QdP1DJcji85YdZRtA3UicyS2n7X9M+C1TdfSQ8u2u3vd9uNUXZcDQ9LhVPOPfx24RtLBVGNmrQAMVGiOxPattj8HXNB0Le3knEVnzJT0Edvfam0sX4hZDdXUr9ZruoAeWkHSSiUcnlOuhFmuoZqacgiwke2Fkl4J/C+wTRlQMJ5vd6DdyM2NSlh0xuHA+ZL2ZXE4TKf6hbBrY1VF004FzpX00aEr4iRNA75Rtg2SJ2wvBLB9r6Q7EhQj6ssbeRMWHVBGEN1a0tuBTUvzj21f3mBZjZH0/pE2MUDdcraPk/RH4OeSVqZ6/48Bx9g+sdnqeq71rm2AtVrXbX+8gZoaU0ZlbruJhMXA8LB/B9F7R9l2Uc+q6AO2TwJOKl1P2H6s4ZKacsSw9UE/qphF9TuiXTA81eNaxiRXQ3VAucrjPOAJFn8JtqT6K3pX2/Obqi2aVa5wOQJ4XWm6DTjO9i3NVdU/yjwX77X9n03XEqNLWHSApPOBC2yfMax9f+ADtnduu+MEVd73SGz7Oz0rpkGSdgaOA/6NxeMfTae6IetTtvvyqpdukzSJaqywoSFhfmF7t2ar6q0y6sMjtv9Q1t9ONTf7XKo5YPru6CJh0QHlZN1GS7ptopL09RE2vQ9Yx/ZAdH9KugnY2fbcYe3TqP64GLQ5HP6aaiykd1MNdbEN8Be2/9RoYQ0o9+Dsavu3kjYHLqX6o+L1wNO2D260wDYG4kvbA23vVyk3og3iMBfPzSFcJvrZl2p47muAo5uqqwGThwcFgO25kgbtPot5wL3AiVRHVY9JunsQg6JYwfbQvB4fBE6zfXz5nXFjg3WNKDfldcZFkr7VOmxBWT4J+ElzZTVH0uSWG6/eAexme0/bN9fsOpEsKvcUPE/pgljUQD1NOpdq+O09gfeW78cgd2u0ntjeDrgMqptXmymnXsKiMz5NNZfuPZJmSZpF1ff4KPCpJgtrgqRDgdupTvLvaPtA23c0XFYTjqIaTPFASZuVnw8BPwP+ueHaesr24cD6wPHA24A7gCmS9iiXFQ+ayyXNkHQC1ZzklwNIWotcDTXxSVoBGBrT5TeDeohdhih/EFhA+zm4X99IYQ2Q9Aaqu3Fbr4Y63vZNzVXVvNINN3SS+52212y4pJ4q3bN7Uo2VNWPoisky58nLbV/cZH3tJCyi4zK/Rwwn6aW2243MjKSNbc/udU2xZBIWEdF1kq63vUVZvsz29u22DQpJj9H+nM3Q0fdLe1xSrVwNFR03Hr8I0XWtJ3SHD3XRl8NbdJPtVZquYUklLDpA0qh/Fdm+vle19IPx+EXotXaj0U5wHmG53Xr0oYRFZxzfsrwl1d26Q38tmerSuBhAo034Q3Up6aB4uaRPUn0vhpYp61OaKyvGKucsOkzSDbbf2HQd0bwy4c/ngDnA8lTzLR8LfBv4su37GyyvpyQdNdp225/vVS2xdBIWHTaIJ+uiPUm3A9tmwp+YCNINFdE9mfCnkDTaTYi2/cWeFRNLJWHRAWXgvKFDtOGTvAzcxC7xnEz4s1i7k/krAQcBawAJiz6XsOiMmS3LA/mXY7SVCX8K289dBFImgvoE8CHgHJ5/gUj0qZyziOixQZ3wp0wl+kmqUYjPBE6w/XCzVcVYZSDBLpN0ctM1RPMkTZL0bknfAe6hGhdoYEj6d+A6qjnIN7P9LwmK8SVHFh1QM/n6TbbX7WU90T8y4U+lDC75JNXQ7O0Gl8xd/X0uYdEBkp6h+muxddiCocnY17G9XCOFRaOGTfjzw5YJf9ZvuLSIJZYT3J1xF7C97XuHb5B0XwP1RH84l2pe5T2BZyRdQIa2iHEq5yw646tUE5i08+VeFhL9IxP+xESSbqiIHhn0CX9ifEtYdIikFYENW2dAK0M8PDM0C1YMlkz4ExNJuqE652ngvDIR/ZBTqEYcjcF05dCCpMuGbTu7t6VEvDgJiw6x/TRwPrAHPHdUMcX2zFF3jIksE/7EhJGw6KxTqIYwANgfOL3BWqJ5mfAnJoxcOttBtn+tymuAvYC/bLqmaFQm/IkJIye4O0zSgcCHgfm29264nGhQJvyJiSRh0WHlqqj7gQ/YvrTpeiIiOiFhEdElmfAnJpKERUSXSPr7Ns3PTfhjO3dxx7iRsIjogZYJfw4CZgDH236w2aoixi5XQ0V0UZsJf7bIPA4xHiUsIrqkTPjzfuBkqgl//thwSRFLLd1QEV2SCX9iIklYRERErQz3ERERtRIWERFRK2ERERG1EhYx4UhaV9IFku6U9BtJJ0harum6OkXSdElfW8J9TpG0SVn+h+5UFhNZTnDHhCJJwLXAibZPlzSJ6tLVhbaPaLa69iRNsv1MD1/vj7l7PJZUjixiotkOeML26QDll/DfAR+WtKKkSZKOk3SrpJslHQYgaUtJV0maJeliSWuV9o9Iuk7STZJ+UAaKRNIZkr4m6b8l3SVpt+GFSJom6deSzpY0W9K5LfvPlXSspOuB3SXtLemWUtex5TG7SrqsDHu/lqT/lfQKSW+TdFF5zL9IOlPSLyTdI+n9kr5cnuunZd5vJF1ZjkiOAVaQdGOp6wuSDm+p+WhJn+jaf50YtxIWMdG8DpjV2lDmwb4X2AA4BJgGbG779cDZ5Rfq14HdbG8JnAYcXXY/z/ZWtt8AzKYarmPIWsC2wHuAY0aoZyPgm7Y3BvKiyTkAAAJQSURBVB4F/rZl20O2twB+DhxLFXSbA1tJ2sX2+VQjGB8KfAs4yvYDbV7j1WXf9wFnAVfY3gz4M7DTsM/iSODPtje3vW95r/sDSFqGah6Ws0Z4LzHAcgd3DJp3ACfZXgRge6GkTYFNgUuqXiwmUf2SBthU0peAVYGVgYtbnuuHtp8Fbpc0dYTXu8/2L8vyWcDHgePK+vfLv1sBV9peACDpbOCvgB8ChwG3AtfY/t4Ir/Fftp+WdEup/ael/RaqYByR7bmSHpL0RmAqcIPth0bbJwZTwiImmtuB53UJSXop8Epgzgj7CLjN9lvbbDsD2MX2TWViq7e1bHty2HO0M9p0qo+PsE+rdYFngamSlinhNNyTALaflfS0F5+IfJaxfcdPAQ4EXkF1pBHxAumGionmMmBFSUNdK5OA44EzbP8JuAT4P5Iml+2rA3cAUyS9tbQtK+l15flWAe4vXVX7LkU9rxx6XmAf4Oo2j/kV8NeS1iz17g1cVWo8razPphqQsBOeHjqXUZwP7Eh1hHNx+11i0CUsYkIpf1XvSnXS+E7gf4EngKHLRU+hOn9xs6SbgH1sP0V1NHJsabsR2Lo8/p+orq76JfDrpSjpDuBQSbOB1YAT29R8P3AkcAVwEzDL9gWl5l/YvpoqKA6WtPFS1DDcyVTv/+zy+k+V157Ry6uyYnzJpbMRXSJpGnCR7U0bLmVU5cT29cDutu9sup7oTzmyiBhg5Ua9OcBlCYoYTY4sIiKiVo4sIiKiVsIiIiJqJSwiIqJWwiIiImolLCIiotb/B43LSQM7YMS6AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.hist(alpha=0.5, figsize=(10,8))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 678
        },
        "id": "jJebJwIKTDf_",
        "outputId": "4b11b3c4-0572-412e-cd9a-75d195d29fd8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7ff668d3ead0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7ff668d50790>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7ff668cc1790>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7ff668c76ad0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7ff668c3a110>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7ff668bf1710>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7ff668ba6d90>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7ff668b68310>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7ff668b68350>]],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 89
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 9 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### [Diagrama de caja](https://en.wikipedia.org/wiki/Box_plot)\n",
        "\n",
        "\n",
        "### Diagrama de caja \n",
        "\n",
        "![box](https://upload.wikimedia.org/wikipedia/commons/thumb/1/1a/Boxplot_vs_PDF.svg/800px-Boxplot_vs_PDF.svg.png)\n",
        "\n",
        "\n",
        "\n",
        "### Interpretación de un diagrama de caja\n",
        "\n",
        "- Desde el minimo al valor más bajo de la caja: primer cuartil, 25% de los datos \n",
        "- Desde el valor más bajo de la caja hasta la mediana: segundo cuartil, 25% de los datos \n",
        "- Desde la mediana hasta el valor mas alto de la caja : tercer cuartil, 25% de los datos \n",
        "- Desde el valor mas alto de la caja hasta el máximo: Cuarto  cuartil, 25% de los datos \n",
        "\n",
        "\n",
        "El rango intercuartil $IQR = Q_3-Q_1$ permite definir que datos pueden ser atipicos, basado en los siguientes limites:\n",
        "\n",
        "$Max = Q3 + 1.5IQR$\n",
        "\n",
        "$Min = Q1 - 1.5IQR$\n",
        "\n",
        "\n",
        "Veamos un ejemplo:\n"
      ],
      "metadata": {
        "id": "z2fPNtitWpMR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "T = np.array([52, 57, 57, 58, 63, 66, 66, 67, 67, 68, 69, 70, 70, 70, 70, 72, 73, 75, 75, 76, 76, 78, 79, 89])\n",
        "Tsort = np.sort(T)\n",
        "print(f\"T sort:{Tsort}\")\n",
        "\n",
        "IQR=9\n",
        "max_ = 75 + 1.5*IQR\n",
        "min_ = 66 - 1.5*IQR\n",
        "print(max_)\n",
        "print(min_)\n",
        "plt.boxplot(T)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HhsreSvxYYpe",
        "outputId": "416fa160-d048-4a67-eb19-ac38e7823252"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "T sort:[52 57 57 58 63 66 66 67 67 68 69 70 70 70 70 72 73 75 75 76 76 78 79 89]\n",
            "88.5\n",
            "52.5\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'boxes': [<matplotlib.lines.Line2D at 0x7ff669b70e90>],\n",
              " 'caps': [<matplotlib.lines.Line2D at 0x7ff669c9ce10>,\n",
              "  <matplotlib.lines.Line2D at 0x7ff6777f8490>],\n",
              " 'fliers': [<matplotlib.lines.Line2D at 0x7ff66ec60350>],\n",
              " 'means': [],\n",
              " 'medians': [<matplotlib.lines.Line2D at 0x7ff67763c4d0>],\n",
              " 'whiskers': [<matplotlib.lines.Line2D at 0x7ff669b707d0>,\n",
              "  <matplotlib.lines.Line2D at 0x7ff669b8d5d0>]}"
            ]
          },
          "metadata": {},
          "execution_count": 90
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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rOaQXw4BLUqMMuCQ1yoBLUqMMuCQ1yoBrXUsyCfwncF2SJ5KMr/VMUlf+Kb0kNcpn4JLUKAMuSY0y4JLUKAMuSY0y4JLUKAMuSY0y4JLUqP8HGHazYLyBJVAAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        " volviendo a nuestro datos tenemos que:"
      ],
      "metadata": {
        "id": "ur10HquGcjN0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = df[df[\"ocean_proximity\"] == \"<1H OCEAN\"]\n",
        "df2[\"median_house_value\"].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MIryMamGUXcK",
        "outputId": "e162c017-4a52-47e7-c1af-802e4da0e40d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff669b70dd0>"
            ]
          },
          "metadata": {},
          "execution_count": 91
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#draw boxplot\n",
        "df.boxplot(column=\"median_house_value\", by='ocean_proximity', sym = 'k.', figsize=(18,6))\n",
        "#set title\n",
        "plt.title('Boxplot for Camparing price per living space for each city')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t_8t-h9cTAXF",
        "outputId": "9274575e-d1e9-42f3-8541-6d6f8800cfe5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/numpy/core/_asarray.py:83: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  return array(a, dtype, copy=False, order=order)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## [Matrix de correlación](https://en.wikipedia.org/wiki/Correlation)\n",
        "\n",
        "¿Como se determina la matrix de correlación?\n",
        "\n",
        "![Matrix de correlación](https://upload.wikimedia.org/wikipedia/commons/thumb/d/d4/Correlation_examples2.svg/1920px-Correlation_examples2.svg.png)\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "corr_matrix = df.corr()\n",
        "corr_matrix\n",
        "\n",
        "plt.figure(figsize = (10,6))\n",
        "sns.heatmap(corr_matrix, annot = True)\n",
        "plt.show()\n",
        "```\n"
      ],
      "metadata": {
        "id": "qUyVrL7lfn-g"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix = df.corr()\n",
        "corr_matrix"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kmw7X5wxffOU",
        "outputId": "a10bbbea-a035-4a59-98ae-c5bce182af24"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-87432d8f-1659-4741-a242-4607ce8997ae\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>longitude</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.924664</td>\n",
              "      <td>-0.108197</td>\n",
              "      <td>0.044568</td>\n",
              "      <td>0.069608</td>\n",
              "      <td>0.099773</td>\n",
              "      <td>0.055310</td>\n",
              "      <td>-0.015176</td>\n",
              "      <td>-0.045967</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>latitude</th>\n",
              "      <td>-0.924664</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.011173</td>\n",
              "      <td>-0.036100</td>\n",
              "      <td>-0.066983</td>\n",
              "      <td>-0.108785</td>\n",
              "      <td>-0.071035</td>\n",
              "      <td>-0.079809</td>\n",
              "      <td>-0.144160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>housing_median_age</th>\n",
              "      <td>-0.108197</td>\n",
              "      <td>0.011173</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.361262</td>\n",
              "      <td>-0.320451</td>\n",
              "      <td>-0.296244</td>\n",
              "      <td>-0.302916</td>\n",
              "      <td>-0.119034</td>\n",
              "      <td>0.105623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_rooms</th>\n",
              "      <td>0.044568</td>\n",
              "      <td>-0.036100</td>\n",
              "      <td>-0.361262</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.930380</td>\n",
              "      <td>0.857126</td>\n",
              "      <td>0.918484</td>\n",
              "      <td>0.198050</td>\n",
              "      <td>0.134153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_bedrooms</th>\n",
              "      <td>0.069608</td>\n",
              "      <td>-0.066983</td>\n",
              "      <td>-0.320451</td>\n",
              "      <td>0.930380</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.877747</td>\n",
              "      <td>0.979728</td>\n",
              "      <td>-0.007723</td>\n",
              "      <td>0.049686</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>population</th>\n",
              "      <td>0.099773</td>\n",
              "      <td>-0.108785</td>\n",
              "      <td>-0.296244</td>\n",
              "      <td>0.857126</td>\n",
              "      <td>0.877747</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.907222</td>\n",
              "      <td>0.004834</td>\n",
              "      <td>-0.024650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>households</th>\n",
              "      <td>0.055310</td>\n",
              "      <td>-0.071035</td>\n",
              "      <td>-0.302916</td>\n",
              "      <td>0.918484</td>\n",
              "      <td>0.979728</td>\n",
              "      <td>0.907222</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.013033</td>\n",
              "      <td>0.065843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>median_income</th>\n",
              "      <td>-0.015176</td>\n",
              "      <td>-0.079809</td>\n",
              "      <td>-0.119034</td>\n",
              "      <td>0.198050</td>\n",
              "      <td>-0.007723</td>\n",
              "      <td>0.004834</td>\n",
              "      <td>0.013033</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.688075</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>median_house_value</th>\n",
              "      <td>-0.045967</td>\n",
              "      <td>-0.144160</td>\n",
              "      <td>0.105623</td>\n",
              "      <td>0.134153</td>\n",
              "      <td>0.049686</td>\n",
              "      <td>-0.024650</td>\n",
              "      <td>0.065843</td>\n",
              "      <td>0.688075</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-87432d8f-1659-4741-a242-4607ce8997ae')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-87432d8f-1659-4741-a242-4607ce8997ae 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-87432d8f-1659-4741-a242-4607ce8997ae');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "                    longitude  latitude  ...  median_income  median_house_value\n",
              "longitude            1.000000 -0.924664  ...      -0.015176           -0.045967\n",
              "latitude            -0.924664  1.000000  ...      -0.079809           -0.144160\n",
              "housing_median_age  -0.108197  0.011173  ...      -0.119034            0.105623\n",
              "total_rooms          0.044568 -0.036100  ...       0.198050            0.134153\n",
              "total_bedrooms       0.069608 -0.066983  ...      -0.007723            0.049686\n",
              "population           0.099773 -0.108785  ...       0.004834           -0.024650\n",
              "households           0.055310 -0.071035  ...       0.013033            0.065843\n",
              "median_income       -0.015176 -0.079809  ...       1.000000            0.688075\n",
              "median_house_value  -0.045967 -0.144160  ...       0.688075            1.000000\n",
              "\n",
              "[9 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualización de la matrix de correlación\n",
        "plt.figure(figsize = (10,6))\n",
        "sns.heatmap(corr_matrix, annot = True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PJh0akuCkdvs",
        "outputId": "d0ad393a-03ca-4f13-92af-f382b3ca6bae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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aKEcHfG7uTmJEwZdSYsQmfIfaiuTqN3Qj5a+dAOwbMp2dXceys+tYTr//EzFvfc2Zj5ZjcnXG5G77rmVydcazZyiWfVU3gpe2/QBODQJxrFML5eiA9409SS6UU3LERqoPCQPAa9B1pP69I69RKbxv6E7ST5dH8WjZuT83Hxwd8LyhJymr/rF3WCVK234A53zPqeo39iCp0P2fFLEJ39tsxY33oOtIMe5/Bx9PMNk+9pzq1cI5KJDMo7G2AtPYrY2DGc/rO2KphFHh6A9/z53IEvfrZmoN7QWAZ/vGZKekkVnoNZ15OpHsVAue7RsDUGtoL+J+23zB23D0zcvRpX5NXIMDsBwt+n5XHsc/XME/YVP5J2wqp3+NJHBoTwC82je6YB5e7RsBEDi0J2d+iyR173HWtnyAPzs+yp8dHyUjOoF/wqeReSaJM79F4t25GcpswuTqhHe7Rpw7UPVnuSiVa3DCjIw8Fu87oCuwHdshvE9qrWOVUsUePKK1tiilHgJ+U0qdA0p6dX8BLFFKjcdWLL4KfGWMFP6Sr99C4EOl1F5gL7DFuJ0zSql7gKVKKWej7wxgf9lTLbvJz85h87YdJCYmE3bLXTw0+m6G3NjfHqFc0PJfVzFgQF/27f2LNIuFMWPyDhON3LyCDh1tx8y9Pm8mbdrYjoF6cdbrHDhg+6b+8ktP4+HhzhdLFwFw/PhJBt9a/GznyhK7Kgr/sFAGbJhHjiWTyEmLctuuj5jNyvDpALSeMYy6g7thdnVi0Ja3OPL5Gva89i3VQ4Lp+sEknLzdCAhvS4vJQ4joPaXyA8+xcuzpJTT57FkwmYn/ciXp+48T+MQwzm0/SFLEZuK+WEnQmxNptX4hOYkpHHrotQtu0qGGN43emwrYdm0lfL+O5LXbKj+X83KsRD/zLsGfPA9mE2e/WknGgWPUmjQCy84DJK/cRMJXEdSd9xhN1y4iJzGVY4/OzV3dvXNLMmPOkHn8VNXFfCE5VmKfX0jdD160narn6xVkHjyG34S7SN95gNTVG3Fp3Zg67zyN2dMDjz6dqTH+Lg4PetBu8Z54ejEN/+8526l6vlxF+v7j+D82nLSdB0mO2ET8lxHUf2MSLda9S3ZiCkceeRWw3fcBjw9HZ2WDVXN8+kJyklIxuTrT6NPnUA4OYDaRsn478Z+vqNQ0ElZuxTesLZ03vkWOJZN9ExbktnVY9QqRYZMBODBlCc3mP4zJxYmEVVEkrLI91/0GdqLx7Ptw9PWk9WfTSN11hB13zsKrS3OCnrwDnZ2DtlrZ/+RishNTKy2PuJXb8AsLpfvGN8mxZLB7Qt5p27qsmsM/YbbX6t4pH9Bq/oOYXJyIWxVF3KqoC2733IFo4ldH0XXNXNCaE5+tJvXfE5WWh7g0SuuqnX15tVJKeWitU43Z1wuAA1rr1+0dV1bc4Sv+AXYNvIwPlL4EX/j2tncI5dbAfM7eIVQIJ4cr/xglR8crPweA9AxHe4dQIZIynOwdQrllYrZ3CBWi36kvVFXeXsauiHJ/zjq3Cq/SmMtLRh4rzv1KqVHYJrFswzb7WgghhBBXsytwt3N5SfFYQYxRRruPNAohhBCi6thOzHJtkQkzQgghhBCi1GTkUQghhBCirK7BU/VI8SiEEEIIUVZyzKMQQgghhCg1GXkUQgghhBCldg3+PKFMmBFCCCGEEKUmI49CCCGEEGUlu62FEEIIIUSpyYQZIYQQQghRatfgyKMc8yiEEEIIIUpNRh6FEEIIIcpKdlsLIYQQQohSk+JRXG1cA3vYO4Rys0T/ae8QKsTm1pPtHUK5JWU52zuECpGRpewdQrmlZZjtHUKFcL1KPnitV/5TiiTT1fGcqmpaX3vneZTiUQghhBCirK6SL0CXQibMCCGEEEKIUpPiUQghhBCirLS1/JeLUEoNUErtU0odVEpNLab9daVUlHHZr5RKzNeWk6/tx4pIWXZbCyGEEEKUVSXvtlZKmYEFQDhwAtislPpRa73nfB+t9aR8/R8F2ubbhEVrHVqRMcnIoxBCCCFEWVX+yGMn4KDW+rDWOhP4Arj5Av2HAUsrKLtiSfEohBBCCFFWVmu5L0qpsUqpyHyXsfluoTZwPN/1E8ayIpRS9YEgYHW+xS7GNv9RSt1SESnLbmshhBBCCDvSWi8GFlfApu4EvtYFzx9UX2t9UikVDKxWSu3UWh8qz43IyKMQQgghRFlV/m7rk0DdfNfrGMuKcyeFdllrrU8afw8Dayl4PGSZSPEohBBCCFFWFbDb+iI2A42VUkFKKSdsBWKRWdNKqWZAdWBDvmXVlVLOxv9+wHXAnsLrXirZbS2EEEIIUVaVPNtaa52tlHoE+B0wAx9orXcrpWYCkVrr84XkncAXWmudb/XmwCKllBXbgOGc/LO0y0qKRyGEEEKIy5jWejmwvNCyZwpdf66Y9f4GWld0PFI8CiGEEEKUVSlO8n21keJRCCGEEKKsrsHftpbi8RIopVK11h4XaPcGhmut3zGuBwLztda3KaVCgUBj6PlSbvM5IFVr/Wo5Qi+z1+fNZOCAvqRZLIwePYltUbuK9Bk69CamTX0Us9nM8uUrmTZ9NgATJ4zlvvuGkZ2dTdyZBMaMfYxjx0qaIGYfM2bPY91fm/Cp7s33n75r73AK8O4TStDM+8Bs4vTnqzj59ncF2pWTA43nj8e9TTDZZ1PY/8A8Mk6cwaG6B02XTMYjtCGnv1zLf0+9l7tOvanDqXFbLxy83dnY6K4qy6XJrHvwDWtLjiWDveMXkrLzvyJ9qrUJosX8hzC5OBG/ahv7n/oIgOApt+M3oANYNZlxSewZv5DMU2cB8O7WgiYvjEI5mMlKSGHr4OcrNY8Ws0ZRw8hjx/iFJO88UqSPZ5sgQuY/iMnFiTOrtrHnqY9z2+qP7k/9e/uhc6ycXrmNfS98TuCQ6wh+6Ma8+6FFPdZfP42U3UcrNReAkBdGEhAWQrYlk8iJi0gsJp+WU4dS/7YeOHm7832j0bnL/bo0I2TmXXg1r8fGcW9z8pdNlR5vfi1mjaJmWCg5lky2X/CxGIfZxYnTq6JyH4u2i8fj3jAAAEdPd7KSz7E+bBqO1T1o//5EvEIbcuKLP9g9/aMqzAhavjiKWkZOURMWklRMTl5tggh905bTqVVR7J5hy8mzZX3azB2NydkRnWNl59QPSNxWrrOxlEmHF+6mdt9Qsi0ZbJi0mIRicgiZMpTgod1x8nLny8ZjirTXHdSRXu9NYPmAp0nYUfS94rJzDY48ymzriuUNPHT+itY6Wmt9m3E1FBhkl6jKaOCAvjRuFESzFt158MEpLHj7pSJ9fHyq8/JLM+jX/w5CQvtSq1ZN+vbpDkBU1C46dxlIu/bhfPPtL8x5aUZVp3BRtwwK5915L9o7jKJMJoJn38+eEbOI6jURv1u649qkToEutYaFkZ2UyrZujxC9+Gfqz7gbAGt6FsfmLuXIzE+KbDZhxWZ2DJpSJSmc5xsWimuQPxu6TODfJ5bQdO7oYvs1nTuGvY8vZkOXCbgG+ePb1/ZrWkcX/MSmPk+yKWwKcRFbCXp8CAAOnm40mzOa7SPnsrHXE+y8//VKzaNGWChuQQH80WUiu55YQqu5RT/0AFrNHc3OxxfzR5eJuAUFUMPIw+e6FtQa0IH1fafwZ6/J/LfwZwCiv/mL9WFTWR82le2PLCDt2JkqKRz9+4ZQLdif37o9ztbJ79Nuzr3F9otZsY3Vg54psjztRByRExZx/Lu/KzvUImqEheIe5M/aLpPY+cQSWpXwnGo99z52Pr6EtV0m4R7kT42+IQBsGzuf9WHTWB82jdhfNhH7y2YArBlZ7JuzjL3PfVZluZxXMywUj2B/VnedxPYnltD65RJyevk+tj++hNVdJ+ER7E9NI6cWTw9n/2vfsO76aeybu4zmTw+vyvABCOwbQrUgf3647nE2Pvk+nV66p9h+JyO28tugZ4ttc3B3odmY/pzZcrASI61glT/b+rIjxWMZKKU8lFKrlFJblVI7lVLnfyZoDtDQ+PHxV5RSDZRSu4yp9TOBO4y2O5RSzymlnsi3zV1KqQbG/08ZP2y+Hmiar09DpdRvSqktSqk/jWn5lebGG/vzf599DcDGTVvx8vbC379mgT7BQfU4ePA/4uISAFi1+k8GD7bVyGv/+BuLJd1Yfwt1agdUZrhl0iG0NV6e1ewdRhEebRthORJLxrFT6Kxs4n5Yj0//jgX6VB/QidNfrQUg/ucNePWwHRNttWSQsulfrOlZRbabuvUAWacTKz3+/GoM6EjssnUAJG85gIOnO041vQv0carpjYOHK8lbDgAQu2wdNQba8s1JteT2M7u5gDGRsNat3Tm9fBMZJ+MByIpLrtQ8ag3owEkjj8QtB3HwdMO5UB7ORh6JxgffyWXrqDWwAwD1R4Vz6K0fsGZmA5BZTLwBg68j5vuqKcYCB7Tn6LI/AUjYehBHTzdcCuVzvi29mOdM2ok4kvYeR1t1kbbKVmtAe04asSduscV+8cfiz9zHIr+Am7oQbRTAOWkZnN20D2tGZiVnUJR///Yc/8rIaWvJOTl6uJK41ZbT8a/+xH+ALSetNQ7VXAFwqOZGeuzZKozepm7/9vz39XoA4rYewsnLHddinlNxWw9hKeF9KOTJ29iz4GesGUXfv8TlQ4rHskkHBmut2wF9gNeUUgqYChzSWodqrSef72z8FuUzwJdG25clbVgp1R7bdPvzI5X5K4bFwKNa6/bAE8A7FZxXAbUD/TlxPDr3+skTMdQO9C/Q5+ChIzRp0pD69etgNpu5+ab+1K0bWGRb994zjN9+X1OZ4V5VnP19yDwZl3s9MyYBJ3/fon2ijT45VnKS03DwufwKYeeA6qQbBR5ARkw8zgE+hfr4kBGTkNcnOgHngOq514On3cF1WxfgP6Q7h+d+BYBbwwAcvdxp9+0zdFzxEv5De1ZqHi4BPgXySI9JwKVQHi4BPqTnyyM9Oq+Pe8MAfDo3o9uvL9L5u2fwCg0uchsBN3cl+ru/KimDglz9fUiLzsvHEpOAa777/HLmEuCD5RIfC0t0fJE+Pl2akXEmibT/Yis34FJwCfAhvdDjUVxOlvzPr5i8nHY/8wktnh7B9VvepsWzI/h39hdVE3g+rv7VOZcvh3PRCbj6l/455dO6Ae6BPpxcFVUZ4VWeyj9J+GVHjnksGwXMVkr1BKzYfmOyVgVtuwfwndY6DUAp9aPx1wPoBiyz1akAOBcbnO03MccCKLMXJpN7BYVWVGJiEo88Oo2lny3EatVs2BBJcMP6BfoMH34rHdqH0CdsSKXFIa5uh1/6ksMvfUn98bdQ574B/PfKMpTZRLWQYLbe9gJmFyc6/PICSVsOYDkcY+9wi6UczDhW9+DvgTPwatuQtksmsrbj+Nx2r3aNsFoySP33hB2jvLYEDu6WO+p4pas/Kpzdz/4fMb9sIuCmLoTMG8s/t8+2d1ilpxTtnx3B3xMX2TuSS3cF7nYuLykey2YEUANor7XOUkodAVwucRvZFBz5vdj6JiBRax16sQ3n/41MB6fal7RP6cFxoxg9egQAkZFR1Mk3ili7TgAno4t+Q//5lwh+/iUCgDGjR5BjzftJzbC+PZg2dTx9w4aQmVn1u4KuVBmxCTjV9su97hTgQ2ZsfNE+gX5kxiSA2YTZ043shJSqDrVYde7tR+BdYQAkRx3CpbYvSUabc4BvgVFGgIyYhAKjkc6BPmTEFN3tFvvNn4R+Po3/XllGRkwC8WdTsaZlYE3LIPGfvVRrWb9Ci8f69/aj7l19AUg08jiv8MgWFB0BcwnM65MeHU+sMakkadshtFXj5FuNzHjbYxZ4S+UXMg3vCSdoRB8AErYfxi3Ql/PPKtcAHyzF3OeXi/r3huc+FklRh3Gt7cv5aEvzWLgG+hboo8wm/G/oxPrw6ZUee0ka3BtOvRHnn1+HcQnMe365lpCTa/7nV0BeTnVv75k7eSbmx38Iee3+yg4fgCb3XE8j4zkVH3UY90Bfzhht7oE+WEq5+9zRwwWvZnUI/+YpAFxreNH7o8dYe8+8y3/SzDVYPMpu67LxAk4bhWMf4PxQWwpQ0n7Dwm1HgHYASql2QJCxfB1wi1LKVSlVDbgRQGudDPynlA/clOsAACAASURBVBpqrKOUUiEVl5LNwnc/pkPHfnTo2I8ff/ydu0fY5vt07tSO5KRkYmNPF1mnRg3bG563txfjxo3i/Q9sP6sZGtqSdxbMYfCt93LmTHyR9UTJUqMO4hoUgHPdmihHB/xu7k7C75EF+pz9fTM1b+8NgO//upK0vuhMeHs58eEKNoVNYVPYFM78ujl3l7Jn+8Zkp6SRWeh4p8zTiWSnWvBs3xgA/6E9OfObbRKDa1DeoRI1BnQk7YBtxv6Z3yLx7twUZTZhcnXCs11jzh2o2Nn8Rz9ckTuZ5dSvkdQ28vBu34jslDQyCuWRYeTh3b4RALWH9uTUb7bH7dSvkfhe1xIA9+AATI4OuYUjStmOvavk4x0PfRTByvDprAyfTvSvkdQf2gMAn3aNyEqxFHts4+Xi6IcRuZNcbI+FLfbSPxY9OPXbltx2v56tST0QXaRAq0pHPoxg3fXTWHf9NGJ/i6Tu7UZO7RqRVUJOWakWvNvZcqp7ew9if7fllB57Ft9uzQHw696Sc4erZlf8/o9Wsjz8KZaHP8WJ37YQdJttwqRfu4ZkJqeVeGxjYVkpFr5u9SDfd57E950nEbf10JVROILtOOzyXq4wMvJYNp8BPymldgKRwL8AWut4pdRfSqldwK/AgnzrrAGmKqWigJeAb4CRSqndwEZgv7GNrUqpL4HtwGlsv2l53ghgoVJqBuAIfGH0qxTLf13FgAF92bf3L9IsFsaMeSy3LXLzCjp07AfYTufTpk0LAF6c9ToHDhwG4OWXnsbDw50vltp2Qxw/fpLBtxY/o9NeJj87h83bdpCYmEzYLXfx0Oi7GXJjf3uHBTlWDk9/jxZLn0aZTZz6YjWW/cepO/lOUrcf5OyKSE4tXUXjt8bT9u+3yU5MZf+4vNnG7TYtxOzhisnJAZ8BndgzbCaW/SeoP+Nu/Ab3wOTqTPstizn9+UqOv/ZVpaYSv3IbfmFt6brxTayWTPZMWJjb1mnVy2wKs83+3jflfeNUPY7Er4oi3jjuqdGM4bg1CkRbraSfiGPf5CUApB04Sfzq7XRe8wpaa6I/W825f49XWh5nVm6jZlgovTa+idWSwY4Jead26r5qDuvDpgKwe8oHtMk9VU8UZ4w8ji9dQ5s3xtHjj1ewZmazY3zeIcs+XZtjiY7HcrTol7PKErsqCv+wUAZsmEeOJZPISXm7C6+PmM1KY0Su9Yxh1B3cDbOrE4O2vMWRz9ew57VvqR4STNcPJuHk7UZAeFtaTB5CRO+qmcl/euU2aoSF0nvjG7bTJk3Ii737qpdYHzYNgF1TPiRk/rgijwVAwC1dix3p7bN5Pg7VbK+dWgM7sOmOl0jdX/mnGDttPL/6/mPLKSrf7tueK19i3fW2nHZO/TD3VD2nV0dx2shpxxNLaPnCSJSDGWtGFjsmv1fs7VSmk6uiCAwL4ea/XyPbksmGSYtz2wZFzGJ5uG1Use2MO2lwSzccXJ0YHDmfQ0vXsuO1b6s8XlF2Sl+BFa8ovUvdbX05skT/ae8QKsTm1pMv3ukyZ7FeHd83M1AX73SZSzOZ7R1ChXC9Snb5Wa/8pxRJV8lz6q7oT6v00bAsfbbcn7Ouw56/op5BV8cngRBCCCGEPVwlX4AuhRSPQgghhBBldQWeaqe8ZMKMEEIIIYQoNRl5FEIIIYQoK9ltLYQQQgghSu0anHgsxaMQQgghRFnJyKMQQgghhCi1a7B4lAkzQgghhBCi1GTkUQghhBCirK7BU/VI8SiEEEIIUUbaKhNmhBBCCCFEaV2DxzxK8SiEEEIIUVbX4G5rmTAjhBBCCCFKTUYer3Jf+Pa2dwjltrn1ZHuHUCE67nzF3iGU25QO0+0dQoVwuwq+NztdJYdZWa+CxwKgZaa9Iyi/Dh4J9g7hyiTHPAohhBBCiFKTYx6FEEIIIUSpXYPF49Wxv0AIIYQQQlQJGXkUQgghhCgrLcc8CiGEEEKI0roGd1tL8SiEEEIIUVYy21oIIYQQQpSanCRcCCGEEEKIkknxKIQQQghRVlZd/stFKKUGKKX2KaUOKqWmFtN+j1LqjFIqyriMydc2Sil1wLiMqoiUZbe1EEIIIUQZ6UqeMKOUMgMLgHDgBLBZKfWj1npPoa5faq0fKbSuD/As0AHQwBZj3bPliUlGHoUQQgghyqryRx47AQe11oe11pnAF8DNpYyuPxChtU4wCsYIYECZczVI8SiEEEIIUVbaWv7LhdUGjue7fsJYVtgQpdQOpdTXSqm6l7juJZHiUQghhBDCjpRSY5VSkfkuYy9xEz8BDbTWbbCNLn5c8VHmuegxj0qpBsDPWutWlRGAUupvrXW3yth2eeXPXSnVARiptR5v36iqVsgLIwkICyHbkknkxEUk7jxSpE/LqUOpf1sPnLzd+b7R6Nzlfl2aETLzLrya12PjuLc5+cumKovbu08oQTPvA7OJ05+v4uTb3xVoV04ONJ4/Hvc2wWSfTWH/A/PIOHEGh+oeNF0yGY/Qhpz+ci3/PfVe7jr1pg6nxm29cPB2Z2Oju6osl9KYMXse6/7ahE91b77/9F17h3NBg58dRfM+bcm0ZLD0iYWc3H2kSJ+xH0/Fs2Z1TGYThzf/yzdPf4A2du10H9Wf60b2Q+dY2bN6Gz/P+byKM7C54dmRNOkTSpYlk2+eeJeYYvIY+fEUqtX0xmQ2c3Tzv/z09Idoq6b/tOE0u74dOZnZJBw7xbeTF5GenFb1SRTS/7mRNO4TQpYlkx+eWETsriNF+gz/+Ek8anpjcjBzbNM+fjVyulwMzJfD908sIqaYHO4qlMMvl0EOofneazeX8F7bKt977Xf53msbPzCQ4OF9sGbnkBGfTORjS0g7EVeF0du492hPzaceQJlNJC77nYTFywq0u3ZoRa2nxuLcNIjoSXNI+f2v3LY6783ENbQZli17OPHAc1UceTlVwHNHa70YWFxC80mgbr7rdYxl+dePz3f1PWBuvnV7F1p3bTlCBS6DkcfLtXAsTGsdea0Vjv59Q6gW7M9v3R5n6+T3aTfn3mL7xazYxupBzxRZnnYijsgJizj+3d+VHWpBJhPBs+9nz4hZRPWaiN8t3XFtUqdAl1rDwshOSmVbt0eIXvwz9WfcDYA1PYtjc5dyZOYnRTabsGIzOwZNqZIULtUtg8J5d96L9g7jopr3DsUvKIDZvSeybPoSbps1pth+Hz/8Jq8OnMLcfpPx8PEk5IYuADTq2oJW4R1y29Yu+bkqw8/VpHcovkH+vN77Mb6f/h43zbqv2H5fPjyfBQOn8Va/J3H38aSVkceh9Tt5q9+TvD1wKnH/xdDzoZuqMvxiNeoTgm+QP2/3epyfp73PDS8W/3r/+uG3WDxwOu+GT8HdtxotbuhcxZGWrHGfEHyC/Jnf63F+ukAOyx5+i3cHTued8Cm4+VajpZ1z8O8bgkewP792e5wtF3ivjV6xjVXFvNcm7jzKygEziAibxomfN9FmxrDKDrkok4lazz7Eifuf4fCgcXj+rxdODesW6JIdc5qYqfNI/nltkdUT3v+GmMmvVlGwFcxqLf/lwjYDjZVSQUopJ+BO4Mf8HZRSAfmu3gTsNf7/HeinlKqulKoO9DOWlUtpi0ezUmqJUmq3UmqFUspVKRWqlPrH2L/+nREUSqm1xigdSik/pdQR4/+WSqlNxhTyHUqpxsbyVONvb2Pdr5VS/yqlPlNKKaNtkLFsi1JqvlKqxE8MpdRzSqmPlVJ/KqWOKqVuVUrNVUrtVEr9ppRyNPq1V0r9YWzz9/N3vLF8u1JqO/Bwvu32Pn+7SqlOSqkNSqltSqm/lVJNjeX3KKW+NW7ngFJqbjEh5o91oTE8vVsp9Xy+5cXmq5RyV0p9YNyP25RSpT1gtkwCB7Tn6LI/AUjYehBHTzdcanoX6Zew9SDppxOLLE87EUfS3uNV/o3eo20jLEdiyTh2Cp2VTdwP6/Hp37FAn+oDOnH6q7UAxP+8Aa8erQGwWjJI2fQv1vSsIttN3XqArGLyvBx0CG2Nl2c1e4dxUa36dSDy23UAHN12ENdqblSrUfQ5lZFqAcDkYMbs6GCbIwh0GxHOqoU/kJOZDUBqfHLVBF5I837tifrW9to4se0gLtXc8ChFHtr4DdyDf+7EmmP7wDi+7SBe/r5VFHnJmoa3Z/s3tpxObjuIs6cbHsW83jOL5FSlYV5Q/hxObDuISwk5FH1cqjTMIgq/1zpd4nvtmb/3kGPJzO3jGuBTuQEXw6VNEzKPRpN1PBayskn+ZR0e13ct0Cfr5Gky9h0ptlhK27Ad6zlLFUVbwSp5wozWOht4BFvRtxf4Smu9Wyk1Uyl1/pvneKOW2A6MB+4x1k0AXsBWgG4GZhrLyqW0xWNjYIHWuiWQCAwBPgGmGPvXd2KbCn4h44A3tdah2KaMnyimT1tgItACCAauU0q5AIuAgVrr9kCNUsTbEOiLrfr+FFijtW4NWIAbjALyLeA2Y5sfALOMdT8EHtVah1xg+/8CPbTWbYFngNn52kKBO4DWwB35DlotzlNa6w5AG6CXUqrNRfJ9Clitte4E9AFeUUq5X+zOKCtXfx/SovNGwi0xCbgGVK+sm6swzv4+ZJ7M22WTGZOAU6EPZ2d/HzKjjT45VnKS03DwufyLryudZy0fEvM9pxJjE/DyL/6Dbuwn05i5ZREZ59LZvvwfAGoEBxDcqRkTvn+Rh798hrptgqsk7sKq1apOUnTe+29ybAKe/sW/NkZ9MpVpW94l45yF3cs3FmlvP7Q3+9dGVVqspVXN34fkfI9NSmwC1WoVn9OIT6bw+NaFZJxLZ28xOdmLZ6EckmMT8Cwhh7s+mcLkrQvJPJfOHjvnUPi9Nq0c77VBw3oTu2Z7RYVWao61fMmOzXvfzY6Nw7GW/b8UXS201su11k201g211rOMZc9orX80/p+mtW6ptQ7RWvfRWv+bb90PtNaNjMuHFRFPaYvH/7TW59/dtmArzry11n8Yyz4Gel5kGxuA6UqpKUB9rXVxXzE2aa1PaK2tQBTQAGgGHNZa/2f0WVqKeH/VWmdhK2rNwG/G8p3GNpsCrYAIpVQUMAOoo5TyNvJaZ/T/vxK27wUsU0rtAl4HWuZrW6W1TtJapwN7gPoXiPN2pdRWYJuxjRYXybcfMNWIeS3gAtQrvNH8B95GpB28wM0LcflaPPIlnuv0IA5ODjTuZjvk2mQ24+blwZu3zOCn2Z8xcsFEO0d5cR+PnMPLnR7CwcmR4G4tC7T1evhmrDk5bP/+rxLWvjx9NvJl5nV8GAcnB4IK5XSl+HTky7zW8WHMV3AOhdUbch3VQ4LZ9459Due4ZlX+bOvLTmlPEp6R7/8coOh4ep5s8opSl/MLtdafK6U2AjcAy5VSD2itV1/kdsp6EvMM4zatSqksrXN3SliNbSpgt9a6wJi6UTyWxgvYRjMHG5Nq1ha+bUOJOSilgoAngI5a67NKqY/Id3+VQAFDtNb7LtQp/4G3XweMuKQdMg3vCSdoRB8AErYfxi3Ql/Pfh10DfLDElOu8olUiIzYBp9p+udedAnzIjI0v2ifQj8yYBDCbMHu6kZ2QUtWhXhOuu7sfXYb1BeD49kN4B+aNRnj7+5AUW/IelOyMLHZFRNIqvAP71+8kKTaenb/bJl4d234IbdW4+1TjXBU8dp3vDqfDMNtr4+T2w3gF5o2Yevr7kBxb8msjOyOLvRFbaB7egUPrdwHQ9raeNA1rx4fDZ5W4XmXrMDKcdnfacorecRjPfI9NNX8fUk6VnFNORhb7VmyhSb/2HDZysoeOI8Npb+RwslAOnv4+JF8gh2wjh2Z2yKHhPeEEl/Be61aG99qaPVrSfMLNrB38IlbjsI6qlHUqHgf/vPddB38/sk7FX2CNq8hlNGGsqpR1wkwScFYp1cO4fjdwfhTyCNDe+P+28ysopYKxjajNB37Atqu2NPYBwUaRBrZdwuW1D6ihlOpqxOaolGqptU4EEpVS3Y1+I0pY34u8mU73lDEGT+AckKSUqgUMzBdbSfn+Djya71jQtmW87RId+iiCleHTWRk+nehfI6k/1PYQ+7RrRFaKpdjjbS43qVEHcQ0KwLluTZSjA343dyfh98gCfc7+vpmat/cGwPd/XUmy44ff1e6v/1vBa4Om8tqgqexcEUmHW207Keq3bUR6ShopZwo+p5zcnHOPgzSZTTTv247Th6IB2LkikkZdbKNENYICMDs6VEnhCLDx/yJYMGg6CwZNZ8+KSEJvtb026rRtREaKhdRi8vDIl0fTvqGcMfJo3KsNPR74H5+OeZWs9Mwqib84kZ9EsHjQdBYPms6+FZGEDLHlVPt8ToVe745uzrnHECqzicZ92xJv5GQvmz+J4N1B03l30HT+zZdDnRJycMqXg8nIIc4OORz6KIKI8OlEhE/nZDnfa71b1af93NH8Neo1Mux0HHD6zv04NQjEsU4tcHTA84aepK76xy6xVDVttZb7cqUpz88TjgLeVUq5AYeB89PDXgW+Ms5R9Eu+/rcDdyulsoBYCh4nWCKttUUp9RDwm1LqHLYDPstFa52plLoNmK+U8sJ2P7wB7Dby+EAppYEVJWxiLvCxUmoGBXO8lBi2K6W2YTt+8jjwl7H8Qvm+YMS5QyllAv4D/leW2y+N2FVR+IeFMmDDPHIsmUROWpTbdn3EbFaGTweg9Yxh1B3cDbOrE4O2vMWRz9ew57VvqR4STNcPJuHk7UZAeFtaTB5CRO8qmK2cY+Xw9PdosfRplNnEqS9WY9l/nLqT7yR1+0HOrojk1NJVNH5rPG3/fpvsxFT2j3s9d/V2mxZi9nDF5OSAz4BO7Bk2E8v+E9SfcTd+g3tgcnWm/ZbFnP58Jcdf+6ry8ymFyc/OYfO2HSQmJhN2y108NPpuhtzY395hFbF3zTaa9wll+h9vkmXJYOnkvNMKPb58Dq8NmoqTmwuj35uMg5MDymTi4Ibd/P1ZBACbvlrDnXPHMfn3V8jJymbp4+/YJY/9a6Jo0ieUx/54nUxLBt9OznttPLx8NgsGTcfRzZm73nscBydHlElxeMMeNn+2EoD/PX8PDk6O3PvpNMA2aebHpz6wSy7nHVgdRaM+oTyybh5Zlkx+fCIvp7HLZ7N40HSc3Jy5473HcnM6smEPkZ+usmPUBR1YHUXjPqGMN3L4IV8O45bP5l3jcRmWL4f/LoMcYldFERAWykDjvXZzvvfa8IjZROR7r61nvNfesOUt/jPea9s8PRwHdxe6Lp4AQNrJOP66Z17VJpFj5dTMhdR9/0Uwm0j6egWZB4/hN/4u0ncdIHX1RlxaN6b2gqcxe3rg0aczfuPv4r8bHgSg3udzcQqui8nNhYbrPiF2+hucW7+1anMoq2tw5FFpe08zKwWllIfWOtUYcVsAHNBav36x9a5UFZnvpe62vhwFkm7vECpEx52v2DuEcpvSYbq9Q6gQbvY/S1m5OWll7xAqxJU35lK8lvYbQK4wratd/ocllUaz/cur9MWROuXWcn/Oerz87RX1gr5S3kHvNyaJ7Ma2y3jRRfpf6a61fIUQQogrU+X/tvVlpzy7rauMMepWYORNKXUvMKFQ17+01g9zmTEmCjkXWny31npncf2Ly1cIIYQQl6ErcLZ0eV0RxWNxjHMVVcj5iiqb1vry+QkGIYQQQlScK3DksLyu2OJRCCGEEMLe7P276PZwpRzzKIQQQgghLgMy8iiEEEIIUVbX4MijFI9CCCGEEGV1BZ7ku7ykeBRCCCGEKKtrcORRjnkUQgghhBClJiOPQgghhBBldQ2OPErxKIQQQghRRlfCzzxXNCkehRBCCCHKSkYehRBCCCFEqUnxKK42Dczn7B1CuSVlFf5Z8CvTlA7T7R1Cub0cOdveIVQInRxn7xDKzZp82t4hVAhVzc/eIVSIuLuu/Ne3JcnR3iGIK4QUj0IIIYQQZXQt/jyhFI9CCCGEEGUlxaMQQgghhCi1a+8HZuQk4UIIIYQQovRk5FEIIYQQoozkmEchhBBCCFF6UjwKIYQQQohSuwaPeZTiUQghhBCijK7F3dYyYUYIIYQQQpSajDwKIYQQQpSV7LYWQgghhBCldS3utpbiUQghhBCirGTkUQghhBBClJaW4vHqopTyBoZrrd+5QJ8GQDet9ecX2VYD4GetdasKDPGy49m7LfWeHwNmE3FLI4hd8G2BduXkQNAbE3Fr05DssykcfvBVMk+czm13CvSj5Zq3iJ73BacW/QBA6w2LyTlngRwrOjuHvTc8USW5NJl1D75hbcmxZLB3/EJSdv5XpE+1NkG0mP8QJhcn4ldtY/9THwEQPOV2/AZ0AKsmMy6JPeMXknnqLADe3VrQ5IVRKAczWQkpbB38fJXkAzD42VE079OWTEsGS59YyMndR4r0GfvxVDxrVsdkNnF487988/QHubtVuo/qz3Uj+6FzrOxZvY2f51zwaV+lZsyex7q/NuFT3ZvvP33X3uFc0PrIHbz87v+RY7Vy64DejLn9xgLt0afieOb1JSQkpeBVzZ2XJj+Ifw0fok/FMfGFN7BqTXZ2DsNvCuf2G8LsksNfUf/y8kffY7VaGdy3M6NvKRhHTNxZZixYSkqaBatVM2H4DfRo2xyA/UejeWHJ16Ra0jEpxeezJ+Ls5GiPNGyPxaLPsFqt3Nq/F6Nv/1+B9uhTcTzzxvucTUrGq5oHsyc/gL+fD/8eOsqLCz7mXJoFk8nE/XfcxIBene2SQ2HOXTriNfERlNnEuR+Xk/p/Swu0e9x5G243DYKcHHISk0ic9Qo5safsFG0et+4d8Js2Dsxmkr/+lcT3virQ7tK+FX7TxuHcJJjYJ2ZzbsV6ABwCa+I//xmUyQQODiR99gPJX/5ijxREKV3VxSPgDTwElFg8Ag2A4UCFfYoqpRy01tkVtb0qYzJR78UH2D/8WbJi4mn+yyskrthE+oETuV387gwnOymVXd0fpPpN3akzfSSHH3o1t73Os/eRtGZrkU3vHzqD7LMpVZIGgG9YKK5B/mzoMgHP9o1pOnc0kQNnFOnXdO4Y9j6+mOQtBwj5fCq+fUOJXx3F0QU/cfhl2xtfnTEDCHp8CPuefA8HTzeazRnNtmGzyTgZj6OfZ5Xl1Lx3KH5BAczuPZH6bRtx26wxvHlL0Zw+fvhNMlItANyzcBIhN3Qh6qcNNOraglbhHXh14BRyMrPx8K262EvjlkHhDB9yE9NfePXine0oJ8fKrAUfs3j2FPz9fLhzwjP06dyOhvVr5/Z59b3PuTGsOzeH92Bj1G7e/OgrXpo8jho+3nw671mcnBxJs6QzeNw0endpR03f6lWbg9XK7A++ZdFTD1DL14vh096gd4eWNKzjn9tnybcr6d81lNv7dePQiVgemfMev749g+ycHKa//TmzHh5O0waBJKacw8HBXKXx5+aRY2X2O5+weNaT1PLzYdjE5+jdpS0N6+U9Fq+9/wU3hl3Hzdd3Z2PUHuZ/uIzZkx/AxdmZWY+PpX5tf07Hn+XO8c/SrX0rPD3c7ZJLLpMJ78cnEDdhMjmnz1Dzg4Wk//k32UeO5nbJ3H+Qc/c+iM7IwH3wTXg+PJazT79gx6ABk4kaMx7m5JhpZJ+Ko+6Xb3FuzT9kHTqW2yU75gynp7+G9723FVg1+0wCJ4ZNgqwslJsL9X5YxLnVG8g5k1DVWZRNFYw8KqUGAG8CZuA9rfWcQu2PAWOAbOAMcJ/W+qjRlgPsNLoe01rfVN54rvZT9cwBGiqlopRSrxiXXUqpnUqpO/L16WH0maSUaqCU+lMptdW4dCvNDSml7lFK/aiUWg2sUkr5KKW+V0rtUEr9o5RqY/QraflzSqmPjds+qpS6VSk114j1N6WUo9FvjlJqj7F+hX7Kuoc2JuNIDJnHTqGzskn4YT3e/Qp+E/fu14n4ZWsAOPvL31Tr3iavrX9nMo+fIn3/8YoMq0xqDOhI7LJ1ACRvOYCDpztONb0L9HGq6Y2DhyvJWw4AELtsHTUGdgQgxyi+AMxuLqBtI3e1bu3O6eWbyDgZD0BWXHKl53Jeq34diPzWltPRbQdxreZGtRreRfqdLxxNDmbMjg5gHMvdbUQ4qxb+QE6m7XtNanzVxV4aHUJb4+VZzd5hXNTO/YeoF1iLugE1cXR0YGCvLqz5Z0uBPoePRdM5tAUAnUJasGaDrd3R0QEnY4QuMysLq7bPgfa7Dh6jbi1f6tTyxdHBgQHd2rJ28+4i/VIt6ba/aenUqG77srFhx34a1wugaYNAALyruWM22eejZNf+w9QLrEUd47EY0LMzazYU/PJ6+NhJOofYRkw7hTRnzT+29gZ1/Klf21Ys1/Stjo+3J2eTqu4LbkmcWjQj+8RJcqJjIDubtJWrcelZ8GMoc2sUOiPD9v/uPZhr1rBHqAW4tG5K1rFosk/EQlY2qb+uxaNv1wJ9sqNPkbn/P7AWqraysiErCwDl6Ah2ej6VlbaW/3IhSikzsAAYCLQAhimlWhTqtg3ooLVuA3wNzM3XZtFahxqXcheOcPUXj1OBQ1rrUOAfIBQIAa4HXlFKBRh9/jTu1NeB00C41rodcAcw/xJurx1wm9a6F/A8sM14IKcDnxh9SloO0BDoC9wEfAqs0Vq3BizADUopX2Aw0NJY/8VLuzsuzCnAh8yYuNzrmbHxOAX4FOzjn69PjpWc5DQcqlfD5OaC/0ODiZ73ZdENa03jz5+j+fLX8BvRryJDLpFzQHXSjQIPICMmHudCuTgH+JARk/fNNiM6AeeAvBGg4Gl3cN3WBfgP6c7hubZRSLeGATh6udPu22fouOIl/If2rORM8njW8iExOi+nxNgEvPx9iu079pNpzNyyiIxz6Wxf/g8ANYIDCO7UjAn/z959h0dVtA0c/s2mQUjvoZfQEUJHOoYmvkpRxIKgrygCCiIiUlQs8IEFFEWkKHZeEeyKSlOKCIQaOoQa0iuBtM3ufH/skmSTACEkMF4QkQAAIABJREFUWcpzX9de2Z3znHOeyUn2zM7MOfvDG4z55mVqNK9bIXnfbOITUwjyz/+9B/r5EJeUYhPToG5N1mwOB2DtP+FcyMwi9ZylYRKbkMSgUVPoNexZ/jv4rgrvdQSIT04jyDf/g0eArydxKWk2MaMG9+HXjTvoNeo1xsxawouPDQTgVHQCSimemrGQIZPmsPTHdRWae0FxSSkE+tkei/jCx6JOTdZstjTe1/6zw3osztvERByOxJibS43ggPJP+goM/n6Y4vOnApniE3Hwv3Tj0PXufmRv2VYRqV2WQ6AvxtiEvNe5sYk4BPiVeH3HIH9qfL+A2uu+JHXJ8hun1xEsPY/X+ri8dsAxrfVxrXUO8D+gf8EArfV6rXWG9eW/QPVrrdbl3OyNx4I6A8u01iatdRzwN9C2mDgnYLFSKgL4Fksrv6RWa60v/sV3Br4A0FqvA3yVUh6XKQdYpbU2YuledgB+t5ZHYBleTwOygI+VUoOAi38odlf1uQeIW/wz5oysIssODZrMwTsncPSR1wgYfidu7a/mV2o/x//vGza3GkPsyk1U/29fAJSDAfcWddk9dDa7H5hJnecGUblusJ0zLWrRsP9jertRODo7Ur+jZZquwcEBV0833hswjZ9nfsWw+c/aOcub1/MjHiQ84hCDx0wjPOIQAb7eGKy9KUH+vny3YCa/fvw2P63ZRGKhRtv1YtXmXdzTrS2rF7zM/BdHMPWDZZjNZkxmE7sOneD/nnmYT197mnXb97E14oi9072kCSMeYMe+Q9z/9EsFjoXKW56QnMqUtxfx2vgRecfoRlG5T0+cGzUg/atiPrTfYHJjEzgzcBSn+j6Ge/9eOPgWHVW5hVUDCg7pRVnLLuVxYFWB15WUUuHW0c4BZZHQzT7nsTTGA3FYeigNWBprJXXhGvedDaC1NiuljFrnjWmZAUetda5Sqh0QBtwHPI2lp9KGUupJ4EmAyV4tGFSldol2nhOTjHNw/idF5yBfcmJsP/3lxFpijDFJ4GDAwcOV3JR0qrRsgPddHak+dTgOHlVAmzFnG0n49DeMsZZt5Calkfr7VqqE1uf81gNX83spkeqP9abqUMuk/3O7I6lUzZeLp2WXYF+bXkaA7Jhkm95Il6o+ZMfY9loAxK7cSOjXkznx1rdkxySTlHIec0Y25oxsUv89iHvTWmQejynz+gB0eqQ3HR60HOIzeyLxquqbt8wryIe02Et/Os/NNrJvdTjNerXhyKYI0mKTiPjD0kNxek8k2qyp4uPOhWT7D9XdSAL8vIkt0CsSl5hMYKHewwBfb959aRwAGZlZrN60vchcugBfb0JqVWfnvsP07tKu/BMvuG8fT2KTUvNexyelEejtaRPz/fqtLJj8BAAtGtQm22gkJf0CAT5etG5cF28PNwA6t2zMwRNnaX9bg4qrgFWgrzdxibbHonBPboCvN3OnjQUsx2LN5vC8Y3E+I5Mxr8zhmeH30aJRSMUlfhnmhEQcAvJ7QB0C/DAlJBSJc2nbCvdHHyZx9Pi8IV97MsUl4RSU30PqGOSHKT7xMmtcYjsJyeQcO0ml1s3yLqi53pXF1dYFz9tWi7TWi0qxnaFAG6BbgeJaWuuzSqm6wDqlVITWOvJa8r2xPmZdvXTg4iSqjcAQpZSDUsof6ApsKxQD4AnEaK3NwCNYegBLYyPwMIBSqjuQqLU+d5nyK1JKuQGeWuvfsDRyWxQXp7VepLVuo7VuU9KGI8CFPUepVCcY5xoBKCdHfPp3JnW17XBI6upt+A7uAYD3XR1J32yZg3v43ilE3P4kEbc/SfzHPxPz/goSPv0NQ2UXDFUqAWCo7IJH11AyD5+mPEQt/ZNtYZPYFjaJhFXb84aUPVrXJzc9g5z4VJv4nPhUcs9n4tG6PgBBg7uS8Pt2ACrXyb9wwL9vWzKOngUg4fdwvNo3RDkYMFR2xqNVfS5Yl5WHzV/8yTv9XuSdfi8S8Wc4bQZZ6lSrZQhZ6RmkJ9jWydnVJW8epMHBQOM7WhEfGQ1AxJ/hhHRoaqlTnWAcnByl4VgKzRrU5VR0LFGx8RiNuaz6+1+6d2hlE5OSlo7ZOq9ryTc/M7C35X08NiGZrOwcANLSL7DrwBFqV6/4nuum9WpwOjaRqPgkjLm5/P7PLrq1aWoTE+znzdZ9lvnAx6PiyDHm4uPhRqcWDTl6OobM7BxyTSZ2HIikbvXACq8DQNMGdTgVHUdUbAJGYy6/b9hK9w4tbWJsjsXyXxjY2/I/ZDTm8uzr87g7rBO9Oxc3CGUfOQcP4VijGg7BQeDoiGvPO8jauMUmxqlBCF4vPEfSxGmYU1IvsaWKlbXvME61quFYLRCcHHG7szsX1v9bonUdAv1QLs4AGDzcqNSqKcYTUVdY6/pRFnMeC563rY+CDcezQI0Cr6tby2wopXoCU4F7tNbZeflpfdb68zjwF9Cy8LpX66buedRaJymlNiul9mHpwt0L7MFyCcELWutYpVQSYFJK7QE+xXJl9kql1DAsw8al7U2cDnyilNqLZXh5+BXKS8Id+FEpVQlQwHOlzK14JjOnX1pMg69eAYMDSd+sIevIGao+/yAX9hwjbfV2Ev+3hjrvPUuzTQswpaYTOfqdy27S0d+LkCUvAqAcHEj+YQPn/tpVpmkXJ2nNLvzCWnL71vcwZ+ZwYNyCvGXt1s5mW9gkAA5P+th6qx4nktbuJmntbgBCpj2Ea0hVtNlMVlQihycuBiDj6FmS1u2h/fq30FoT/dU6LhyqmAuEDq7fReMeoUz5+z2Mmdksm5h/O5sJv83inX4v4uxaiceXTMTR2RFlMHBsy37++Wo1ANuWr+eBN59i4h9vYTLmsmzC5W5CUPEmvjKL7bv2kpp6jrABQxn9+CPce3cfe6dVhKODA1NGDeOpaW9hMpkZ2LsrIbWq88HnK2naoA49OrRi+96DvPfpcpRStG7WkKmjLf/mx8+c5e3Fy1DKcg3W8EF30qBOjSvssXzqMPm/gxg1cxFms2ZA93aE1Ahi/vLfaVq3Ot3bNGPCI3fz2sJv+fLXDSileG3UAyil8HBz5ZH/dOOhKe+iUHRp2YiurewzFcVyLB5h1LS3MJnNDLAei/lffEeT+rUtxyLiEPM+/RYFtGrWkKljhgHwx8at7Nx3mLT08/y0xtLD9fr4ETSqV8sudcljMpP6zvv4vTsbDA5c+GUVuSdO4v7EoxgPHiFr0z94PD0S5VoJnxmvWFaJiyf5haJ3XqjovBNmzKfq4pkog4Fz3/9JzrFT+Dw9jKz9R8hY/y8uzRoQPO9lDB7uVOnRgdynh3HmnidxrlsTvxeesJyZFaQuXUHO0ZP2rc9VqID7PG4H6iul6mBpND6A5S4xeZRSLYGFQF+tdXyBcm8gQ2udrZTyAzphezFNqShtp6v9RMUIrz7ghj/AaUYXe6dQJn6trK4cdJ2bHT7T3imUCX3u6ofTrjfmc/FXDroBKPeSX1RxPUscOsXeKVyzzDT73KuzrIUc+KNC32zjune/5vNs4F9/XTZnpVQ/4F0so6GfaK1nKKVeA8K11j8ppdYAtwEX51Cd1lrfY71jzEIs098MwLta64+vNd+buudRCCGEEOJGZ52u9luhspcLPO95ifX+wdKoLFPSeLxKSqk+wOxCxSe01gPtkY8QQggh7Ee+nlBckdb6D+APe+chhBBCCPvT5ht/StLVksajEEIIIUQpSc+jEEIIIYQoMa1vvZ7Hm/0+j0IIIYQQogxJz6MQQgghRCnJsLUQQgghhCgxuWBGCCGEEEKU2K34XSsy51EIIYQQQpSY9DwKIYQQQpSSDFsLIYQQQogSk8ajEEIIIYQosVtxzqM0Hm9yzo4me6dwzbKNN8enOtebYIqxPpdo7xTKhPLws3cK10xlpNk7hTJhcPO2dwplIvKEr71TuGZuTjn2TuGGdCv2PN74ZzMhhBBCCFFhpOdRCCGEEKKUbsWvJ5TGoxBCCCFEKck3zAghhBBCiBIzS8+jEEIIIYQoqVtx2FoumBFCCCGEECUmPY9CCCGEEKV0K96qRxqPQgghhBClJDcJF0IIIYQQJXYr9jzKnEchhBBCCFFi0vMohBBCCFFKcqseIYQQQghRYrfirXqk8SiEEEIIUUpywYwQBbh1a0W1l58ABwPJ36wmYcEKm+XK2ZEac56jcrN6mFLTOfX0mxij4vHq3w3/kYPy4io1qs3R/zxL1oETFZp/kxnD8Q9riSkzm71jF3Au4mSRGI/mdWgxbxSGSs4krN3Fgamf5S2r9Xgfaj3WG20yE79mF4df/5qq93ai7ui782Lcm9RkU8/JpO8/VRFV4q5XhtGgRyjGzBxWPv8RMftPFokZ9tkk3AO8MDg4cGr7IX5+aSnarOkz+SEa9WyFKSeX5NNxfDdxIVnnMiok74s2he9l9kdfYDKbGdS3OyPuv9tmeXRcIi/PXUxyWjqe7lX4v4mjCPL3IToukWdffxez1uTmmnjonl7cf1dYheZeUtNmzmHD5m34eHvxw5cf2TudS9q06wCzP1mB2WxmUFhHHh/U22Z5TEIy097/gvSMTEwmM88O7U+X1k0x5pqYvuArDh4/g8lk5u7u7RgxqI+dagGbtu5g1rwlmMwm7r2rNyOG3mezPDo2npdmzSM5NQ1PD3dmTXuOoAA/AN5ZsJQNW8IxmzW3tw1l8tgnUKp8e5HqvfEYPmGtMGVmc2TcfM5HFH1fdGtel4bvjcFQyZnktTuJnLYUAEcvNxovHE+lGv5knUng4JNzyE27QPXR9xAwqAsAytGAa/3qbGn6OE6+HjReOD5vu5VqBXDqzW84u/i3cqmbR/eWVJ9uOWckLVtN3IcrbZYrZ0dqvzueyrfVw5SSzonRb5ETFY9z9QCarP+ArMizAFzYeYQzUxaUS47l4VYctr7uLphRSnkppUZfIaa2UuqhEmyrtlJq32WWP6qU+qA0eZbF+tc1g4Fqrz3FiUenc6TXGLzu6YpLSA2bEJ/7e2NKO8/h7iNJ+PhHgl98FIDUH//maL9xHO03jjPj55BzJq7CG47+YaG41gnm7w7Psu/5xTR7c0Sxcc3efJyICYv4u8OzuNYJxv+OUAB8OjUhsG8bNt0xiY3dJnJiwS8ARK/czKawF9kU9iJ7np5PxumECms4Nugeim+dIOZ2f44fpizhnhn/LTbumzHzmH/nZN7v/QJVfDxodlcHACI3RfB+7xf44M4XSTwRQ9fR91RI3heZTGZmzP+MD1+fyI8LZ7Pqry1EnjprE/P2kq+5O6wz3y2YyVMPDeC9T5cD4O/jxZdzXmHF/Bl8/e50Pl7+C/FJKRWaf0kN6NeLj+a8Ye80LstkMjNz8XIWTB3ND+9OY9WmHUSeibGJWbTid3p3bMXyt1/kzeceY8bibwD4c8tOjMZcvps7lf+9NYkVf27mbHySPaqByWTijbkLWfDWK/z0+Xx+W7uByJOnbWLe/vAT7unTg+8/fZ9Rw4fw7qLPAdgVcZBdEQf5buk8fvjsffYfOsr23Zc8XZQJ77CWVK4bzPbbn+Ho8wsJmf1EsXEhs5/gyISP2H77M1SuG4y39X2pxjMDSN0YwfaOY0ndGEGNZwYAEPXhT+zsOZGdPSdyYsbXpG05QG7qeTIjo/PKd/aehDkzh8RV28qncgYDNd4YybFhr3Lwjqfx7t+FSvVtzxm+D/QiN/U8B7o8RfySn6g2ZXjesuxTsRzqO55DfcffUA3HW9V113gEvIDLNh6B2sAVG4/2opS64Xt0XUPrk3MqhpwzcWhjLqk/b8Cjd3ubGI/e7UlZuRaAtN8249axRZHteN3TldSfN1ZIzgUF9m3D2W83AJC64xiOHq64BHjZxLgEeOHoVpnUHccAOPvtBgLvbANAreG9iHz/R8w5uQDkJJ4rso/ggZ2I+eGf8qyGjca9W7P7O8vvMmrXMSq5u+Lm71UkLvt8JgAGRwccnBzR1jGVYxsjMJvMAJzZdQzPIN8Kytwi4kgkNasGUiM4ACcnR+7s1oH1/+6wiTl+Opr2oU0AaNeiCeu3WJY7OTni7OwEQI7RiPk6HidqE3obnh7u9k7jsvYdO0nNID+qB/nh5ORI386tWL99r02MUooLmVkAnM/IxN/H01KOIiMrh1yTieycHJwcHXCrXKnC6wAQcfAoNasFU6NqEE5OTtwZ1oV1m7baxESePEO7Vs0BaNeqOeuty5VS5OQYMebmkmPMxZhrwte76P9TWfLr05a45X8DkL7zKI4eVXAu9L7kbH1fSt95FIC45X/j17cdAL592hK3/C9r+V/4WssLChjYmfjvNxUp9+7SjMyTsWRHJZZllfJUCa1P9slYck5bzhkpP23Es7dtfl6925O8Yh0AKb9uxr1T83LJpaJpra75caO5HhuPs4B6SqndSqm3rI99SqkIpdSQAjFdrDHjrT2MG5VSO62PjlexvxpKqb+UUkeVUq9cLFRKDVVKbbPuY6FSysFa/phS6ohSahvQqUD8p0qpj5RSW4E3lVKhSql/lVJ7lVLfK6W8rXGXKv9LKTVXKRWulDqolGqrlPrOmtcb1pgqSqlflVJ7rL+TIZQTp0BfjNH5bzLGmCScAn0vHWMyY0q/gIO3h02M53+6kPrT3+WV5iVVCvYh62x+b0hWTDKVgn2KxsQk58dE58dUqReMT/tGdFz1Bu2/fxnP0LpF9hHc/3aiv99cTjUoyj3Qm7To/HzPxSbjEeRdbOzwz19k8o6PyL6Qyf7fthZZ3npwd478tbvcci1OfGIKQf75xyDQz4e4Qr2HDerWZM3mcADW/hPOhcwsUs+lAxCbkMSgUVPoNexZ/jv4LgJ8i6+7uLK45DQC/fJ/f4E+3sQnpdnEjBrSj182bKPnE9MYPWMBkx8fDECv21viWsmZsBFT6T3yZYbfE4ane5UKzf+i+MSkvCFogEB/P+ITbHtBG4bUYc2GLQCs2bCFCxmZpKadI7RZI9q2vI0eAx+lx8DhdGrXknq1bXvKyppzsA/Z0fn5Zcck4Vzofck52IfsmOJjnP09yYlPBSAnPhVnf0+bdQ2VnfHuEUrir0X/5/0HdCLhh/J7v3IK8iWn8Dmj0AdUpyCf/Ji8c4blg5ZzjUAarZpL/W9nUKVdk3LLszxofe2PG8312Hh8EYjUWocC/wKhQAugJ/CWUirYGrNRax2qtZ4LxAO9tNatgCHAvKvYXzvgXqA5MFgp1UYp1di6nU7WPEzAw9Z9v4ql0dgZKPwXXh3oqLV+DvgcmKS1bg5EABcbppcqB8jRWrcBPgJ+BMYAzYBHlVK+QF8gWmvdQmvdDPj9KupZ4SqHNsCcmU32kdNXDr7OKEcHnLzd+OfOaRx67StaLn7WZrlnqxDMmdmcPxRlpwwv77Nhs5jdbjSOzk7U7djUZlm3Mf0xm0zsKccTSWk9P+JBwiMOMXjMNMIjDhHg643BYHmbCvL35bsFM/n147f5ac0mElPSrrA1cS1WbQynf48OrFn8Bh9OHcWUeZ9jNpvZd+wkBoOBNYtnsGrBq3z28zqiYsunN6ssPD/6McJ37+O+x8cRvns/gf6+GAwGTkdFc/xUFGtXfMK6lUvZtnMvO/bst3e6V0UXanX49m7Due2HyE09b1OunBzx7d2GhJ+2VGR6JWaMT2Zf+xEcunM8Ua99Qp33J2Bwq2zvtErMrNU1P2401/vwamdgmdbaBMQppf4G2gKFxxCdgA+UUhcbeg2uYh+rtdZJAEqp76z7zAVaA9utk6crY2mgtgf+0lonWOO/KbSvb7XWJqWUJ+Cltb7Y5fYZ8O2lygus/5P1ZwSwX2sdY93PcaCGtfwdpdRs4BetdbHjwUqpJ4EnAV7yuY373Gtdxa/DwhiXhFPV/E/0TsG+GOOSio0xxiaBgwEH9yqYUvIPjdfdXUn9acNV77u0aj3WmxpD7wAgdXcklarlf+ot3MsIRXsjK1XNj8mKTiL2V8vcoLRdkWizxtnXnZwkSy9Y1QEdif6+/Ies2z/SizYP9gDg7J7jeFbNz9cjyIdzsZee95ebbeTg6h007tWGyE2WuVwt7+tKw7BWLH1oRvkmXowAP29iE/KPQVxiMoGFeg8DfL1596VxAGRkZrF603Y83KoUiQmpVZ2d+w7Tu0vRYTtxZYE+nsQl5v/txCWnEOBr24v1/dotLHhpDAAtGtYlO8dISvoFftsYTqfQJjg5OuDr6U7LRnXZH3ma6kF+VLQAP19i4/MbrnEJiQT4+xaJeW/GFAAyMjJZs+EfPNzdWPHLn7Ro2gBXV0sjpXP71uzZf4jWLWw/bF2r4Mf6EPxwTwDSdx/DpWp+fi7BvuQUel/KiUnGJbj4mJyENJwDvCy9jgFeGAtNp/Hv34n4YkZDfO4I5XzECYyJ5feByxibhHPhc0ZsoXNGbDLORc4ZlvdUU47lZ2ZEJNmnYqhUtxoZe4+VW75l6UYcdr5W12PPY2mMB+Kw9FC2AZyvYt3CHcYaUMBn1p7NUK11Q6319BJs68JV7Lc42daf5gLPL7521FofAVphaUS+oZR6ubiNaK0Xaa3baK3blKbhCJCx5yjOtaviVD0Q5eSI191dObfadqL1udVb8b7XcsWrZ79OnP+nwJwppfC6qzNpP1dc4/HU0j/zLmaJWxVOtcFdAfBqHUJuegbZ1uGei7LjU8k9n4lX6xAAqg3uStzvliHTuFXh+HaynESq1A3G4OSY13BEKYLv6UB0Bcx33PrFaub3m8L8flM48Gc4odYrKqu3DCE7PZPzCbZ1cnZ1yZsHaXAw0PCOUBIiowGo3605XUb+hy9HvI0xK6fccy+sWYO6nIqOJSo2HqMxl1V//0v3Dq1sYlLS0jGbLfMyl3zzMwN7dwMgNiGZrGxLzmnpF9h14Ai1qwdXbAVuIk1DanEqJoGouESMxlx+37ST7m1s558F+fuwde9hAI5HxZJjNOLj4Uawnw/b9lnKM7Ky2XvkJHWqBVZ4HQCaNarP6ahooqJjMRqNrFq7kR6dbOdmp6Sey/ubWvzVCgb2szTkggP8Cd+9n9xcE8bcXMJ376NurbIfto5Z+kfeRStJv28n8H7L37R7q/rkpmfkDUNflGN9X3JvVR+AwPu7kfjHdgCS/gwn8P7u1vLuJFnLARzcXfG8vYlN2UX+AzsT/0PReZBl6cKeo7jUDsa5RgDKyRHve7qQVuickbp6Gz73WT7ge9/VifTNlnOGo48HWEcYnGsG4lKnKtmnY8s1X3Ftrseex3Tg4mzzjcBIpdRngA/QFZgIVCsQA+AJRGmtzUqp4YDDVeyvl1LKB8gEBgD/BTKAH5VSc7XW8dbl7sBW4D3rEPI5YDCwp/AGtdZpSqkUpVQXa+/gI8DflyovaaJKqapAstb6S6VUKlD8JcRlwWQm+uWPqPv5q+BgIGX5GrKPniZw/MNkRhzl3JptJC9fTY05z9Hwr4WYUs9z+pk381av0r4pOTEJ5JyJK7cULydhzS4CwkLptvU9zJnZ7B2Xf8uUzmtnsSnsRQD2T/qE5nm36tlNwlrLPMAzy9bT/N2n6PL3W5hzctk79sO89X1ub0xmdBKZp+IrtE5H1u+mQY9Qnvt7LjmZ2Xw3cWHesjG/zWR+vyk4ubowdMkEHJ2dUAbF8S0H2P7VGgD+8+qjODo78diXky113HWMn6Z+UmH5Ozo4MGXUMJ6a9hYmk5mBvbsSUqs6H3y+kqYN6tCjQyu27z3Ie58uRylF62YNmTracjXm8TNneXvxMpSyzA8aPuhOGtQp3/lppTXxlVls37WX1NRzhA0YyujHH+Heu+13K5viODo4MGXE/Yx6fT4ms2bAHR0IqRnM/GW/0CSkJj3aNuf54QN5dcEyvvhlPUrB608/glKKB/p25aX5XzJw3BtooH+PDjSoXc0+9XB0YMqzIxn5/HRMZjMD+/UkpE5NPvj4K5o2DKFH5/Zs3x3Buws/t/xNtWjKtPFPAdC7e0e27dzLwEefQSlF5/at6N6pfHuyk9fsxCesJW3/fR9zZg6Hn52ft6zVmrfY2XMiAMdeXJx/q551u0lZuwuAM+9/T+NFzxH00B1kRSVw8Mm5eev79WtHyt97MGdk2+zT4OqCd9fmHJ24qFzrhsnMmZcWEfLldJSDgaRv1pJ15AzBEx4iY+8x0lZvI+l/q6n97niabPwIU2o6J8a8DYBb+6YET3gInZsLZs2ZyQswFRp6v57diMPO10oVnjNxPVBKfY1lDuIqa9GdWHoE39Baf6OUcgL+AHyBT4FfgJXWmN+BMVprN6VUbSzDu80usZ9HsTQYPbHMV/xSa/2qddkQYDKW3lmjdZv/KqUes5anAruxzFN8Win1qXVfK6zrh2KZu+gKHAce01qnXKb8L+B5rXW4Uqq79fl/rNv6C3jeWt+3sPREGoFRWuvwy/0u99a++/o7wFcpKtM+k/HL2j+Vb/yO/pfXPXvloBuA8qj4IdayZo6NtHcKZcLgX9PeKZSJLS2m2TuFa+bmVPEjEuWh1ZkfK7Q192/VQdd8nu0Q/d1lc1ZK9QXew9I5tkRrPavQchcs11S0BpKAIVrrk9Zlk4HHsUzrG6u1/uNa870uG4+i7Ejj8fohjcfrhzQerx/SeLx+SOOxdP4Jvveaz7MdY1ZeMmfr3V6OAL2AKGA78KDW+kCBmNFAc631U0qpB4CBWushSqkmwDIsFwdXBdYADazXkpTajX82E0IIIYS4ebUDjmmtj2utc4D/Af0LxfTHchEuwAogTFmu+O0P/E9rna21PgEcs27vmlyPcx7LnFKqDzC7UPEJrfVAe+QjhBBCiJtDWVxtXfAuKVaLtNYXJ6pWA84UWBaF5e4vBeXFaK1zlVJpWKa6VcNy28OC617zJOVbovFoHd+/5jF+IYQQQoiCzGWwDWtDsZyvaio7t0TjUQghhBCiPGjKfYrlWSz3er6ourWsuJgo61cke2K5cKYk6141mfMohBBxy7EZAAAgAElEQVRCCFFKZn3tjyvYDtRXStVRSjkDD5D/pSIX/QQMtz6/D1inLVdE/wQ8oJRyUUrVAeoD27hG0vMohBBCCHGdss5hfBrL9DsH4BOt9X6l1GtAuNb6J+Bj4Aul1DEgGUsDE2vccuAAlm/PG3OtV1qDNB6FEEIIIUrNXP7D1mitfwN+K1T2coHnWVi+uKS4dWcAZfqdtNJ4FEIIIYQopQqY83jdkcajEEIIIUQplcXV1jcaaTwKIYQQQpTSrdjzKFdbCyGEEEKIEpOeRyGEEEKIUpJhayGEEEIIUWLSeBQ3HSena76dk91lZDvYO4Uy4XzlG8Fe98zn4u2dQplQGWn2TuGaGYLq2TuFMmFOjrZ3CmXCgRv/Hzw1x8XeKdyQZM6jEEIIIYQQlyE9j0IIIYQQpWS+9ToepfEohBBCCFFaFfENM9cbaTwKIYQQQpTSjT/b9epJ41EIIYQQopRuxaut5YIZIYQQQghRYtLzKIQQQghRSmYlcx6FEEIIIUQJyZxHIYQQQghRYrfinEdpPAohhBBClNKteJ9HuWBGCCGEEEKUmPQ8CiGEEEKUktwkXAghhBBClJhcMCPKhFKqNvCL1rrZFWI6aq2/tr5uAwzTWo+tgBSvWpUurQmcNhLlYCB1+R8kLfrWZnnlts0ImvokLg3rcHb8LNJ/32ynTIvX4vVhBIe1IDczh/BnF5IacbJITNMXB1Prvi44e1Xhh5DH88r9OjSixWtD8Wxck61PfcDZX7dVYOaX1mf6MOr3aIExM4cfn19I7L6TRWIe+uwF3AK8MDg6cHrbYVa9tBRttt9b3ebdh5j96Q+YzWYG3tGexweE2SyPSUxh2vxlpGdkYjZrxj10F11aNgbgyKloXl+8gvOZWRiU4uuZz+Li7GSParBp1wFmf7ICs9nMoLCOPD6ot83ymIRkpr3/BekZmZhMZp4d2p8urZtizDUxfcFXHDx+BpPJzN3d2zFiUB+71OFKps2cw4bN2/Dx9uKHLz+ydzqXtGlHBLMXL8Ns1gzq1YXHB/ezWR4dn8jL7y0l5dx5PN2qMHPCCIL8fAB46pW5RByOpGXj+nzwyrhyz9WrRyh1X38MHAzEfbWWsx/8YLNcOTvS4P1nqNK8Lrkp5zk8cg7ZZxIAqPbMQAIfugNMZo5P+4TUv/bkr2gw0OKP2eTEJnPwkf8DwLPzbdR++REwKMwXsjg6bj5ZJ2PLpV71ZzyGb1hLzJnZHBj7IecjThSJcW9eh8bzxmCo5EzS2l0cnboUgHovD8Wvd2u0MZfMk3EcHPchuecyqFTDn/Yb55IRGQ3AuR1HOfzC4nLJ/1rJnEdRkWoDD118obUOv14bjhgMBE0fzZkRLxN551N4/KcbziE1bEJyo+OJnjSHtJ//sk+OlxF0Rwvc6wbxe8cJ7Jz4Ma1mPVZsXMyfu1jX7+Ui5RlRiYSPW8iZ7/8p71RLLKRHC3zrBPFBtwn8Mvlj7nqj+DqtGPM+i+6cwke9JlHF150md7Wv4EzzmcxmZn7yHR9OfoLv57zA75t3ERllezJb/N0a+tweyvLZE5g9bigzP14JQK7JxJQPvmbaiPv4/p0X+PiV0Tg6OtijGphMZmYuXs6CqaP54d1prNq0g8gzMTYxi1b8Tu+OrVj+9ou8+dxjzFj8DQB/btmJ0ZjLd3On8r+3JrHiz82cjU+yRzWuaEC/Xnw05w17p3FZJpOZmR99xYLp4/lh/uus2rCVyNPRNjHvfLKcu+/oyMr3X2XkA3cz77OVecseHdSHGc+NqJhkDQbq/t8I9j80g11dx+M/sDOVG1S3CQl8KIzc1AvsvP0Zohf+Qu1pQwGo3KA6/gM6savbePY/NIO6s54AQ/7pu+oT/cg8GmWzrXqzn+DImPfY03MiCd9vovr4e8ulWr5hLXGtE8S/HcZy6PlFNHyz+N9nwzef4NCEhfzbYSyudYLwuSMUgJS/97Kt2wS29ZhIRmQMtcYOzFsn81Qs28NeYHvYC9dtw/FWdUs2HpVStZVSh5RSXymlDiqlViilXJVSYUqpXUqpCKXUJ0opF2v8SaXUm9bybUqpEGv5p0qp+wps9/wl9rVRKbXT+uhoXTQL6KKU2q2UGq+U6q6U+sW6jo9S6gel1F6l1L9KqebW8unWvP5SSh1XSlVIY7Ny8wbknIrGeCYWjLmc+3UD7mG328QYz8aTffgk6OvvpgVV+7bm1LcbAUjeeQwnD1cqBXgViUveeYys+NQi5RlRiaQdPGPXHrvCGvZqzZ6Vljqd3XUMFw9X3IqpU875TAAMjg44ODmi7ViFfcdOUyPQl+qBvjg5OtK3Y0v+2r6/SNz5zCzLz4ws/L09ANiy9wj1awbTsHZVALzcq+BgsM/b175jJ6kZ5Ef1ID+cnBzp27kV67fvtYlRSnEhrx6Z+Pt4WspRZGTlkGsykZ2Tg5OjA26VK1V4HUqiTehteHq42zuNy9p39Dg1gwOoHuRvORZd27F+6y6bmOOnY2jf3NJ73a55I9Zv3Z23rEOLJlSpoN+/e8sQsk7Ekn06Hm3MJeGHzfj0aWsT49OnLfHL/wIg8ZcteHa+La884YfN6Jxcsk/Hk3UiFveWIQA4B/vg3bM1cV+ttd2h1ji4uQLg4O5KTmxKudTLr28bYr/dAFh6Bx09quBc6L3IOcALB7fKnNtxFIDYbzfgf6el7sl/70WbLOeNtB1HcKnqUy55lidzGTxuNLdk49GqIfCh1roxcA54DvgUGKK1vg3LkP6oAvFp1vIPgHevYj/xQC+tdStgCDDPWv4isFFrHaq1nltonVeBXVrr5sAU4PMCyxoBfYB2wCtKqXIft3MM8iU3JjHvtTE2EcdA3/LebZmpHORDRnR+705mTDKVg73tmNG1cw/y4VyBOqXHJuMeWHydHv58EhN2LiD7QhYHf9taUSkWEZ+cRpBv/kklwNeTuJQ0m5hRg/vw68Yd9Br1GmNmLeHFxyy9EKeiE1BK8dSMhQyZNIelP66r0NwLiktOI9Av/3cd6ONNfFKhegzpxy8bttHziWmMnrGAyY8PBqDX7S1xreRM2Iip9B75MsPvCcPTvUqF5n8ziUtKJdAvv7ER6OtNfJLtB8AGdWqwZssOANZu2cmFzCxSzxX5nF/unIN9yInOfx/NiUnCJdinSEz2xRiTmdz0DBx93HEpZl1n67p1Xn+Mk69/gS70yfDYhI9o8tUU2uxcSMDgrpx9//tyqZdLsA9ZZ/Nzyy6mXi7BPmTH5L9fZUUXjQGo+tAdJK3Nb9xXrhlA2zWzafn9dDzbNyqH7MuGLoPHjeZWbjye0VpfnJj3JRAGnNBaH7GWfQZ0LRC/rMBP2263y3MCFiulIoBvgSYlWKcz8AWA1nod4KuU8rAu+1Vrna21TsTSMA0svLJS6kmlVLhSKnx52umrSFXcjL4aNps5bcfg6OxInY5N7Z3OZa3avIt7urVl9YKXmf/iCKZ+sAyz2YzJbGLXoRP83zMP8+lrT7Nu+z62Rhy58gbtZNXGcPr36MCaxW/w4dRRTJn3OWazmX3HTmIwGFizeAarFrzKZz+vIyo28cobFKU24b+D2bHvCPePm074vsME+HpjsFOvdVnz7tUaY2IaF/YeL7Ks6pP/4cDDMwlvNZL4/62nzqvD7ZBhydV6diA610ScdUQlOy6Fza1Gs73nJI698hlNF4zFwa2ynbMsnlld++NGcytfMFO4sZ8KXK47TRfzPBdrA1wpZQCci1lvPBAHtLDGZpUm2QKyCzw3Ucwx1FovAhYBHKzf75o/1OTGJuEY7Jf32inIj9y463Oe1kX1Hu1FnYd7AJC85ziuVX25mHHlYB8yY8pnCKc8tRnWi1YPWOoUvfc4HlXz/1zdg3xIj7t0nUzZRg7/uYMGvVtzfNO+cs+1OAE+nsQW6BWKT0oj0NvTJub79VtZMPkJAFo0qE220UhK+gUCfLxo3bgu3h5uAHRu2ZiDJ87S/rYGFVcBq0AfT+IS83/XcckpBPgWqsfaLSx4aQwALRrWJTvHUo/fNobTKbQJTo4O+Hq607JRXfZHnqZ6kB/i6gX6ehGXmJz3Oi4phQBf2yHTAF9v5k6xHIuMzCzW/LMTD+twbkXKiUnGuWr+cXYO9iU7JrlIjEtVP3JiksHBgKO7K7nJ6WQXs25OTDI+fdrg07st3mGtMLg44eDmSv0PxnLilU9xbVqL87ssw8QJP/5D02VTy6wu1R7rQ9Whlovd0ndHUqmaH2kcBsClmHplxyTjEpz/flWpqm1M0JBu+PVqza77Xssr0zm55OZYeojT954g82QcrvWCSd9TtKFsbzfisPO1ujk+fpVOTaXUxR7Eh4BwoPbF+YzAI8DfBeKHFPi5xfr8JNDa+vweLL2MhXkCMVprs3WbF2f5pwOXmlC0EXgYQCnVHUjUWp8rUa3KQWbEEZxrV8WpeiA4OeJxV1fS1/5rr3RKJPLT1azpNYU1vaYQvSqcWoO7AODTKgRjemaxcxuvd+Gfr2ZRvyks6jeFw3+G0+JeS52qtQwhOz2T84Xq5OTqkjcPUjkYqH9HS5Iio4tst6I0rVeD07GJRMUnYczN5fd/dtGtjW1PaLCfN1v3WU54x6PiyDHm4uPhRqcWDTl6OobMbMt8wR0HIqlbvUine4VoGlKLUzEJRMUlYjTm8vumnXRv09wmJsjfh617LSfT41Gx5BiN+Hi4Eeznw7Z9lvKMrGz2HjlJnWr2qcfNoGn9OpyKjiMqNsFyLDZso3u7UJuYlLR0zGbL6X3Jt78xsGdne6RK+u5jVK4bjEvNAJSTI/4DOpH853abmOQ/wwm4vzsAfv+5nbTN+6zl2/Ef0Anl7IhLzQAq1w0mfdcxTs38mvBWI9nRdjSHn3qXtM37OPr0PHJTz+Po7kqlusEAeHVtTsaRs2VWl7NL/8i7kCVh1TaCBlsG6Txa18eUnkFOofeinPhUTOcz8WhdH4CgwV1J/D0cAJ8eLag1pj97h83GnJmTt46TrzsYLF1ylWoF4Fo3mMxTcWVWB3FtbuWex8PAGKXUJ8ABYCzwL/CtUsoR2A4UvD+Ft1JqL5aevwetZYuBH5VSe4DfgQvF7OdDYKVSalihmL2Aybrup0DBWd7TgU+s+8sA7DveYDIT++oCanzyhuVWPSv+JOfYafzGDSUr4ijn122l0m31qf7hSzh4uOHWoz3+Y4dyvN+oK2+7AsSu3U1QWCh9t8zBlJlD+PiFect6rp7Jml5TALht2oPUGNgRh8rO9NvxPie/Xs+Bd77Du0Vdbv9kPM5ergT3akmTifeyuvske1UHgKPrdhPSI5SnN8zBmJnDT8/n1+nJ32ayqN8UnF1dGLLkORydnVAGxcktBwj/cu1ltlq+HB0cmPzfQYyauQizWTOgeztCagQxf/nvNK1bne5tmjHhkbt5beG3fPnrBpRSvDbqAZRSeLi58sh/uvHQlHdRKLq0bETXViWZAVI+9Zgy4n5GvT4fk1kz4I4OhNQMZv6yX2gSUpMebZvz/PCBvLpgGV/8sh6l4PWnH0EpxQN9u/LS/C8ZOO4NNNC/Rwca1K5ml3pcycRXZrF9115SU88RNmAoox9/hHvvvr5uK+To4MCUpx5m1CtzMZnNDOjZmZBa1Zj/5Q80qV+bHu1D2b7vMPM+W4lSilZNGzB11MN56w+fNIuTUTFkZGXT89HneXXso3Rqdck7rF0bk5njU5bQdNk0cDAQv2wdmYejqPnCEM7vjiT5z3Divl5Lgw/G0mrL++SmnufwSMt0+MzDUST+9A8tN7wLuSYiJy8B82X6u0xmjj3/EY0+fh7Mmty0Cxx9dn65VCtpzS58w1px+9Z5mDJzODjuw7xlbde+yfawFwA4PGkJjeeNxqGSM0lrd5O01nLKa/B/j2NwdiR0+UtA/i15vDo0oc4L96NzTWA2c+iFxeSmFneKtb9bsedRFZ5keysoyX0YC8WfBNpY5xneUMpi2Nre9p+/sS9uuehAcZMabjAv/PjglYNuAMrRxd4pXDNDUD17p1AmzMn26w0vS+Fdr+Y6yutTtr45BiPviFteobMIP6ox9JrPs0+d+fKGmvl4K/c8CiGEEEJck1ux5/GWbDxqrU8CJR6b0FrXLrdkhBBCCCFuILdk41EIIYQQoixIz6MQQgghhCixG/7CglK4OWbHCiGEEELYgb1vEm79SuPVSqmj1p9FrjJVSoUqpbYopfZbv/p4SIFlnyqlTli/Lnm3Uiq08PqFSeNRCCGEEKKUroPvtn4RWKu1rg+stb4uLAMYprVuCvQF3lVKFbyj/kTr1yWHaq13F7O+DWk8CiGEEELcuPpj+UplrD8HFA7QWh/RWh+1Po/G8vXG/qXdoTQehRBCCCFK6TroeQzUWsdYn8cCl/3aKqVUOyxfpxxZoHiGdTh7rlLqijfClcajEEIIIUQp6TJ4KKWeVEqFF3g8WXAfSqk1Sql9xTz62+Ri+eaXS17Do5QKBr4AHrN+bTLAZKAR0BbwAa74FWpytbUQQgghRCld6wUvAFrrRcCiyyzveallSqk4pVSw1jrG2jiMv0ScB/ArMFVr/W+BbV/stcxWSi0Fnr9SvtLzKIQQQghRStfBsPVPwHDr8+HAj4UDlFLOwPfA51rrFYWWBVt/KizzJfddaYfSeBRCCCGEuHHNAnoppY4CPa2vUUq1UUotscbcD3QFHi3mljxfKaUigAjAD3jjSjuUYWshhBBCiFKy903CtdZJQFgx5eHACOvzL4EvL7H+HVe7T2k83uSysp3sncI1q2y+Ob78yXwTdPQrdz97p1AmDG5F7qF7wzEnR9s7hTJh8Klq7xTKhFL2bkJcOx+XLHuncEMy2735WPGk8SiEEEIIUUo3R/fG1bnxu0KEEEIIIUSFkZ5HIYQQQohSuvUGraXxKIQQQghRarfisLU0HoUQQgghSqksbhJ+o5HGoxBCCCFEKd2KV1vLBTNCCCGEEKLEpOdRCCGEEKKUbr1+R2k8CiGEEEKUmlwwI4QQQgghSuxWnPMojUchhBBCiFK69ZqOcsGMEEIIIYS4CtLzKIQQQghRSjLn8SallKoN/KK1blbB+z2vtXa7ivjpwHmt9duFymtTQfm7d2tJ9elPoBwMJP1vNXEfrrTN0dmRWnPH43pbPXJT0jk55i1youJxrh5A43UfkBV5FoCMXUc4M2UBACHfvIFTgA/mrGwAIodOJzcprbyrQpMZwwkIC8WUmcOesQs4F3GySIxH8zq0mPcUDpWciV+7mwNTPwOg5aKxVKkXDICTRxWM5y6wKWwyTt5utP74WTxD6xH1v7/ZP+XTcq/Hpdw5fRj1e7TAmJnDD88vJGbfySIxQz97AbcALwyODpzedphfX1qKNttvkGVT+F5mL/wKs9nMoD7dePz+/9gsj45L5OV3PyYl7Rye7m7MnDiSID8fDkWe4o35n3EhIxODwcATQ+6hb7f2dqoFbNq6g1nzlmAym7j3rt6MGHqfzfLo2HhemjWP5NQ0PD3cmTXtOYIC/AB4Z8FSNmwJx2zW3N42lMljn0Cpir/L8KYdEcxevAyzWTOoVxceH9zPtg7xibz83lJSzp3H060KMyeMIMjPB4CnXplLxOFIWjauzwevjKvw3Etq2sw5bNi8DR9vL3748iN7p2PDq0codV77LzgYiP96LWc/+N5muXJ2pP68sVRpXpfclHSOjJxDdlQCjt5uNFw8EbfQesR/8xcnpi7JW6fx19NwDvBGOTpwbusBjk9eAubybdq4d2tFtVdGoBwcSPrfn8QvKHrOqDlnPK63hZCbco5TT1vOGQCVGtWmxv+NxuDmCmYzR+6ZgM42opwcqfbaSNw6NAOzJubtL0hbtaVc63EtZM6juLUZDNR4YyTHHn4FY0wSDX9+m7TV28g6eiYvxHdIL0xp5znQ9Sm87u5C1cnDOTnmLQCyT8Vy+M7xxW765Lg5ZO49ViHVAPAPC6VKnSD+6jAer9YhNHvzcf6586Uicbe9+V8iJiwmdccx2n49Cf87WpCwbg+7npyXF9N4+lCM5zIAMGcbOTzrW9wb1cC9UfUKq09h9Xu0wKdOEPO6TaB6yxDueuMxlgx4pUjct2PeJ/t8JgD3fzSOpne1Z9/P/1Z0ugCYTGZmfvg5i2a8QKCfDw8+O53uHVpSr2a1vJh3Pv4fd4d1on/PzmzdfYB5S79l5sSRVHJxYcaEJ6lVLYj4pBQeGPsKHVs3w8Otih3qYeKNuQtZPOc1gvx9GfLkBHp0bke92jXzYt7+8BPu6dOD/neGsXXHHt5d9Dmzpj3HroiD7Io4yHdLLX9fw55+ke2799Gu5W0VXAczMz/6ikWvTyDQ15sHn3ud7u1DqVezal7MO58s5+47OtI/rBNb9xxk3mcrmTnhCQAeHdSHrOwcVqz6u0LzvloD+vXioXvvYcrrb185uCIZDNSd+QT7h7xGTkwSzVfNJvnP7WQeicoLCXwwjNy08+zq+DS+/TtRa9ojHHlqDuYsI6ffXIZro5q4Nqxps9kjT76Dyfr/3nDJRHzvvp2kHzeXaz2qvz6SyIdfxhibRIOf3iFtzTayC5wzfKznjIPdRuJ1dxeCXxzOqaffAgcDtd59jlPj55B18CQOXu5oo8lS96cHk5uUyqEeo0ApHLxK3AdjF7de0/HWmvPooJRarJTar5T6UylVWSkVqpT6Vym1Vyn1vVLKG0Ap9ZdSqo31uZ9S6qT1eVOl1Dal1G7rOvWt5UMLlC9USjlc3KlSaoZSao91P4HWstpKqXXWbaxVStUsnKxSqrV1vT3AmALlxeZQFlxD65N9Mpac03FoYy4pP2/Es3c7mxjP3u1JWrEOgNTfNuPeqXlZ7b5MBfZtzdlvNwKQuuMYTh6uuAR42cS4BHjh6FaZ1B2WRu3ZbzcSeGebItsKvqcD0d//A4ApI5uUbYcxZ+eUcw0ur2Gv1uxZaalf1K5jVPJwxa1Q/YC8hqPB0QEHJ0e0Hd/l9h05Ts2qgVQPDsDJyZG+XduzfstOm5jjp8/SvkVjANq1aMz6fy3La1cPola1IAACfL3x8fIgJS29YitgFXHwKDWrBVOjahBOTk7cGdaFdZu22sREnjxDu1aW/412rZqz3rpcKUVOjhFjbi45xlyMuSZ8vYset/K27+hxagYHUD3I33os2rF+6y6bmOOnY2jf3Hosmjdi/dbdecs6tGhClcqVKjTn0mgTehueHu72TqMIt5YhZJ6MJdv6Xpv44yZ8+rS1ifHu24745X8BkPTLFjy7WD5gmDOzSd92CHOWsch2LzYclaMDysmR8v6Ht5wzYsg5U+Cc0ct2RMCzV3uSVxY8Z7QAwL1rSzIPnSTr4ElL7qnpeb2kPvf3JH7+CssGtMaUYp//dXFpt1LjsT4wX2vdFEgF7gU+ByZprZsDEUDRrhtbTwHvaa1DgTZAlFKqMTAE6GQtNwEPW+OrAP9qrVsAG4AnrOXvA59Z9/sVMI+ilgLPWNe9bA4lqn0JOAf5khOdmPc6JyYJp0BfmxinIB+MF2NMZkzpF3Dwtrw5O9cIpOFvcwlZPoMq7ZrYrFfr7WdouGougWPvL6t0L6tSsA+ZZ5PyXmfFJFMp2KdITFZMct7rzOikIjE+HRqRnZBGxonY8k34KnkE+XAuOr9+52KT8Qj0LjZ26OeTmLhzATkXsjjw29ZiYypCXFIKgX75v99APx/ik1JsYhrUqcmazTsAWPvPDi5kZpF67rxNTMThSIy5udQIDij/pIsRn5iUNwQNEOjvR3xCkk1Mw5A6rNlgGWZbs2ELFzIySU07R2izRrRteRs9Bj5Kj4HD6dSuJfVq16jQ/AHiklJtj4WvN/FJqTYxDerUYM0W67HYsrPYYyFKxyXIh5yzBd9rk3EO8i0aU/C99lwGjj5Xbgg3XvYSbSM+wXQ+k6RfyneUwSnIF2NMfj2MMYk4BRU+Z/gWe86oVKcaaE3dz6fT4Ne5BIwcBICDh2U0Iej5h2nw61xqfzgJR7+K/4B1Ncxl8LjR3EqNxxNa64sfnXcA9QAvrfXFcZfPgK5X2MYWYIpSahJQS2udCYQBrYHtSqnd1td1rfE5wC8F9lnb+vx24Gvr8y+AzgV3opTysua2oUDM5XKg0PpPKqXClVLhK8+fvEKVyoYxPpn9HUZwuN94zr7+CbXnTcDgVhmAU2PncKj3OI7eNwW3dk3wubdHheRUFqoO7JjX63ij+nLYbN5pOwYHZ0fqdGxq73Qua8KIB9ix7xD3P/0S4RGHCPD1xmDInw+YkJzKlLcX8dr4ERgM1+/b1/OjHyN89z7ue3wc4bv3E+jvi8Fg4HRUNMdPRbF2xSesW7mUbTv3smPPfnunW6wJ/x3Mjn1HuH/cdML3HbYei+v3dy4sDj74OttDR2BwccKzc4VO8786jgaqtG3CqXHvcPTeSXj27fD/7N13fBTV2sDx37ObTgiQhEBCr9I7IoIIBGzXxmtvV7E3UFRUil0seC3XDnpt19712qgqiCK9Sa/SkpCENFJ3c94/ZpJsGiGbkM3C8+WzH3Zmzsw+Z7Kze/a0IXxIL3A6CIpryqHlG9n8jwkcWrGRuCljfR3tYZla+Odvjqc+j3kez93A4X7KuCgpWBe3zRhjPhSRP4F/AD+IyE2AYNUiTqrgOAXGFLcbuKmF811RDMaY+WXSzARmAqxsfd4RvyvzE1IIiiupUQmKjaIgsXSNSkFCKoFx0RQkpIDTgbNhg+ImBXe+9X/O2m3k7dpPcPsW5KzZSkGiVbtXeCiHg18vIKx3J1K/+Ln6ma9Cm7GjaXXlSADSV20ntEUURfVaZWsZoXxtZGhcVKk04nTQ/B8n8tvoybUeqzcG/nM0/S+1Ct5712wnIq7kF35E80gyEg9WtiuuvAI2zV5Ol9P6s/23dUc91oo0i2pCYnLJ+U1MTiUmqnRtaUxUE56fOh6A7Jxc5i5aVtyvMSs7h9seetPRhBcAACAASURBVI5xV19I7y4d6y7wMmKio0hIKqltSTyQTEzTqHJp/j3Net9kZ+cwd8HvRDQM5/PvZtO7e2fCwqwfVkMH9Wf1Xxvp37tuC/XNohqX/lukHCQmqvRHYkxUE56fbPWYyc7JZe7vK4gID6vTOI9VeQmpBLXw/KyNJD8hpXyauGjy96dan7URYbhSj6z51uQVkDprCZGnn0j6gjW1GrungoQUAmNL8hEYa383lE1TwXdGwf4UDv35V/H3R8bPywnt0YGsRWtwZ+cWD5BJ+34RkZeMPmp5qA3+WHNYU8fzz8h04KCInGIvXwUU1ULuxKpNBCgeRiki7YHtxpgXgW+AXsA84EIRibHTRIpImype+3fgUvv5FcBCz43GmDQgTUSGeqQ5XAy1Inv1FoLbxRLUKgYJDKDJOaeQPmdJqTTpc5YQdaFVQGt81hAyf7c+mAIiI8CulQhq3YzgdnHk70qwPizsZm0CnESMGkjO5r9rK+RSdr09h9/iJ/Fb/CQSf1xGi4usP23j/h1xZWaTl1S6WS4vKQ1XVg6N+1sFkRYXnULiT8uLt0cP60nWln3lCp2+svS9Obx+1mReP2syG2cvo/cFVv5a9u1IXmYOWWXyFxQWXNwP0uF00GlkX5K37avzuIt079yOXfsS2ZNwgIICFz8t+JPhJ/UtleZgeiaFdr+nNz/9jjGnWY0BBQUu7nzsRc6JH8JpQweWO3Zd6tGlE3/v2ceefQkUFBTw47yFjBhSup/XwbSM4ny88cHnjDlrFACxMU1ZtuovXC43BS4Xy1ato32bum+27t6p7N9iCcNP7FM6D55/i89+YMyooRUdSnkha9VWQtvFEmx/1kafN5TUWctKpTk4aykxFw8HIOrswaRX8aPPERZCYFG/Z6eDJvH9ydm692iEX8z6zogjqFWz4u+MjDmlu8ZkzF1C5AXlvzMyf11BSJc2SEgQOB2ED+pePNAmY+4SwgdbfTwbDulVagBOfVSIqfHD3xxPNY8VuRp4XUTCgO1AUd34v4BPReRG4HuP9BcDV4lIAZAAPGGMSRWRqcBsEXEABVgDXHYd5nXHAW+LyETggMfrehoLvCUiBph9uBiqlePDcRey54GZdPjvw9ZUPZ/MI3fzbprfdTnZa7eSMWcJKZ/Moc0LE+i24HVcaZnsvN0axdhgUHdi774cU+CCQsPuya/hTs/CERpMx/cfRgICwOkg87fVpHw4+/Bx1IKkuStpGt+H4X++gDsnjzV3zCjeNnTek/wWb1UUr7vvbXq/eDOOkCAOzFvFgXklgwJizx9cYZP1iKUvEtAwFEdQAM3OHMCSS54ka/PR/ZAua8v8VXQa0YfxC56jICefb+4pyd/NPzzB62dNJjAsmMvevIuAoEDEIez4Yz3L3p9Xp3F6CnA6mXzLVdwy9RnchYWcf9owOrZpySv//ZJundoy4qR+LF27kRff+QwB+vU4gSm3/ROAWQv/ZMW6TaRnZvHt3N8AeGzC9XTpUNXvtKOQjwAnk++8iZvueRh3YSFjzhpFx3atefk/H9D9hI6MGDqIpavW8sKM9xAR+vfuztQJNwNw2vCTWbJiDWOuGYeIMHRQP4YPObGKVzwKeXA6mXzzFdzy0PPW32LUUDq2acEr739t/S0G9WHpuk28+O4XiAj9undmyi3Fv2G5+r6n2LlnP9m5eYy65h4eGX8NQ/rVvybSiQ89xdKVa0hLyyD+/Cu59bqruOCc030dFrgL2T75Tbp99ADidJD48XxyNu+m1cRLyVq9lYOzl5H40Tw6vTSevr+/jCsti803P1+8e78lr+EMtz6DIs84kfWXPYorNZOu705C7Os9fdE6Et6bddTzsefBGbR/z/rOSP10Lrlb7O+MNVvJmGt/Zzx/F11/nYErLdMaaQ24Mw5x4M1v6Py/58AYMn5eTsZ8qwC976l3afP8XTgfvB5Xajp/3/Pvo5sPVW1ifDn8Uh111Wm2rq/25R0bTWVLQ/y/on/S/HG+DqFWOMIrHlzkTwrTD/g6hFrhiIyrOpEfWNpzoq9DqLGwoPIjuP1Rn13f1unEqbe0vbjG37Ov7fy07id7rYHjveZRKaWUUspr/tjsXFNaeFRKKaWU8tLxOGBGC49KKaWUUl7yx6l2asr/O2EppZRSSqk6ozWPSimllFJe0mZrpZRSSil1xI7HZmstPCqllFJKeel4rHnUPo9KKaWUUuqIac2jUkoppZSXCo/Dm61o4VEppZRSykvHX9FRm62VUkoppbxWiKnxoyZEJFJE5ojIFvv/Cu+/KiJuEVllP771WN9ORP4Uka0i8omIBFX1mlp4VEoppZTykqmFfzV0PzDPGNMJmGcvVyTHGNPHfpzrsf5p4HljTEfgIHBdVS+ohUellFJKKf91HvCu/fxd4Pwj3VFEBBgJfF6d/bXP4zEuPa/K2ud6r1B8HUHt6J7v6whqLvnKyb4OoVZs2xHl6xBqzHmM9LQSOTbyMXDtM74OocZcCz72dQh+qR5M1dPMGLPffp4ANKskXYiILANcwFPGmK+BKCDNGOOy0+wBWlT1glp4VEoppZTyUk37LAKIyI3AjR6rZhpjZnpsnws0r2DXKZ4Lxhgjlf8ia2OM2Ssi7YH5IrIWSPcmXi08KqWUUkp5qTbuMGMXFGceZvuoyraJSKKIxBpj9otILJBUyTH22v9vF5FfgL7AF0BjEQmwax9bAnurilf7PCqllFJKeamwFh419C1wtf38auCbsglEpImIBNvPo4EhwHpjjAF+Bi483P5laeFRKaWUUsp/PQWMFpEtwCh7GREZICJv2mm6AstEZDVWYfEpY8x6e9t9wF0ishWrD+R/qnpBbbZWSimllPKS8fEdZowxKUB8BeuXAdfbz38Helay/3bgxOq8phYelVJKKaW8VBsDZvyNFh6VUkoppbxUD6bqqXPa51EppZRSSh0xrXlUSimllPJSbUzV42+08KiUUkop5SXt86iUUkoppY6Yr0db+4IWHpVSSimlvKQDZpRSSimllDqMY7bm0b5v4z3GmGUi8gNwuTEmrZaOfTOQbYx5rzaOV990nDaWqPh+uHPy2Dj+FbLW7iiXJrxXe7q8eBvOkCBS5q1g65S3AWh6zkm0vediwjq3YMUZk8hcvR2AkFZNGbjwBXK27QMgY/lmNt/7Rp3lqfvjV9Msvg/unHxW3fEa6Wt3lkvTqFc7+vz7ZpwhQSTOW8VfU98FIKJ7G3pNvw5HcCDGXcja+98ibeW2Oou9SJ/H/klsfG9cOfksvXMGaRXkocf9F9HmwlMIatyArzpeV7y+001n0v7yERS63OSlZLDsrjfI3pNch9GXF3zSQBrdeTvidHDo2x/I+u9HpbaHX3ohYeeeBW437rR00qY9gzshsU5j7PD4WCLta2HzHZVfCyf8+zYcIUGkzlvBtqnWtRDQOJyuMyYQ0qopubsPsOHG53ClH6LlrecS83+nACABDsI6teSP7tcRGBVB1xkTio8b0iaGXdM/Ye8bP9QoD41H9KH9Y2PB6SDxg3nsffnrUtslKIDOL42jQa/2uA5msemm58jbfQCAFuPG0OzykeAuZPvUt0j7ZXXJjg4HvWc9TX5CKhuuehKARkN70vbBq8AhFB7KZcsdr5C7M6FG8VeWp3aPXgtOB0kfzmPvy1+Vy1OnF8fbecpk803PkbfnAAFNwjnhjYmE9+lA0ie/sGPKm8X7dP1wKkExTZAAJxl/rmf7pDehsH7UKU194jkWLFpCZJPGfP3+674Op1KLNu1l+ndLKCw0jBnYiWuHl5+TetaancyYtwqAzrGRPHXpMABe+HE5CzftAeDGkb04vVe7ugu8ho7HATPHRc2jMeas2io42sd7/VgtOEbG9yW0XSx/njSOzffMoPP0GypM13n6DWy++3X+PGkcoe1iiRzZB4BDG3ez7tp/kf7HhnL75O5KYFn8RJbFT6zTgmNMfB/C2zdn/uAJrL7nDXo+fV2F6Xo+fS2r736D+YMnEN6+OTEjewPQ7YHL2fzsFywYNYlN0z+j6wOX11nsRZqP7E14++b8ePLdLJ/4H/o9NbbCdPtmr2TeWQ+WW5+2dhdzz5jKnPhJ7PluCb2mXna0Qz48h4PGd99Byl33k3jZWMJGjySgbZtSSfI3b+XA2FtIuuoGcucvIOK2G+s0xCbxfQltH8vSwePYcs8MOj5d8bXQ8WnrWlg6eByh7WNpYl8LrcadT9rCtSw9eTxpC9fSatz5AOx59VtWjJrIilET2THtQ9L/WI8rLYucbfuK16847T4Kc/JJ/nFJzTLhcND+yev56/JprBw2gaZjhhLauWWpJM0uj8eVdogVg8exb8Z3tJ16JQChnVvS9PwhrDx1An9dPo32T90AjpKvjLgbziJny55Sx+rw9A1svu3frB41kQNf/UbLCRfULP7K8vTEDay/YhqrTr2T6PMryNNl8bjSs1h58u3sm/kdbaZeBUBhbgF/T/+InY+W//jefOOzrB51N6uG30lgVCOizhlc+7F76fyzRvP6c4/7OozDchcW8uS3i3ll7Ci+nHAeP63ewbbE0l+7u5IzeOuXtbxz85l8OeF87j17IAALNu5hw74UPhl3Du/fehbvLviLrNx8X2TDK4WYGj/8Tb0qPIpIWxHZKCLviMhmEflAREaJyCIR2SIiJ4pIAxF5S0SWiMhKETnP3jdURD4WkQ0i8hUQ6nHcnfaNwBGRr0VkuYj8JSI3eqTJEpFpIrJaRBaLSLPDxPmwiNxjP/9FRJ6249ksIqfY650i8i8RWScia0RknL0+3o57rZ2PohuV7xSRJ0VklYgsE5F+IjJLRLbZNZ1Frz1RRJbax3ykVv8AQPQZA0n87FcAMpZvISCiAUExjUulCYppTEB4KBnLtwCQ+NmvRJ9p3dkoe8ve4trF+qL56f3Z/elCANJWbCUwIozgMnkKjmlMYHgoaSu2ArD704U0P2MAYHWGDmhovZ0CGoaRm3CwDqO3xJ3Rn12fWXlIXbGVoIgwQsrkoWhbblL530kHfl+POye/OE1obOTRDbgKQd264NqzF/e+/eBykT13PiHDTi6VJn/FKkxenvX8r/U4Y5rWaYzRpw8k8VPrWshccfhrIXOFfS18+ivRZ1jXQtTpA0n89Bd7/S9EnVH+7l8xY4aS9NVv5dY3OaUHOTsTyKth7XDDvh3J3ZFA3t9JmAIXB75eROTpA0uliTx9IEl2nMnf/UGjoT2L1x/4ehEm30Xe30nk7kigYd+OVr5jI2kyqj+JH8wr/YLG4AwPA8DZMIz8o3CthPftaJ2bvxMxBS6Sv/mtXJ6anHFicZ5SvvuDRqdYeSrMySNzyUYKcwvKHdedlQOABDiRwACoR4MgBvTpSaOIhr4O47DW7U6mVVQELSMbEhjg5PTe7fhlw+5Sab5cuplLBp9ARGgwAJHh1ufq9qQ0+rdtRoDTQWhQIJ1jm7Boc/36HjkcY0yNH/6mXhUebR2BZ4Eu9uNyYChwDzAZmALMN8acCIwAnhGRBsAtWE3JXYGHgP6VHP9aY0x/YAAwXkSi7PUNgMXGmN7AAqDiaoaKBdjx3Gm/NsCNQFugjzGmF/CBiIQA7wCXGGN6YnUbuMXjOH8bY/oAC+10FwInAY8AiMhpQCese1D2AfqLyLBqxFml4NhI8vamFC/n7U8huExBIzg2krz9Hmn2lU9TkZDWMfSfO50+Xz1Co0Fdai/oql43NpLcfSXx5uxPJaRMvCGxkeTsTy1ezt2fUpzmrwffo9sDVzBq+ct0e+gKNj7xcd0E7iG0eSTZHnnI3p9KaGwTr47V7rLhJPy8uuqER5GjaTTupKTiZXdSMs6mlRcOw845i7w/algLV01BsZHk7St9LQSVed8Elb0WPNIENW1Evl2Qz09KI6hpo1L7OkKDaDKiD8nf/1nutZueP4QDXy+qlTzk7yspgOZXcD1b+bTTuAtxZWYTENmQ4Ar2Lcpbu8fGsvOx/5b70tt69+t0+2AyA1bMIOaiYex9qXRzcm0Ibh5J/l7PuFIJah5VPo1HntwZVp6q0vWjBxi49i3cWTmkfLe4VuM+1iVlZNO8UYPi5WYRYSSlHyqVZldyBruSM7j69R+46tXvWbRpLwCdmzdh0Za95OS7OHgol6XbEkgss299pjWP9cMOY8xaY0wh8Bcwz1ifUGuxCmOnAfeLyCrgFyAEaA0MA94HMMasAdZUcvzxIrIaWAy0wiqMAeQD39nPl9uvdaS+rGC/UcAMY4zLjikVOMHO32Y7zbt23EW+tf9fC/xpjMk0xhwA8kSksZ3304CVwAqswnUn/EBe4kH+6HcLy0fdy9aH3qXra3fgDA+tesd6oM3Vo/nrof8yt//t/PXQf+n9XN02n9am1hcMoUnv9mx69buqE9cToaePIqhLZzI/+MTXodRI2YJW1GkDyFi6EVdaVqn1EhhA1GkDOPDtH3UZ3hFrMro/BcnpHFqzvdy2uBvPZv0VT7Cs300kffwz7R652gcRem/DZY+xtM/1OIIDaTS0h6/DOea43Ya/kzN484YzeOrSYTz61e9k5ORzcucWDD2hJVe//gP3f7yAXq2b4hDxdbjqMOrjgJk8j+eFHsuFWPG6gQuMMZs8d5IjeKOJyHCsQt1gY0y2PagmxN5cYEo+3d1U79wUxVjd/So7jme+i5YDAAGeNMbMONxB7Ob4GwHuatiPc0LbH/ZF48aeTtyVowDIWLWV4BYlv+KDY6PI86iRA8jbn0pwrEeauPJpyjL5Llz51pdk1prt5O5MJKxDbPGAmtrWduxoWl8xEoC0VdsJiSuJNzQ2ktwy8ebuTy3VlBsSG1WcptXFw4oHz+z/djG9n61OpbT3OlwzmvZXjAAgdfV2wuKiKKrjCouNJGd/9ZoEY07pTtc7zuOXMY9TmO+q5Wirp/BAMs6YmOJlZ0w07gMHyqULHtiPhtdcQfKtE6CgfFNjbYsdezqxV1jXQuaqrQTHlb4W8su8b/LLXgseafIPpBMU09iqdYxpTEFyRql9m543hKSvytcuRo7sQ9baHRQkp9c4P/n7UwmKiy5eDqrges7fn0pwXLQVt9NBQMMwXKmZ5FWwb/7+VCJPH0DkaQNpEt8PR3AgzvAwOr08nh0PvUNY9zZkrbSa8A988zvdP5pS4zyUlZeQSlALz7giyU9IKZ/GI0/OCCtPR8LkFZA6awmRp59I+oLK6iBUWTERYSR41BYmZmQT41ETCdCsURg9WkUT6HTQIrIhbaIj+Ds5gx6torlhRC9uGNELgPs/XkCb6Ig6jb8mdMCMf5gFjBO7tCgife31C7CauBGRHkCvCvZtBBy0C45dsJqEj5Y5wE0iEmDHFAlsAtqKSEc7zVXAr9U45izgWhEJt4/ZQkRiyiYyxsw0xgwwxgyoquAIsO/tWcUDWZJ/XEqzi04FIKJ/J1yZ2cVNb0Xyk9JwZeUQ0d+q9Gx20akk/7T0sK8RGBVR3Nk+pE0Moe1jydmVdNh9amLn23NYMGoSC0ZNIuGnZbS62Brd2rhfRwoys8krk6e8pDQKsnJo3M/607S6+BQSZi0HIDfhIFEndwUgemh3Dm2v/dGjFdn2zhzmjJ7MnNGT2fvjMtpcZOUhsl9HCjJzKuzbWJnGPdrQf/p1LLr6WfJSMqre4SjL37CRgFYtcMY2h4AAwkaNJHdh6Zq2wM4daXzvXaRMnErhwVob73ZY+9+eVTxoJeWnpTS72LoWGvY7/LXQsJ99LVx8KsmzrGshZfYyml083F4/nJRZJdeIs2EYjQZ3K7WuSNMxQ0n6unw/SG9krtpKaPtYglvHIIEBND1/CKmzS79m6uxlxNhxRp89mPRF6+z1S2l6/hAkKIDg1tY1m7lyK7ue+JBl/W5i+cBb2XTzC6QvWseW21/ElZZFQMMwQtrHAtB4WC+yN++tlXx4ylq1ldB2sQS3svIUfd5QUmctK5Xm4KylxXmKOnsw6b+tO+wxHWEhBBb1Z3U6aBLfn5yttR/7sax7y2j+Ts5gb2omBS43s1bv4NSupQcyjejWmmXbrRkTDh7KZVdyBi0jw3EXFpJ2KBeAzftT2ZJwkMGd4uo8D94qNKbGD39TH2seq/IY8AKwRkQcwA7gbOA14G0R2QBswGpCLusn4GY7zSaspuuj5U2gsx1nAfCGMeZlERkLfGYXKpcCRzzvgjFmtoh0Bf6wy85ZwJVArZXCUueuICq+L4P+fAl3Tj6b7nileNuAec+wLH4iAFvue4MuLxZNT7KK1HkrAYg+80Q6PXEtgVER9PxgElnrdrLm0mk0Oqkr7e69BONyYwoL2XzvzHLNdUdL0tyVxMT3YeTiF3Dn5LHqzpKK22Fzn2TBqEkArL3/7eKpepLmryLJnk5izT1v0P2xfyIBTgrzClgz8c0KX+doSpi3itj4Ppz5x3O4c/JZOqEkD6PnPMGc0ZMB6Dn1MlqPORlnaBD/WP4SOz78mfXPfkmvBy4noEEIg2feAUD23mQWXfNcneejmLuQtGdfIvqFp8Hh5NB3P+LasZOGN1xDwYbN5P72OxG334SEhRA5zepG7E5MIvXeqXUWYurcFUTG92Xg4pcozMln050l10K/uc+wYpR1LWy9/42SqXrmr+KgfS3sfukrus68i+aXjyR3zwE23Ph88f7RZ53IwV9XU5idV+o1HWHBNBnWiy0TZ9ZOJtyFbJ/8Jt0/mmpNa/PRfHI27aH1vZeQtWobqbOXkfjhPDq/PJ5+f7yEKy2LTTdZceZs2kPyt7/Td8EL4HKzraqpa9yFbL3ndbr85x4oNLjSD7HF45zVGjtP3T56AHE6SPx4Pjmbd9Nq4qVkrd7KwdnLSPxoHp1eGk/f31/GlZbF5ptLzn2/Ja/hDA/FERRA5Bknsv6yR3GlZtL13UlIUCDiENIXrSPhvVm1H7uXJj70FEtXriEtLYP486/k1uuu4oJzTvd1WKUEOB3cf+4gbnlrLoWmkPMGdKJjsya8Omcl3VpEMbxba07uHMcfW/bxf89/jUOECWcOoHGDEPIK3Fw78ycAGgQHMu3iUwhw+k/dlv8V/WpO/HGUjzpyvzS7yO//wJnij79xyssV//kwrMzJbff7OoRasW1HVNWJ6jnnMfKVJXJs5GPg2md8HUKNuRbU/WDAoyH0/ybXaYfJU1rE1/hNvHDvPL/q5HlsfCsrpZRSSvmAP46WriktPB6GiEwBLiqz+jNjzDRfxKOUUkqp+kULj6oUu5CoBUWllFJKVeh47P6nhUellFJKKS8djzWP/t+DXymllFJK1RmteVRKKaWU8tLxOEm4Fh6VUkoppbykfR6VUkoppdQR0z6PSimllFJKHYbWPCqllFJKeUmbrZVSSiml1BE7HputtfColFJKKeUlHW2tlFJKKaWOWKE2W6tjTT5OX4dQY+kO/88DwIDwVF+HUGM56YG+DqFWhAfm+zqEGkvLD/Z1CLUiMjjX1yHUCteCj30dQo0FDLvU1yEoP6GFR6WUUkopL2mztVJKKaWUOmLabK2UUkoppY7Y8VjzqJOEK6WUUkp5qdCYGj9qQkQiRWSOiGyx/29SQZoRIrLK45ErIufb294RkR0e2/pU9ZpaeFRKKaWU8l/3A/OMMZ2AefZyKcaYn40xfYwxfYCRQDYw2yPJxKLtxphVVb2gFh6VUkoppbxkauFfDZ0HvGs/fxc4v4r0FwI/GmOyvX1BLTwqpZRSSnmpNpqtReRGEVnm8bixGiE0M8bst58nAM2qSH8p8FGZddNEZI2IPC8iVc4DpgNmlFJKKaW8VBsDZowxM4GZlW0XkblA8wo2TSlzHCMilQYkIrFAT2CWx+pJWIXOIDuG+4BHDxevFh6VUkoppeoxY8yoyraJSKKIxBpj9tuFw6TDHOpi4CtjTIHHsYtqLfNE5G3gnqri0WZrpZRSSikvGVNY40cNfQtcbT+/GvjmMGkvo0yTtV3gREQEq7/kuqpeUAuPSimllFJeKsTU+FFDTwGjRWQLMMpeRkQGiMibRYlEpC3QCvi1zP4fiMhaYC0QDTxe1Qtqs7VSSimllJeMj+8wY4xJAeIrWL8MuN5jeSfQooJ0I6v7mlp4VEoppZTyUi3UHPodLTyqck6YdjVN4/vizslj3fjXyFy7s1yahr3a0ePFW3CGBHFg3ko2TXm31PY2N/+DEx65ip+73kBBaiYATU7uxgmP/RNHgJP81EyWjTnsYK5aNeCxq2gxsg+unDz+mDCT1Ary1Pu+i2h/0VCCGjXgk07Xl9ve6qyBnPrmHfxwxgOkrtlRB1GXaHBKf2Km3IQ4HaR9NovUmZ+V2h46oAfNptxI8Ant2DfhKTJnLSre1vLNRwnt04Wc5evZc9PDdRp3WWFDBxA96WZwOsn4/EfS3vy01PaQ/j2InnQzwZ3bk3DPExya/RsAAXExNH/xQcThgIAA0j/4hoxPvvdFFgCIGN6Xlg/fAE4HKR/NIfHVL0ptl6AA2r4wgdCeHXAfzGTHrc+QvyeJoJYxdPv5ZXK37QXg0IrN7J78Wp3G3mnaWKLi+1KYk8f68a+Stbb8e7lhr3Z0ffE2HCFBpMxbyZYpbwPQ4cEriT6tP6bARc7ORDbc8SqujGxCWjVl0MLnyd62D4CM5VvYdO8bRy0PDU/tR4uHrkecTlI+nk3Sa+XPf+vnJhDWsyOugxnsut06/wAhXdrS6slbcYSHQWEhm8+9G5NXgAQG0OLRmwg/qQcUGvb/67+k//jHUcuDp0Wb9jL9uyUUFhrGDOzEtcN7lksza81OZsyz5m7uHBvJU5cOA+CFH5ezcNMeAG4c2YvTe7Wrk5ira+oTz7Fg0RIimzTm6/df93U4qobqvPAoIr8A9xhjlonID8Dlxpi0Wjr2O8B3xpjPa+N4dUlErgEGGGNu92Uc0fF9aNAult9OupNG/TvSbfr1/Hnm1HLpuk2/jvV3zyR9+Vb6fXg/0SP7kDzfCrAdxwAAIABJREFU+mALjosiangvcnYfKE4fEBFG16euZcVlT5K7N4Wg6Ig6y1PcyN40bNecb4bcTXS/Dpz45DX8dPbD5dLtnbOCzW/P4dxF/yq3LaBBCF2uP50Dy7fWQcRlOBw0e+hWdo+dQkFCMm2/eIGseYvJ37a7OIlrfxL773+OyOsuKLd76n++wBESTONLz6rLqMtzOGg69Tb2Xj8JV2IyrT55iUM/L6Zg29/FSVz7D5A0+Vkaj72w1K6uA6nsuWwCFBQgYSG0/mYGh+b/gftAal3nAhwOWj1+E1suf4iC/Smc8N2/SJ+zhNwtJX+PqEtH40rLYv0pN9Pk3FNoMflqdtz6DAB5uxLYeMaEuo8biIrvS1i75iw+aTwR/TtxwvTrWX7mlHLpTph+AxvvnkHG8i30/nASkSP7kDp/FQd/XcP2aR9i3IV0mHoFbcaPYdvjHwCQsyuBpfH3Hv1MOBy0fOwmtl3xIAUJKXT+9lnS5y4hz+P8R14yGnd6FhtOvYnG55xC7P1Xs+v2Z8DpoM0Ld7FrwnPkbtiJs3FDTIEbgGa3X4QrJY2NI24BEZyNw49+XgB3YSFPfruY1687jWYRYVzxyvec2rUVHZo1Lk6zKzmDt35Zyzs3n0lEaDCpWTkALNi4hw37Uvhk3DkUuN1cN3MWQzq3IDwkqE5ir47zzxrN5Recy+THyn+++jtfN1v7gk8HzBhjzqqtgqOqHU3PGMC+zxYAkL58KwERYQTFNC6VJiimMQHhoaTbBal9ny2g6ZkDird3efSfbH70Azxr8mP/bwhJPywhd28KAPnJGUc5JyVand6fHZ9bNVjJK7YR1KgBoWXyVLQtJ6nit2Pvey9k/SvfUZhXUOH2oymkV2fyd+2jYHcCFLjI+H4B4aMGl0pTsDeJvE07obD8qL3sP1ZTeCinjqKtXEjPEyj4ex+uPVY+sn78hfCRpfPh2pdI/uYd5fNR4IIC69xLYCA4fPfR1aBPJ/J2JpD/dyKmwMXBbxfS6LQTS6VpfNogUj+fD8DB7xfRcEgvX4RaTvQZA0iwr++M5VsIiGhQ4fXtDA8lY/kWABI+W0DTMwcCkPrrGozb+tukL99McFxkHUZvCevTibyd+8nfbZ///y2k0ehBpdI0Gj2I1C+s85/2wyIaDukNQMNhfcnZuJPcDTsBcKdlFr/XIi8eRdIrdr2DMbgPZtZJftbtTqZVVAQtIxsSGODk9N7t+GXD7lJpvly6mUsGn0BEqDV3c2R4KADbk9Lo37YZAU4HoUGBdI5twqLN++ok7uoa0KcnjSIa+jqMo8LX97b2hSP6BBaRtiKy0b559mYR+UBERonIIvtG3CeKSAMReUtElojIShE5z943VEQ+FpENIvIVEOpx3J0iEm0//1pElovIX54zq4tIlohME5HVIrJYRKqaOX2YiPwuIttF5EL7GCIiz4jIOhFZKyKX2OuHi8h3Hq/1sl0DiIg8JSLr7RnX/2WvayoiX4jIUvsxpJLz5bDz1thj3RYRaSYi54jIn/Y5mltRfuzzfKHHcpbH84n2a68RkUeqOBfVFhIbWVzAA8jdn0pIbGT5NPtLanxy95WkaXpGf3ITUsla/3epfcI6xBLQqAEDvnyQk2Y/QexFp9R26JUKbd6EQ/tK8nRoXyqhzcvdN75SkT3b0iAukr3zqrzd51ER2CwKV0Jy8bIrIZnAZlE+iaUmnM2iKEgoqY12JSTjjIk+4v0Dmjel1Vev0Xb++6S9+alvah2BwOZR5O8r+XsU7E8hsHlUmTSRJWnchbgzD+FsYn1xBrVqRpcfn6fTZ9NocGK3OosbIDg2kty9JbHn7U8huMz1HRwbSd5+j8+AfeXTAMRdPpIUj2sitHUMA+c+Td+vHqbRoC5HIXpLYPMoCvZ7nv/kCs5/FAUVnP+Qdi3AGNq/9zCdv3+emJv+DwBnRAMAmt9zBZ2/f562r95HQHT5H5hHQ1JGNs0bNShebhYRRlL6oVJpdiVnsCs5g6tf/4GrXv2eRZusbg+dmzdh0Za95OS7OHgol6XbEkgss686+urB7QnrXHWarTsCFwHXAkuBy4GhwLnAZGA9MN8Yc61daFpiz4h+E5BtjOkqIr2AFZUc/1pjTKqIhAJLReQLewRRA2CxMWaKiEwHbuDww8hj7bi6YM199Dnwf0AfoDfWMPSlIrKgsgOISBQwBuhiz9Ze9Cnyb+B5Y8xvItIaa4b2rmX3N8YUisg39jHeFpFBwC5jTKKI/AacZB/3euBe4O7D5MczrtOATsCJgADfisgwY0ylealLjtAg2t8xhuUXTyu3TZxOInq3Z/mFj+MICeLE7x8lfflWsrfvr+BI9YgI/R+6gt/vnOHrSI57roQD7B5zC86mkcS+9DBZsxfiTvGvhouCpFTWDboed1omoT070OHNyayPv53CLN/XDFdHmzvHYFxuEr9YCEBe4kEW9bsV18EsGvZqR893JvLnsLtx17d8BThoMLAbm8+5i8KcPDp+9DjZ67aSs34HQXFNObR8I/see4um159H3JSx/D3heV9HDIDbbfg7OYM3bziDpPRDXDvzJz674zxO7tyCv/amcPXrP9CkQQi9WjfFIeLrcI87x2OzdXUKjzuMMWsBROQvYJ5dAFoLtAVaAueKSNHM5CFAa2AY8CKAMWaNiKyp5PjjRWSM/bwVViEpBcgHimoHlwOjq4jza2PNuLneo1ZvKPCRMcYNJIrIr8BAoLK203QgF/iPXTNZ9PqjgG5ScnFGiEi4MSargmN8AjwIvI11H8lP7PUtgU/sSTmDgOqMvDjNfqy0l8OxzlOpwqNdc3sjwB0NB3BWaIfDHrTV2NNocaU1Uj9j1TZCWpT8ii9bywjlayND4qw0YW2bEdq6KYPnTwcgOC6Sk+Y8yZ9nTCF3fwoFBzNxZ+fhzs7j4OKNNOze+qgVHjtfM4qOV4wAIGXVdhrERVFU59UgLpKchINHdJzA8BAadWnJ6C+sfmGhTRsx/J27+OWa5+ps0ExBYgoBzUtq6AKaR1OQmHKYPeond2IKgc2bFi8HNI/GnZR8mD0qOc6BVPK37iSkf4/iATV1qSAhhaC4kr9HYGwUBQkpZdKkEhQXba13OnA2bFDcDOrOt/7PWbuNvF37CWnfguw1R68vbYuxpxN3pTWLR+aqbYS0iCadTQAEx0aRV+b6ztufSnCsx2dAXOk0zS85lejR/Vl5YcmAN5PvwpVvfQxmrtlBzs5EwjrEkrl6e63npyAhhcBYz/MfXcH5TyGwgvNfsD+FQ3/+Vfy3yPh5OaE9OpC1aA3u7NziATJp3y8i8pKqvmpqR0xEGAketYWJGdnEeNREAjRrFEaPVtEEOh20iGxIm+gI/k7OoEeraG4Y0YsbRljdIu7/eAFt6rA/uTp+VafjUJ7H80KP5UKsQqgAFxhj+tiP1saYDUdyYBEZjlUwG2yM6Y1VOAqxNxeYkmK9m6oLvJ5xVvUTzEXpcxACYIxxYdXufQ6cDfxkb3dg1RoW5bFFJQVHgD+AjiLSFGvG9i/t9S8BLxtjemLVyoZUsG9xXCLiwCpkFuXnSY/X72iM+U/ZnY0xM40xA4wxA6oqOALsfns2i+PvZ3H8/ST9uIy4i6xRfI36d8SVmU1+mX6A+UlpuLJyaNS/IwBxFw3jwE/LyNqwm1+638TCgeNYOHAceftSWTx6EvkH0jnw0zIaD+qCOB04QoNo3K8jh7bsrTI2b21+Zy4/jJ7CD6OnsOen5bS7cCgA0f06kJ+RXWnfxrIKMnP4vMctfD1oAl8PmkDyim11WnAEyF27maC2cQS2bAaBAUT8YxhZ8xbX2evXltx1mwhs04KAFlY+ws8czqGfjywfzmbRSLB1GTgiwgnp152CHXuOZriVOrR6C8FtYwlqFYMEBtDk3FNIn7OkVJq0OUuIvND6QdbkH0PIXGT9Zg6IjCjurxnUuhnB7eLI+zvhqMa79+1ZLI2/l6Xx93LgxyU0t6/viP6dcFdyfbuzcojo3wmA5hcNI/mnZQBEjuhNm9vOY80/n6YwJ794n8CohuCwPm5D2sQQ1j6WnF2JRyU/2au3ENwujqBWzazzf84pZMz5s1SajLlLiLzAOv+NzxpC5u/W+c/8dQUhXdogIUHgdBA+qHvxQJuMuUsIH2yNcm44pFepAThHU/eW0fydnMHe1EwKXG5mrd7BqV1blkozoltrlm23zufBQ7nsSs6gZWQ47sJC0g7lArB5fypbEg4yuFNcncStStSDScLrXG2Otp4FjBORcXaNZF9jzEqsWrHLgfki0gOoqOd4I+CgMSZbRLoAJ9ViXAALgZtE5F0gEqs2dCIQiFWTGIzVFzMe+E1EwoEwY8wPIrIIKPr5PBsYBzwDICJ9jDEVdoSzz8FXwHPABrsJviivRaWmqyvaF9gJ9Ac+xeoWEGivnwU8JiIfGGOyRKQFVuH6cPexrJbkuSuJju/D0D//jTsnj7/uKJlS4aR5T7E4/n4ANtz3Fj1evAVHSBDJ81aRXEV/wENb9pEyfxWDf54OxrDng/lkbaybL/+981YRF9+b835/FldOPn9MKLn3/FlzpvHDaKtWse/US2l7/skEhAYxZtmLbPvoF9Y8+2Vlh6077kISH32NVv95HJwO0j+fTf7Wv4kefyW567aQNf9PQnp2osUrD+CMCCd8xCCix1/Jjn/cAkDrD6cT1L4VjrAQOix4j4TJL3Dot8p6jxzdfByY9gpxbzyBOBxkfDWb/K27iLz9n+T+tZnsnxcT3KMzsS8+iCOiIQ1GnITr9n+y+9wbCWrfmuh7b7AGYQmkvf05+Vt21n0e7HzsfmAmHd9/GHE6SPlkHrmbdxN79+Vkr9lK+pwlpHw8h7YvTKDbwtdxp2Wy4zZrhGn4oO7E3n05xuWCQsPuSa/hTqvs92ftS5m7kqj4fgz+80XcOflsuOPV4m0D500vHi296b436frirThDgkiZt4qUeVZjR+cnr8MRFECfTx8ASqbkaXxSN9rdezHG5YbCQjbe+wautKPU985dyJ4HZ9D+Pev8p346l9wtu2l+l3X+M+YuIeWTObR5/i66/joDV1qmNdIacGcc4sCb39D5f8+BMWT8vJyM+VbBeN9T79Lm+btwPng9rtR0/r7n30cn/jICnA7uP3cQt7w1l0JTyHkDOtGxWRNenbOSbi2iGN6tNSd3juOPLfv4v+e/xiHChDMH0LhBCHkFbq6dadVtNAgOZNrFpxDgrJ83jpv40FMsXbmGtLQM4s+/kluvu4oLzjnd12HViuOx2VqOJNP2LW2+M8b0sJffsZc/L9qG1Qz8AnAyVq3ZDmPM2XYfxrex+htuwJrd/DZ7qp6dwAAgE/gaq/l7E9AYeNgY84uIZBljwu3XvRA42xhzTSVxFsdlL2cZY8LFameeDpyJ9fXzuDHmEzvNdKy+iTuALKx+krOw7g0ZglXb9y9jzLv24J5XsPo5BgALjDE3H+a8DcDqH3qNMeZde915wPPAQWA+MNAYM1w8puqxm9u/wSrQ/mSfr6JzcAclM8ZnAVcaY7ZVFsPsZpf6/bs6yXlsTEc6INw3AzxqU0CA29ch1IqMzIoq/P1LWn6wr0OoFZEhub4OoVac8Hxt13nUvYBhl/o6hFoRGN2+Tjt+RjbsVOPv2dTMLX7VWfWICo/Kf2nhsf7QwmP9oYXH+kMLj/WHFh69czwWHo+Nb2WllFJKKR84Hivh/LLwKCJTsKYN8vSZMab8HDFHP5axwB1lVi8yxtxW17EopZRSqm7544CXmvLLwqNdSKzzgmJFjDFvY/XpVEoppdRxRmselVJKKaXUEfPH2wvWVP0c06+UUkoppeolrXlUSimllPKSP96buqa08KiUUkop5aXjsdlaC49KKaWUUl7SATNKKaWUUuqIHY/N1jpgRimllFJKHTGteVRKKaWU8pI2WyullFJKqSOmhUellFJKKXXEjr+iI8jxWGJWtUtEbjTGzPR1HDVxLOQBNB/1ybGQBzg28nEs5AE0H6r+0AEzqjbc6OsAasGxkAfQfNQnx0Ie4NjIx7GQB9B8qHpCC49KKaWUUuqIaeFRKaWUUkodMS08qtpwLPRdORbyAJqP+uRYyAMcG/k4FvIAmg9VT+iAGaWUUkopdcS05lEppZRSSh0xLTwqpZRSSqkjpoVHpZRSSil1xLTwqNQxQERCReQEX8ehjh0i4hSROBFpXfTwdUzVISIdRCTYfj5cRMaLSGNfx+UNERkqImPt501FpJ2vY/LGsZIPpYVH5SURCRORB0TkDXu5k4ic7eu4qkNEOovIPBFZZy/3EpGpvo6rukTkHGAV8JO93EdEvvVtVNUjItNFJEJEAu2/yQERudLXcVWXiFwkIg3t51NF5EsR6efruKpLRMYBicAc4Hv78Z1Pg6q+LwC3iHTEGt3bCvjQtyFVn4g8BNwHTLJXBQLv+y4i7xwr+VAWLTwqb70N5AGD7eW9wOO+C8crb2B9kBUAGGPWAJf6NCLvPAycCKQBGGNWAf72i/40Y0wGcDawE+gITPRpRN55wBiTKSJDgVHAf4DXfByTN+4ATjDGdDfG9LQfvXwdVDUVGmNcwBjgJWPMRCDWxzF5YwxwLnAIwBizD2jo04i8c6zkQ6GFR+W9DsaY6ZQUvLIB8W1I1RZmjFlSZp3LJ5HUTIExJr3MOn+bgyvA/v8fwGcV5MdfuO3//wHMNMZ8DwT5MB5v7Qb89W9QpEBELgOupqTWNNCH8Xgr31hz6hkAEWng43i8dazkQ1Hyga1UdeWLSCglHwQdsGoi/UmyHXdRHi4E9vs2JK/8JSKXA04R6QSMB373cUzV9Z2IbARygFtEpCmQ6+OYvLFXRGYAo4Gn7T53/vgjfTvwi4h8j8d1bYx5znchVdtY4GZgmjFmh92/7r8+jskbn9rvqcYicgNwLVarib85VvKh0EnClZdEZDQwFegGzAaGANcYY37xZVzVISLtsfpCnQwcBHYAVxpjdvoyruoSkTBgCnAaVu3vLOAxY4xfFb5EJBJIN8a47TxFGGMSfB1XddhxnwGsNcZsEZFYoKcxZraPQ6sWu39aOcaYR+o6FlX8eVt8fRtj5vg4JK8cK/lQWnhUNSAiUcBJWB8Ei40xyT4OySt284nDGJPp61iOVyLixGrqbYtHi4if1XQBICJNsAZneOZjhe8i8p6IhAMYY7J8HcuREpG1HKbbhh/23QRARCIo/Z5K9WE46jinzdaqWioYOVrUzNtaRFr7w5ekiNxVyXrA/wosIvI/yn9ZpgPLgBl+UgP5P6xm6rVAoY9j8ZqIPAZcA2yj5G9igJG+iskbItIDq4k30l5OBv5pjPnLp4EdmaJZH26z/y9qqr4S/+sLjIjcBDyCdX0UYv1YN0B7X8ZVXSKSScn5D8Lqf3rIGBPhu6iUt7TmUVWLiPxsPw0BBgCrsT7MegHLjDGDK9u3vvBokjsBGAgUTWtzDrDEGONXU8SIyL+BpsBH9qpLgAysD+oIY8xVvortSInIGn+tEfIkIpuwmqnzfR1LTYjI78AUY8zP9vJw4AljzMk+DawaRGSlMaZvmXUrjDF+NXWSiGwBBvtry05FxPqlfh5wkjHmfl/Ho6pPax5VtRhjRgCIyJdAP2PMWnu5B9aUMfVeUb8tEVmAlYdMe/lhrPns/M3JxpiBHsv/E5GlxpiBIuIPNUUAP4rIaf7WN7AC64DGQJKvA6mhBkUFRwBjzC9+ODpWRGSIMWaRvXAy/jl4aRuQ7esgapM96vpr+4e8Fh79kBYelbdOKCo4Ahhj1olIV18G5IVmgGcNUb69zt+E210G/gaw7wQSbm/zlxqwxcBXIuLAmv5JsL5j/K1J60lgpT3xvOco5XN9F5JXtovIA5Ru8t3uw3i8cR3wlog0wno/HcQa4etvJgG/i8iflH5PjfddSNUnIv/nsejAarnyhy41qgJaeFTeWiMib1Jyh4ArgDU+jMcb7wFLROQre/l84F0fxuOtu4HfRGQb1pdkO+BWu6bIX/LzHNaE82uNf/eleRd4Gj/vu4lVyHoE+NJeXoifFbyMMcuB3nbhET+eO3QGMB//f0+d4/HchXUzgPN8E4qqKe3zqLwiIiHALcAwe9UC4DU/GZxRzB4AdIq9uMAYs9KX8XjLnk+wi724yQ//DguA4cYYf/5ypKi7gK/jOJ5VNiCuiB8OiCvXd1MpX9PCozpu2c275RQ1//oTu89pN6yBTAAYY97zXUTVIyLvYI0e/RH/nZQaEXkOK/5vKZ2Pej8LAYCIvGCMubOSEfx+0fxe2RyVRfxtrkoReQKrlu5/lH5P+cVUPSLyEoefOsmvmt+VRQuPyisisoOKv1z8ZvqIMvPBhWI1924yxnT3XVTVZ39ZDscqPP4AnAn8Zoy50JdxVcexMim1x2wEnowxxi+m6hGR/saY5SJyakXbjTG/1nVMxzv7s7Ys4y+ftSJy9eG2G2P8pWuN8qCFR+UVe4LwIiHARUCkMeZBH4VUY3YT9q3GmOt9HUt12IXg3sBKY0xvEWkGvG+MGe3j0KrNHyelPhaJyB3GmH9Xta4+E5GWwEtYd78Cq9/mHcaYPb6LSqljgz9OW6DqAWNMisdjrzHmBaw7hPgtu2lxkK/j8EKO3VfQZd+FIgnrDid+Q0R6iMhK4C+se3UvFxG/qgEGEJFGIvKciCyzH88WDdjwMxXVFl1T10HU0NtY3Qfi7Mf/7HV+RUQCRWS8iHxuP24XkUBfx1VdItJURP4lIj+IyPyih6/jUt7R0dbKK2XuNFM07YJfvZ/KdKx3AP2AfT4KpyaWiUhj4A1gOZAF/OHbkKptJnBXmUmp38C677g/eQtrrseL7eWrsAos/1fpHvWIiFwGXA60E5FvPTY1BPyij52HpsYYz8LiOyJyp8+i8d5rWHdjedVevspe51ctJMAHwCdYlQw3Y/1AOeDTiJTXtNlaeaVM3y4XsAN41hizyUchVVuZfnZFU0d84W8jlT2JSFusu8qs8VjXvb7fVk5EVhtjele1rr4TkVXGmD5VrauvRKQNVt/fJyk9eXMmsMYY4/JJYF4QkXlYBfeiOy9dBow1xsT7LqrqO4aujeXGmP6ed5PS2Qn8l1/VFKl65TpjTKlJg0Wkna+C8dJ6Y8xnnitE5CLgs0rS13vGmJ0VrP4vVq1qfXYsTEoNkCMiQ40xvwGIyBAgx8cxHTFjzC5gF9acm/7uWqw+j89jDYz7HRjr04i84xaRDsaYbQAi0h5w+zgmbxTY/+8XkX9gtfJE+jAeVQNa86i8UtE9Yot+WfoqpuqqJA9+d+/bqvjDPHEi0gRrUuqh9qqFwMPGmIO+i6r6RKQP1kThRXc1SQWu9qwJ9gcichJWwasrEAQ4gUN+eMcfvyci8Vg1qNux3lNtsGpQKxrZX2+JyNlY13UrrPdWBPCIMebbw+6o6iWteVTVIiJdgO5AozK3m4rAY47B+kxEzgTOAlqIyIsemyKwmq+PNfX+F6JdSBwvIg2tRf8cbW2MWYV1V5MIeznDxyF562XgUqxa+AHAP4HOPo2omkSkKXAD0BaP7zpjjL/dKWeeiHQCTrBXbTLG5B1un3rqT/suP+nACF8Ho2pGC4+quk4AzgYaU/p2U5lYH9T+YB+wDDgXa4BJkUxggk8iOs6JSE+s20VG2svJWDV263waWDXZI6sfwr7zkoj8Cjzqj7fGM8ZsFRGnMcYNvG2Php/k67iq4Rusmq65+GczLwAichvwQVHttYg0EZHrjDGvVrFrfbNIRHZiDZr50t9aFVRp2mytvCIig40x/jaitxQRCfCnAQDeEpHFxpiTfB3H4YjI78CUMqOtnzDG+NVoaxH5Amu0ddHEx1cBvY0xfjHauoh9u8hRwJtAArAfuMafBmn400Clw6lkEFa974pSERE5EatG+3xgPfCxMeZ930alvKGFR1UtInKvMWZ6Zbec8odbTYnIp8aYi8vcYaZY0UhAfyIiLbD6Qnk2zy3wXUTVcwyNKPXr0dZF7FHXSVhTxEzA6sP5qjFmq08DqwYReRz43Rjzg69jqQn7c6qXsb+sRcSJNfLd7+ZBLSIi0cBzwBXGGKev41HVp83Wqro22P8v82kUNXOH/f/ZPo2ilojI08AlWL/ki5rnDOA3hUd0tHW9Yo+6Bit2f7tFZCbW+1+AySKSD+Tby8YPB/38BHwiIjPs5ZvsdX7F7gc8BqvmsQPwFXCiT4NSXtOaR3XcEpGnjTH3VbWuvhORTVg1E/7YiR4oN9raYPVVe8Tf+kWJSG+svptFd5U5iB+Ntq6sNr6IP9bK+zsRcWAVGIvmp5wDvGn3RfUbYt2j+2vgU3/v8qS08Ki8JCL/o/yXTDpWjeQMf5hou5Kpetb42xekiPwIXOSvI5TtZri5xhi/HoFp5+NpY8w9/jra2m6urpRHjWS9JyICXAG0M8Y8JiKtgFhjzBIfh3ZcEhExhylwiMhLxphxdRmT8p42WytvbQeaUnL3hkuwRit3xrqt3FU+iqtKInILcCvQXkQ8a4QaAot8E1WNZAOr7DtqFNc++kP/UwBjjFtECkWkkT+OSi5i52Oo/dyvCo1F/KlweAReBQqBkcBjWLftfAXwqzua2F0fHqakT3NR83t7X8ZVXYcrONqG1EkgqlZo4VF56+Qyt5X6X9GtpkSkXt8KD/gQ+JEKbsH2/+3de5CkVX3G8e8Dcl+ugloWQRaCXFRAWAQENWgkhiCIAgoKBKKVQBTiLUJpKRIFUVHJahCrFLkoKoIiFKJgQMTFcFmXu5uIiEKIWhQsiCwu+OSP87bTO8wuMz2ze+b0PJ+qqZl+e7bq6Zqd6fOey+9nu7X+vQDf6T5a9nvgVklXAI/2LrYyAO7z064n9AUs/Touqhdp4vr2DUIpEr4a7RUJ39X2Tl2JIWw/KGn12qEG8EXKoaWbaLjkUAyXDB5jULMkbWb7VwCSNgNmdc/9sV6WljeBAAASBElEQVSsp9dXqPYQAEnPohQ4nyVpVu81tcL22U//XdPeRd1H69YEHqDMdvWYxl6b7XV7X3fLv/sD07rc0xiWdFsJeqeUN6HMRLZmke3v1g4R0S97HmMgkvYBPg/cRVlGmU1ZCr4aeJvtz9RLNz6SXkspF/FcSlmS5wF3tlYCo+s+cQqwHX1dflpb1loeSRfafkPtHDNZa7UFJb2Zsp1mJ0rdzQOBD4zuZz/dSfoYpT3kRSy9LWV+tVArQGv/v2a6zDzGQGxf1g1atukuLew7JDPtB46dj1BmU660/WJJe1FKxLTmLEpXk09T2n4dCaxSNdHUm9YD4WXVPe1pbfl9VOvRVSgtCqf9Ibh+tr8i6SbKKWUBr7N959P8s+lo1+7znL5rZunZ7WZIWtv2H8Z46vSVHiYGlsFjTMbOjPSN3UESts+pG2lClth+QNIqklaxfZWkVga+/dbq+t+qO/BwYvem+cHawabQdF8i6dU93YMyA/z17vFBlPqbrelvPfoE8EvK0nUzJG0J3G37c13HoldLut/2Q5WjTUjrVQh6JL2U0rFoFrBZV9bqH20fA2D7yxXjxQRl8BgDkXQupdDrApYuTN3S4PEhSbMoxbS/Ium39B1yaMjjXS24/5H0duA+RvafxkrQ23faneTfs9f2UtLnKTUrm2L7yNoZpsCFwBxJfwmcSTlU9lVgn6qpxknSW2yfJ+ldYz1v+1MrO9MkfRr4G7rDfbZvlvTyupFiUBk8xqDmANuNo/zCdLY/ZSnunZR6cOsDJ1VNNJjjgLWBYyklSV4JHFE10dRT7QDjtCGwHtA7tT+ru9YUSVtQlhF3o9wUXge803ZLXX/+ZPuJbgn+s7bn9k5eN2Kd7vO6y/2uhtj+dTl/9Wc5Pd6oDB5jULcBzwHurx1kULb7ZxmbPbFs+4buy99T9jsOo1a6/nyMUq7nKsqA9+WUGn2t+SqlJuIB3eM3UWq67rrMfzH9LJF0CHA4I8vwq1XMMyG2z+w+L7c9pKQTbJ+yclJNyq+7pWtLWo1y09viHtQgp61jQN2b447A9Sx9AnC/aqHGaVQNu6WeoqHet5I+Y/tfltHtp5WfxbLa4fV+Fk11+wGQ9BxGBln/Zfv/auYZxFidliTdbHuHWpkmStJ2wD8B19k+X9Js4GDbp1aONqXG6pQ1HUnamDKb/deU3+/vA8fZfqBqsBhIBo8xEEmvGOu67R+u7CwzlaSdbd/U8s9imNrhwVIt8bawfVJX//Q5rbXEk3QqpS/31yiD+zdSlt8/AdBoMf2hlBI3UUMGjzEwSc9mpNXX9bZ/WzNPRG2SzqBriWd7W0kbAt8f1Y1p2pN093KebqI1XvcaxpqRn/bZJ6KhmcePU8qjPQZcDmxP2Ud7XtVgMZDseYyBSDqYMgtxNWUJYq6k99r+ZtVgM8hylnwBaGnJV9JuwFxgW0o7vFVprx0eDElLPNuza2eYAv11EdeklE3aqFKWFamVw2R72/5XSQdQSj+9nlLpIoPHBmXwGIN6P7BLb7axa/11JZDB48qzb/f5n7vP53af38L0r4s42mcphzIuoLzpHw48v2qiwQxFS7zuQMPRlAM/UG4Sz7S9pFqoCRpjL91nhrD+KZTfmRb0xht/B1xge9Gok9fRkAweY1CrjFqmfoDh62oyrfX2A0p69ag9T++TNB84vk6ywdj+uaRVbT8JnNXN3p1QO9cE/TvwLeDZkj5K1xKvbqSBnEE5mfwf3ePDumtvrZZogiT1L+X2uuQ0957X3YC8jZGGDADYPqr7fHKdZBN2qaSfUZatj+5eV1Ndi2JEc79IMW1cLul7lPIdUDbUX1Yxz0wmSXvY/nH34KW0N5D/Q7e8u6DbG3U/7b2G0S3xoN2WeLuMOln9n5JurpZmMKf1fd3rknNwnSiTcjGl0PyVNFwX0fbx3e/2IttPSnqUxroWxYgMHmMgtt8r6Q2UdmwAX7D9rZqZZrB/AL4kaf3u8UPAURXzDOIwymDx7ZSi7X9B2RPVorUpezYNrFU5y6CelLSl7bvgz0XDmxq4DEtbP2Bt263UOV0mSYf3fd3/VEtdyaKT09YRQ6I3eLS9qHaWiZJ0nO3Tn+7adCfpg5SDGRdSDjK8jrK/6yNVg02QpFcBZwG9jjKbA0favqpaqAnqfh8+xMi+zR8CJ7X2+yHpI8A8202v7Eia2/dwTcrs/HzbB1aKFJOQwWNMyLAU2B4mXcmkk4Hn2v7brjjy7ra/WDnauI1VbqTF+nWSFgI72F7cPV4LWGB767rJJkbSmsC7KW/wDwE3AJ/uva4WSLqQ0gmr1z3qMMrPpqkZ7e5v7jqUZgxLGJK/tZI2AL5m+zW1s8TEZdk6JsT20PRZHSJfpswSvb97/N/A14FpP3js2scdCsyW9J2+p/r7Q7fkfymzKr1B1hrAffXiDOwc4GFKr3QoP6NzKbOqrdjS9hv6Hn9Y0oJqaQY0xH9zHwWGoSTUjJTBY0T7Nrb9DUknANh+QlIr+9PmUQ7HbMzSBxweAW6pkmgA3ZKcgUXA7ZKu6B6/mtLCszUvtL1d3+OrJN1RLc1gHpO0p+1rASTtQTnp25yu2PxWlBsTAGxfUy/RxI1qo7oqpabrN+olisnI4DGifY9KeiYjtQV3owxipr2u3NA9wO6jOhbdafuJeskm7Mbu802UUj09V6/8KFNivqTdbP8EQNKujLzGVhwNnN13kOxB4IiKeQYi6a3AccCmwAJgN+A64JU1cw3gk31fPwHcY/veWmFicrLnMaJxXT27ucALKXu8NgEOtN3SzN1BlDeXqyl7ul4GDF3HIkkXjlpKnZYk3QlsDfyqu7QZsJDypu8WuhdJWoNSZ3NLYAPKDZVtn1Q12AR1naR2AX5ie0dJ2wAnt7Z3E9LSdphk5jGicbbnS3oF5c1ewMKWOoF0PsDM6FjUSl/lYTjEcDHlsM982tx32rPY9mJJSFrD9s8kNXUAC9LSdthk8BjRuK4d3j6MdKDYWxK2P1U12MTMlI5FTSz19LoXNW7TITnJe293MvnbwBWSHqRs9WhNWtoOkQweI9p3CeV076002Ee58910LIopNk/Si2zfWjvIZNg+oPvyRElXAesDl1eMNKiZcoM4I2TwGNG+TVvYg/Y0DJwJ7Nk9/gLlYMCw0dN/S0xGt0fQlPe3IyX9glIjsVcfsYnfFUnr2X5Y0kZ9l3sD4Vm0V8oqLW2HSA7MRDRO0qnAD2x/v3aWQS2jSPgtrbzRj5ekvVv+ObVA0vOW93wrS/KSLrW9r6S7KYPh/hsP225l/+yfjWpp+6O0tG1XBo8RjZN0AHAeZQmoqQ4Uko4GjqEcJLmr76l1gR/bfkuVYBPUN9v1lKdoaLYrImI8MniMaFw3M7E/cKsb+4XuavBtCJwCHN/31CO2m1mWG5bZrpg+uhJcy2R7/srKMhUkvR44FXgW5aaqmZvceKoMHiMaJ+ka4K9st3pYJiJG6Q7HQOkqMwe4mTLg2h640fbutbINQtLPgdfavrN2lpi8HJiJaN8vgKslfZdyMACgtVI9Q6Hr7jOX0nptdUobtkczuxITZXsvAEkXATv1To1LeiFwYsVog/pNBo7DI4PHiPbd3X2s3n1EPZ8F3gRcQJktOhx4ftVE0bqt+8sN2b5N0rY1A01Et1wNcKOkr1PqVfbf5F5UJVhMSpatI4acpLm231E7x0wg6Ubbc/pPikv6qe0X184WbZJ0PvAo5VAcwJuBWbYPqZdq/CSdtZynbfuolRYmpkxmHiOG3x5P/y0xRf4gaXVggaSPA/eTQsgxOUcCRwPHdY+vAc6oF2dibB85nu+TdILtU1Z0npgamXmMGHJj1VCMFaM7df0byvaBd1K6gXzO9l3L/YcRyyFpLWAz2wtrZ1lR8neqLbkjjoiYOq+zvdj2w7Y/bPtdwL61Q0W7JO0HLKBrSShpR0nfqZtqhUj3pYZk8Bgx/PJHeeU5Yoxrf7+yQ8RQ+RDwEuAhANsLgNlVE60YWQZtSPY8Rgy/02sHGHaSDgEOBWaPmhVaj/Z6EMf0ssT2Immpe8BhHGjlJrchGTxGNE7SJTz1zWQRcCNwpu0vr/RQM888yuGYjYHT+q4/AtxSJVEMi9slHQqsKmkr4FjK/7dhc0HtADF+OTAT0ThJpwObAOd3l94IPEwZUK5n+7Ba2WYiSc8GdukeXm/7tzXzRNskrQ28H9i7u/Q94N9sP77sfzX9SNoEeBuwOX0TVynV06YMHiMaJ+kG27uMdU3S7bZfUCvbTCPpIOCTwNWUZbiXAe+1/c2auaJdkuZQBo+bMzLocq+OaCskzQN+BNwEPNm7bvvCaqFiYFm2jmjfLEmb2f4VgKTNgFndc3+sF2tG+gCwS2+2sZttuRLI4DEG9RXgPcBtQMv969e2/b7aIWJqZPAY0b53A9dKuosy2zUbOEbSOsDZVZPNPKuMWqZ+gFS1iMn5ne1LaoeYApdK2sf2ZbWDxORl2TpiCEhaA9ime7jQ9uKaeWaqrqvMDiy9//SWzLjEoCS9CjgE+AEN94SW9AiwDuU1LKHc6Nr2elWDxUAy8xgxHHZmZE/UDpKwfU7dSDOSgTOBPbvHXwB2qxcnhsCRlBvD1RhZtjbQ1ODR9rq1M8TUycxjROMknQtsSelC0duIbtvH1ks1M43VYk3SLa0dbojpQ9JC21vXzjEVJG0IbAWs2btm+5p6iWJQmXmMaN8cYDvnTrAaSUcDxwBbSOqv67gu8OM6qWJIzJO0ne07ageZDElvBY4DNqXc6O4GXAe8smauGExmHiMaJ+kC4Fjb99fOMlNJWh/YEDgFOL7vqUdsp8NMDEzSnZSVhbsp+wV7ewWbms2WdCul/ulPbO8oaRvgZNuvrxwtBpCZx4j2bQzcIel6lt5Qv1+9SDOL7UWUrj6H1M4SQ+c1tQNMkcW2F0tC0hq2fyZpKJbjZ6IMHiPad2LtABGxYti+p3aGKXKvpA2AbwNXSHoQGJbXNuNk2ToiIiJWGkmvANYHLredRgYNyuAxolGSrrW9Z1c/rf8XOfXTImJakLSe7YclbTTW89kT3KYMHiMiImKFkHSp7X0l3U25yVXf07a9RaVoMQkZPEY0TtKWwL22H5f0V8D2wDm2H6qbLCIihlEGjxGNk7SAUutxc+Ay4GLgBbb3qZkrIkLSTst73vb8lZUlpk5OW0e070+2n5B0ADDX9lxJP60dKiICOK37vCblJvdmytL19sCNwO6VcsUkrFI7QERM2hJJhwBHAJd211armCciAgDbe9neC7gf2Mn2HNs7Ay8G7qubLgaVwWNE+46k3L1/1PbdkmYD51bOFBHRb2vbt/Ye2L4N2LZinpiE7HmMiIiIFUrS+cCjwHndpTcDs2ynK1ODMniMaFxfCYylpARGREwXktYEjgZe3l26BjjD9uJ6qWJQGTxGNE7SM/sergkcBGxk+4OVIkVEPIWktYDNbC+snSUmJ4PHiCEk6aZuU3pERHWS9gM+Aaxue7akHYGTbO9XOVoMIKV6Iho3qo7aKpRyGPndjojp5EPAS4CrAWwv6A73RYPyBhPRvtP6vn4C+CVwcJ0oERFjWmJ7kdTfnfCpe7WjDRk8RjSuq6EWETGd3S7pUGBVSVsBxwLzKmeKAaXOY0TjJK0v6VOSbuw+TpO0fu1cERF93gG8AHgc+CqwCDiuaqIYWAaPEe37EvAIZan6YOBh4KyqiSIilrZd9/EMSlWI/YEbqiaKgeW0dUTjJC2wvePTXYuIqEXSQuA9wG3An3rXbd9TLVQMLHseI9r3mKQ9bV8LIGkP4LHKmSIi+v3O9iW1Q8TUyMxjROO6emlnA719jg8CR9i+pV6qiIgRkl4FHAL8gLLvEQDbF1ULFQPL4DGicZLWAA4EtgQ2oGxEt+2TqgaLiOhIOg/YBridkWVr2z6qXqoYVJatI9p3MfAQMB+4r3KWiIix7GJ769ohYmpk8BjRvk1tv6Z2iIiI5ZgnaTvbd9QOEpOXwWNE++ZJepHtW2sHiYhYht2ABZLupux5FGXZevu6sWIQ2fMY0ShJt1Laez0D2Ar4BfmjHBHTkKTnjXU9pXralMFjRKOW9ce4J3+UIyJiRcjgMSIiIiLGLe0JIyIiImLcMniMiIiIiHHL4DEiIiIixi2Dx4iIiIgYtwweIyIiImLc/h9uy0qifoRz8QAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cols = [\"median_house_value\", \"median_income\", \"total_rooms\",\"housing_median_age\"]\n",
        "#pd.plotting.scatter_matrix(df[cols], alpha = 0.2, figsize = (12,8))\n",
        "g = sns.pairplot(df[cols], diag_kind=\"kde\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L92iVqKdfrMW",
        "outputId": "5920afd6-3ab9-4e11-eae0-88c153ee82c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 20 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ax = sns.scatterplot(df.median_income, df.median_house_value, alpha = 0.5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4TbPtqjEqXlp",
        "outputId": "82b2ee2e-72e4-4c27-ed96-93c53a49f1c6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#sns.set()\n",
        "#tips = sns.load_dataset(\"tips\")\n",
        "\n",
        "ax = sns.scatterplot(df.longitude,df.latitude, c=df.median_house_value)\n",
        "sm = plt.cm.ScalarMappable()\n",
        "ax.figure.colorbar(sm)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ubp1VUp-QvQI",
        "outputId": "33699697-9593-4b28-81a5-3c2c7a0d19bf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.colorbar.Colorbar at 0x7ff6684c4f50>"
            ]
          },
          "metadata": {},
          "execution_count": 97
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# cols=df.columns\n",
        "# cols\n",
        "# fig, axs = plt.subplots(3, 3, figsize=(10,10))\n",
        "# fig.add_gridspec(3, 3, hspace=10, wspace=40)\n",
        "# k = 0\n",
        "# for i in range(0,3):\n",
        "#     for j in range(0,3):        \n",
        "#         sns.histplot(df[cols[k]],ax=axs[i, j])\n",
        "#         #sns.kdeplot(df[cols[k]], ax=axs[i, j],color=\"b\")        \n",
        "#         axs[i, j].legend(fontsize = 8)        \n",
        "        \n",
        "#         if(j==0):\n",
        "#           axs[i, j].set_ylabel(\"\")\n",
        "#         if(i==2):\n",
        "#           axs[i, j].set_xlabel(\"\")\n",
        "#         k=k+1\n"
      ],
      "metadata": {
        "id": "HQOsFvciXUd_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "id": "igQKqYaHWmdk",
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        },
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      },
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              "      <td>452600.0</td>\n",
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              "      <td>352100.0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-122.25</td>\n",
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              "      <td>1274.0</td>\n",
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              "      <td>341300.0</td>\n",
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            ],
            "text/plain": [
              "       longitude  latitude  ...  median_house_value  ocean_proximity\n",
              "0        -122.23     37.88  ...            452600.0         NEAR BAY\n",
              "1        -122.22     37.86  ...            358500.0         NEAR BAY\n",
              "2        -122.24     37.85  ...            352100.0         NEAR BAY\n",
              "3        -122.25     37.85  ...            341300.0         NEAR BAY\n",
              "4        -122.25     37.85  ...            342200.0         NEAR BAY\n",
              "...          ...       ...  ...                 ...              ...\n",
              "20635    -121.09     39.48  ...             78100.0           INLAND\n",
              "20636    -121.21     39.49  ...             77100.0           INLAND\n",
              "20637    -121.22     39.43  ...             92300.0           INLAND\n",
              "20638    -121.32     39.43  ...             84700.0           INLAND\n",
              "20639    -121.24     39.37  ...             89400.0           INLAND\n",
              "\n",
              "[20640 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Combinar caracteristics puede ser una buena forma de definir nuevas variables y mejorar\n",
        "# los entrenamientos del algoritmo."
      ],
      "metadata": {
        "id": "Eqxn0gYNnJKz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Preparación de data para un algoritmo de machine learning "
      ],
      "metadata": {
        "id": "Cs83I-MnQilp"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Evitar el data *Snooping bias*.\n",
        "\n",
        "En algunos casos se sugiere dividir los datos en entrenamiento y test desde el principio dado que el cerebro puede sobreajustar el dataset y los resultados no significativos se pueden volver significativos. El procedimiento correcto es probar cualquier hipótesis en un conjunto de datos que no se utilizó para generar la hipótesis. \n",
        "\n",
        "\n",
        "# *Sampling bias*\n",
        "\n",
        "Si el dataset es lo suficientemente grande un muestreo aleatorio de la muestra puede ser considerado, sin embargo si la muestra es pequena se debe garantizar homegeniedad en el dataset de entrenamiento. \n",
        "\n",
        "\n",
        "Ejemplo: \n",
        "\n",
        "Por ejemplo, la población de EE. UU. esta compuesto por un 51,3 % de mujeres y un 48,7 % de hombres, por lo que una encuesta bien realizada en EEUU\n",
        "trata de mantener esta proporción en la muestra: 513 mujeres y 487 hombres. Esto se llama muestreo estratificado(stratified sampling): la población se divide en subgrupos homogéneos llamados estratos(strata), y se muestrea el número correcto de instancias de cada estrato para garantizar que el\n",
        "El conjunto de prueba es representativo de la población general. Si usaran muestras puramente aleatorias, habría alrededor del 12% de posibilidades de muestrear un conjunto de prueba sesgado con menos del 49% de mujeres o más del 54% de mujeres. De cualquier manera, los resultados de la encuesta serían\n",
        "significativamente sesgada.\n",
        "\n"
      ],
      "metadata": {
        "id": "w2-OZweOVSaw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html\n",
        "from sklearn.model_selection import train_test_split"
      ],
      "metadata": {
        "id": "rxV98k2oVRt_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# ¿Es significativa la muestra que se esta considerando?\n",
        "train_set, test_set \\\n",
        "  = train_test_split(df, test_size = 0.2, random_state = 42)"
      ],
      "metadata": {
        "id": "MZ2xabhFRGpD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(train_set))\n",
        "print(len(test_set))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kT0GhkppbROx",
        "outputId": "64b0e248-c7ed-47e7-c4c1-a3ee5fc3fc8a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "16512\n",
            "4128\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "sn26cMU3uEur",
        "outputId": "a8062c8d-cd00-4410-8eec-e19390ae36d7"
      },
      "execution_count": null,
      "outputs": [
        {
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              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
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              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
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              "      <th>median_house_value</th>\n",
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              "      <td>452600.0</td>\n",
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              "      <td>356.0</td>\n",
              "      <td>114.0</td>\n",
              "      <td>2.5568</td>\n",
              "      <td>77100.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20637</th>\n",
              "      <td>-121.22</td>\n",
              "      <td>39.43</td>\n",
              "      <td>17.0</td>\n",
              "      <td>2254.0</td>\n",
              "      <td>485.0</td>\n",
              "      <td>1007.0</td>\n",
              "      <td>433.0</td>\n",
              "      <td>1.7000</td>\n",
              "      <td>92300.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20638</th>\n",
              "      <td>-121.32</td>\n",
              "      <td>39.43</td>\n",
              "      <td>18.0</td>\n",
              "      <td>1860.0</td>\n",
              "      <td>409.0</td>\n",
              "      <td>741.0</td>\n",
              "      <td>349.0</td>\n",
              "      <td>1.8672</td>\n",
              "      <td>84700.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20639</th>\n",
              "      <td>-121.24</td>\n",
              "      <td>39.37</td>\n",
              "      <td>16.0</td>\n",
              "      <td>2785.0</td>\n",
              "      <td>616.0</td>\n",
              "      <td>1387.0</td>\n",
              "      <td>530.0</td>\n",
              "      <td>2.3886</td>\n",
              "      <td>89400.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20640 rows × 10 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0d6ac817-9287-4c7f-97c4-2c606fe35bb5')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0d6ac817-9287-4c7f-97c4-2c606fe35bb5 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-0d6ac817-9287-4c7f-97c4-2c606fe35bb5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       longitude  latitude  ...  median_house_value  ocean_proximity\n",
              "0        -122.23     37.88  ...            452600.0         NEAR BAY\n",
              "1        -122.22     37.86  ...            358500.0         NEAR BAY\n",
              "2        -122.24     37.85  ...            352100.0         NEAR BAY\n",
              "3        -122.25     37.85  ...            341300.0         NEAR BAY\n",
              "4        -122.25     37.85  ...            342200.0         NEAR BAY\n",
              "...          ...       ...  ...                 ...              ...\n",
              "20635    -121.09     39.48  ...             78100.0           INLAND\n",
              "20636    -121.21     39.49  ...             77100.0           INLAND\n",
              "20637    -121.22     39.43  ...             92300.0           INLAND\n",
              "20638    -121.32     39.43  ...             84700.0           INLAND\n",
              "20639    -121.24     39.37  ...             89400.0           INLAND\n",
              "\n",
              "[20640 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### División del dataset en grupos\n",
        "La siguiente division debe ser basada en la experticie de lo que se esta realizando, y sobre ello se debe tomar una muestra significativa"
      ],
      "metadata": {
        "id": "iJDoUvaHgevX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"income_cat\"] = pd.cut(df[\"median_income\"],\n",
        "                               bins=[0., 1.5, 3.0, 4.5, 6., np.inf],\n",
        "                               labels=[1, 2, 3, 4, 5])"
      ],
      "metadata": {
        "id": "illO7GXnZrRk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.income_cat.hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "Yl1KzCCeZu_H",
        "outputId": "2c6a833e-0fbe-4897-83ec-6a9cb0caa6d4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff668493810>"
            ]
          },
          "metadata": {},
          "execution_count": 106
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import StratifiedShuffleSplit\n",
        "\n",
        "split = StratifiedShuffleSplit(n_splits = 1, test_size=0.2, random_state=42)\n",
        "\n",
        "for train_index, test_index in split.split(df, df[\"income_cat\"]):\n",
        "  strat_train_set = df.loc[train_index]\n",
        "  strat_test_set = df.loc[test_index]\n"
      ],
      "metadata": {
        "id": "VC9_03mnaAN0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Proporciones del dataset"
      ],
      "metadata": {
        "id": "i0KrWkAbhvrm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"income_cat\"].value_counts() / len(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jH3h4MBiaIGH",
        "outputId": "2f79fc66-a624-4228-d362-e455ef61343e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3    0.350581\n",
              "2    0.318847\n",
              "4    0.176308\n",
              "5    0.114438\n",
              "1    0.039826\n",
              "Name: income_cat, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "strat_train_set[\"income_cat\"].value_counts() / len(strat_train_set)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yuPm6dTLhJLP",
        "outputId": "85ced212-c4d2-4625-843b-b2a7c231aa02"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3    0.350594\n",
              "2    0.318859\n",
              "4    0.176296\n",
              "5    0.114462\n",
              "1    0.039789\n",
              "Name: income_cat, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "strat_test_set[\"income_cat\"].value_counts() / len(strat_test_set)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N9aPEYzgiDyo",
        "outputId": "958a5d89-6819-4378-ba6f-321a9315e8d9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3    0.350533\n",
              "2    0.318798\n",
              "4    0.176357\n",
              "5    0.114341\n",
              "1    0.039971\n",
              "Name: income_cat, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_set, test_set \\\n",
        "  = train_test_split(df, test_size = 0.2, random_state = 42)\n"
      ],
      "metadata": {
        "id": "YL8JYyd4hYaj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "test_set[\"income_cat\"].value_counts() / len(test_set)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WZqJ04S-iKLT",
        "outputId": "1efdd014-de79-40eb-c3fb-4a29bc046732"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3    0.358527\n",
              "2    0.324370\n",
              "4    0.167393\n",
              "5    0.109496\n",
              "1    0.040213\n",
              "Name: income_cat, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_set[\"income_cat\"].value_counts() / len(test_set)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5QM67C3viU_T",
        "outputId": "6b1c88d7-c989-4de8-f8e3-095456974cdd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3    0.358527\n",
              "2    0.324370\n",
              "4    0.167393\n",
              "5    0.109496\n",
              "1    0.040213\n",
              "Name: income_cat, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def income_cat_proportions(data):\n",
        "    return data[\"income_cat\"].value_counts() / len(data)\n",
        "\n",
        "train_set, test_set = train_test_split(df, test_size = 0.2, random_state = 42)\n",
        "\n",
        "compare_props = pd.DataFrame({\n",
        "    \"Overall\": income_cat_proportions(df),\n",
        "    \"Stratified\": income_cat_proportions(strat_test_set),\n",
        "    \"Random\": income_cat_proportions(test_set),\n",
        "}).sort_index()\n",
        "compare_props[\"Rand. %error\"] =abs( 100 * compare_props[\"Random\"] / compare_props[\"Overall\"] - 100)\n",
        "compare_props[\"Strat. %error\"] =abs( 100 * compare_props[\"Stratified\"] / compare_props[\"Overall\"] - 100)"
      ],
      "metadata": {
        "id": "Zuv9wwOCixcH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "compare_props"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "ASL8zhpijWun",
        "outputId": "7451aa99-af5d-4e3c-b822-ec3977cc7ae0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Overall</th>\n",
              "      <th>Stratified</th>\n",
              "      <th>Random</th>\n",
              "      <th>Rand. %error</th>\n",
              "      <th>Strat. %error</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.039826</td>\n",
              "      <td>0.039971</td>\n",
              "      <td>0.040213</td>\n",
              "      <td>0.973236</td>\n",
              "      <td>0.364964</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.318847</td>\n",
              "      <td>0.318798</td>\n",
              "      <td>0.324370</td>\n",
              "      <td>1.732260</td>\n",
              "      <td>0.015195</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.350581</td>\n",
              "      <td>0.350533</td>\n",
              "      <td>0.358527</td>\n",
              "      <td>2.266446</td>\n",
              "      <td>0.013820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.176308</td>\n",
              "      <td>0.176357</td>\n",
              "      <td>0.167393</td>\n",
              "      <td>5.056334</td>\n",
              "      <td>0.027480</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.114438</td>\n",
              "      <td>0.114341</td>\n",
              "      <td>0.109496</td>\n",
              "      <td>4.318374</td>\n",
              "      <td>0.084674</td>\n",
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              "                                                     [key], {});\n",
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              "  "
            ],
            "text/plain": [
              "    Overall  Stratified    Random  Rand. %error  Strat. %error\n",
              "1  0.039826    0.039971  0.040213      0.973236       0.364964\n",
              "2  0.318847    0.318798  0.324370      1.732260       0.015195\n",
              "3  0.350581    0.350533  0.358527      2.266446       0.013820\n",
              "4  0.176308    0.176357  0.167393      5.056334       0.027480\n",
              "5  0.114438    0.114341  0.109496      4.318374       0.084674"
            ]
          },
          "metadata": {},
          "execution_count": 115
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "En Conclusion"
      ],
      "metadata": {
        "id": "SwA7F3GSjrtQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Si no recuerda los comandos de pandas, puede ver una cheat sheet \n",
        "#https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf\n",
        "data_link = \"https://raw.githubusercontent.com/hernansalinas/Curso_aprendizaje_estadistico/main/datasets/Sesion_07_housing.csv\"\n",
        "df = pd.read_csv(data_link)\n",
        "\n",
        "#1. Leer los data. \n",
        "#2. Para hacer el split analizar si la muestra es significativa para el entrenamiento y test\n",
        "#3. Dejar los data de test ocultos para hacer las pruebas"
      ],
      "metadata": {
        "id": "IbhCrTpGjdqE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"income_cat\"] = pd.cut(df[\"median_income\"],\n",
        "                               bins=[0., 1.5, 3.0, 4.5, 6., np.inf],\n",
        "                               labels=[1, 2, 3, 4, 5])"
      ],
      "metadata": {
        "id": "9Hc1xHGNjxuM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "split = StratifiedShuffleSplit(n_splits = 1, test_size=0.2, random_state=42)\n",
        "\n",
        "for train_index, test_index in split.split(df, df[\"income_cat\"]):\n",
        "  strat_train_set = df.loc[train_index]\n",
        "  strat_test_set = df.loc[test_index]\n",
        "\n",
        "df_train = strat_train_set\n",
        "df_test = strat_test_set"
      ],
      "metadata": {
        "id": "L_5i6JZpkMZD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Matrix de correlación"
      ],
      "metadata": {
        "id": "BtMALke5ULkC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix = df_train.corr()\n",
        "corr_matrix[\"median_house_value\"].sort_values(ascending=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h7XPSAwsn1x_",
        "outputId": "17e7500f-425c-4682-d1b3-5ae7455333a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "median_house_value    1.000000\n",
              "median_income         0.687151\n",
              "total_rooms           0.135140\n",
              "housing_median_age    0.114146\n",
              "households            0.064590\n",
              "total_bedrooms        0.047781\n",
              "population           -0.026882\n",
              "longitude            -0.047466\n",
              "latitude             -0.142673\n",
              "Name: median_house_value, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualización de la matrix de correlación\n",
        "plt.figure(figsize = (10,6))\n",
        "sns.heatmap(corr_matrix, annot = True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 474
        },
        "id": "xJW_3pVdnoS-",
        "outputId": "948b9e85-96c9-428e-fc05-a50e9c2e238a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Agregar nuevas variables"
      ],
      "metadata": {
        "id": "hL9CJtC4prW9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_train[\"rooms_per_household\"] = df_train[\"total_rooms\"]/df_train[\"households\"]\n",
        "df_train[\"bedrooms_per_room\"] = df_train[\"total_bedrooms\"]/df_train[\"total_rooms\"]\n",
        "df_train[\"population_per_household\"]=df_train[\"population\"]/df_train[\"households\"]\n"
      ],
      "metadata": {
        "id": "hNfunc88kaun"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix = df_train.corr()\n",
        "corr_matrix[\"median_house_value\"].sort_values(ascending=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UE2czz92kmdY",
        "outputId": "5aa3b98f-4af0-463a-970f-de0c92d858d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "median_house_value          1.000000\n",
              "median_income               0.687151\n",
              "rooms_per_household         0.146255\n",
              "total_rooms                 0.135140\n",
              "housing_median_age          0.114146\n",
              "households                  0.064590\n",
              "total_bedrooms              0.047781\n",
              "population_per_household   -0.021991\n",
              "population                 -0.026882\n",
              "longitude                  -0.047466\n",
              "latitude                   -0.142673\n",
              "bedrooms_per_room          -0.259952\n",
              "Name: median_house_value, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 122
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualización de la matrix de correlación\n",
        "plt.figure(figsize = (10,6))\n",
        "sns.heatmap(corr_matrix, annot = True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        },
        "id": "qndP5tQJngUN",
        "outputId": "28603321-e1f7-4c33-a871-cab2ce4deb21"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Limpieza de datos"
      ],
      "metadata": {
        "id": "jG7NimaVpf2Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_train.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NbIYCyEzoFMq",
        "outputId": "5118cdcb-1610-4c09-80be-a3dd08bd1427"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "longitude                     0\n",
              "latitude                      0\n",
              "housing_median_age            0\n",
              "total_rooms                   0\n",
              "total_bedrooms              158\n",
              "population                    0\n",
              "households                    0\n",
              "median_income                 0\n",
              "median_house_value            0\n",
              "ocean_proximity               0\n",
              "income_cat                    0\n",
              "rooms_per_household           0\n",
              "bedrooms_per_room           158\n",
              "population_per_household      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#df_train.dropna(subset=[\"total_bedrooms\"]) #Eliminar los nan\n",
        "#df_train.drop(\"total_bedrooms\", axis=1)  # Eliminar la columna\n",
        "median = df_train[\"total_bedrooms\"].median()\n",
        "q=df_train[\"total_bedrooms\"].fillna(median).copy()"
      ],
      "metadata": {
        "id": "6Uqwpt1CohFl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "q=pd.DataFrame(q)"
      ],
      "metadata": {
        "id": "wQivaj95xh5V"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "q.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pjD0RfJdxeWg",
        "outputId": "8d1648b7-2668-4aa1-e22e-c528595c4c42"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "total_bedrooms    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 127
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Imputer"
      ],
      "metadata": {
        "id": "Yil600g7rfG9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_train_num = df_train.drop(\"ocean_proximity\", axis=1)"
      ],
      "metadata": {
        "id": "e7plKqDSsts-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.impute import SimpleImputer\n",
        "#imputer = Imputer(strategy=\"median\")\n",
        "imp_mean = SimpleImputer( strategy='mean')"
      ],
      "metadata": {
        "id": "Tx7V6K6KqwZv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "imp_mean.fit(df_train_num)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-UcBM3s3rH81",
        "outputId": "5c08727f-73f9-4639-a5da-579c5d5657e2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SimpleImputer()"
            ]
          },
          "metadata": {},
          "execution_count": 130
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "imp_mean.statistics_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3TvQFj8usSkB",
        "outputId": "c7a92a71-52dc-440d-cb55-effab132e938"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-1.19575635e+02,  3.56393144e+01,  2.86534036e+01,  2.62253979e+03,\n",
              "        5.34914639e+02,  1.41968738e+03,  4.97011810e+02,  3.87588428e+00,\n",
              "        2.07005322e+05,  3.00678295e+00,  5.44040595e+00,  2.12872772e-01,\n",
              "        3.09646921e+00])"
            ]
          },
          "metadata": {},
          "execution_count": 131
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_train_num.median().values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IWoxFb8Wsegi",
        "outputId": "51a51899-5fa4-4086-cb10-6ff6fa4addc7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-1.18510000e+02,  3.42600000e+01,  2.90000000e+01,  2.11900000e+03,\n",
              "        4.33000000e+02,  1.16400000e+03,  4.08000000e+02,  3.54155000e+00,\n",
              "        1.79500000e+05,  5.23234164e+00,  2.03027043e-01,  2.81766108e+00])"
            ]
          },
          "metadata": {},
          "execution_count": 132
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = imp_mean.transform(df_train_num)\n"
      ],
      "metadata": {
        "id": "k1GHLJqmtE3f"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7LFXpQittcas",
        "outputId": "24db8f37-0a71-4fa4-f970-a2091e91f86a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-121.46      ,   38.52      ,   29.        , ...,    5.48583569,\n",
              "           0.20578363,    3.16855524],\n",
              "       [-117.23      ,   33.09      ,    7.        , ...,    6.92708333,\n",
              "           0.16071429,    2.62369792],\n",
              "       [-119.04      ,   35.37      ,   44.        , ...,    5.39333333,\n",
              "           0.19159456,    2.22333333],\n",
              "       ...,\n",
              "       [-122.72      ,   38.44      ,   48.        , ...,    4.11046512,\n",
              "           0.23479491,    2.6627907 ],\n",
              "       [-122.7       ,   38.31      ,   14.        , ...,    6.29740519,\n",
              "           0.18383518,    2.41117764],\n",
              "       [-122.14      ,   39.97      ,   27.        , ...,    5.47715736,\n",
              "           0.20574606,    3.17258883]])"
            ]
          },
          "metadata": {},
          "execution_count": 134
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "housing_tr = pd.DataFrame(X, columns=df_train_num.columns)\n"
      ],
      "metadata": {
        "id": "UKduRhpRtjhF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "housing_tr"
      ],
      "metadata": {
        "colab": {
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        "id": "h56iZGb9toKD",
        "outputId": "06d38c56-c226-4f46-d481-cc2d7f053626"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "      <th>income_cat</th>\n",
              "      <th>rooms_per_household</th>\n",
              "      <th>bedrooms_per_room</th>\n",
              "      <th>population_per_household</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-121.46</td>\n",
              "      <td>38.52</td>\n",
              "      <td>29.0</td>\n",
              "      <td>3873.0</td>\n",
              "      <td>797.0</td>\n",
              "      <td>2237.0</td>\n",
              "      <td>706.0</td>\n",
              "      <td>2.1736</td>\n",
              "      <td>72100.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.485836</td>\n",
              "      <td>0.205784</td>\n",
              "      <td>3.168555</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-117.23</td>\n",
              "      <td>33.09</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5320.0</td>\n",
              "      <td>855.0</td>\n",
              "      <td>2015.0</td>\n",
              "      <td>768.0</td>\n",
              "      <td>6.3373</td>\n",
              "      <td>279600.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.927083</td>\n",
              "      <td>0.160714</td>\n",
              "      <td>2.623698</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-119.04</td>\n",
              "      <td>35.37</td>\n",
              "      <td>44.0</td>\n",
              "      <td>1618.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>667.0</td>\n",
              "      <td>300.0</td>\n",
              "      <td>2.8750</td>\n",
              "      <td>82700.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.393333</td>\n",
              "      <td>0.191595</td>\n",
              "      <td>2.223333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-117.13</td>\n",
              "      <td>32.75</td>\n",
              "      <td>24.0</td>\n",
              "      <td>1877.0</td>\n",
              "      <td>519.0</td>\n",
              "      <td>898.0</td>\n",
              "      <td>483.0</td>\n",
              "      <td>2.2264</td>\n",
              "      <td>112500.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.886128</td>\n",
              "      <td>0.276505</td>\n",
              "      <td>1.859213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-118.70</td>\n",
              "      <td>34.28</td>\n",
              "      <td>27.0</td>\n",
              "      <td>3536.0</td>\n",
              "      <td>646.0</td>\n",
              "      <td>1837.0</td>\n",
              "      <td>580.0</td>\n",
              "      <td>4.4964</td>\n",
              "      <td>238300.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.096552</td>\n",
              "      <td>0.182692</td>\n",
              "      <td>3.167241</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",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>16507</th>\n",
              "      <td>-117.07</td>\n",
              "      <td>33.03</td>\n",
              "      <td>14.0</td>\n",
              "      <td>6665.0</td>\n",
              "      <td>1231.0</td>\n",
              "      <td>2026.0</td>\n",
              "      <td>1001.0</td>\n",
              "      <td>5.0900</td>\n",
              "      <td>268500.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.658342</td>\n",
              "      <td>0.184696</td>\n",
              "      <td>2.023976</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16508</th>\n",
              "      <td>-121.42</td>\n",
              "      <td>38.51</td>\n",
              "      <td>15.0</td>\n",
              "      <td>7901.0</td>\n",
              "      <td>1422.0</td>\n",
              "      <td>4769.0</td>\n",
              "      <td>1418.0</td>\n",
              "      <td>2.8139</td>\n",
              "      <td>90400.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.571932</td>\n",
              "      <td>0.179977</td>\n",
              "      <td>3.363188</td>\n",
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              "    <tr>\n",
              "      <th>16509</th>\n",
              "      <td>-122.72</td>\n",
              "      <td>38.44</td>\n",
              "      <td>48.0</td>\n",
              "      <td>707.0</td>\n",
              "      <td>166.0</td>\n",
              "      <td>458.0</td>\n",
              "      <td>172.0</td>\n",
              "      <td>3.1797</td>\n",
              "      <td>140400.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.110465</td>\n",
              "      <td>0.234795</td>\n",
              "      <td>2.662791</td>\n",
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              "    <tr>\n",
              "      <th>16510</th>\n",
              "      <td>-122.70</td>\n",
              "      <td>38.31</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3155.0</td>\n",
              "      <td>580.0</td>\n",
              "      <td>1208.0</td>\n",
              "      <td>501.0</td>\n",
              "      <td>4.1964</td>\n",
              "      <td>258100.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.297405</td>\n",
              "      <td>0.183835</td>\n",
              "      <td>2.411178</td>\n",
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              "    <tr>\n",
              "      <th>16511</th>\n",
              "      <td>-122.14</td>\n",
              "      <td>39.97</td>\n",
              "      <td>27.0</td>\n",
              "      <td>1079.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>625.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>3.1319</td>\n",
              "      <td>62700.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.477157</td>\n",
              "      <td>0.205746</td>\n",
              "      <td>3.172589</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16512 rows × 13 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bd25b8de-1cb7-4fea-8ac3-fe2a572089ad')\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-bd25b8de-1cb7-4fea-8ac3-fe2a572089ad 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-bd25b8de-1cb7-4fea-8ac3-fe2a572089ad');\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",
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              "          docLink.innerHTML = docLinkHtml;\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       longitude  latitude  ...  bedrooms_per_room  population_per_household\n",
              "0        -121.46     38.52  ...           0.205784                  3.168555\n",
              "1        -117.23     33.09  ...           0.160714                  2.623698\n",
              "2        -119.04     35.37  ...           0.191595                  2.223333\n",
              "3        -117.13     32.75  ...           0.276505                  1.859213\n",
              "4        -118.70     34.28  ...           0.182692                  3.167241\n",
              "...          ...       ...  ...                ...                       ...\n",
              "16507    -117.07     33.03  ...           0.184696                  2.023976\n",
              "16508    -121.42     38.51  ...           0.179977                  3.363188\n",
              "16509    -122.72     38.44  ...           0.234795                  2.662791\n",
              "16510    -122.70     38.31  ...           0.183835                  2.411178\n",
              "16511    -122.14     39.97  ...           0.205746                  3.172589\n",
              "\n",
              "[16512 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 136
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Manejo de texto y atributos categoricos"
      ],
      "metadata": {
        "id": "cbk632Utt110"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#from sklearn.preprocessing import OrdinalEncoder\n",
        "from sklearn.preprocessing import OneHotEncoder"
      ],
      "metadata": {
        "id": "m86uYU82to5S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_train[\"ocean_proximity\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CmGjK9p7xFHQ",
        "outputId": "231c141e-c0a7-4f03-c8dc-7cc1ecee39d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['INLAND', 'NEAR OCEAN', '<1H OCEAN', 'NEAR BAY', 'ISLAND'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 138
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "housing_cat=df_train[[\"ocean_proximity\"]]\n",
        "housing_cat"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "kE2sQwkayiJQ",
        "outputId": "21cbf3a2-a6e7-482e-b44d-88dab759cb0f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
              "  <div id=\"df-a09c4596-1b5a-4b74-8cc1-1d113d13bf76\">\n",
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              "      <td>&lt;1H OCEAN</td>\n",
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              "      <th>12661</th>\n",
              "      <td>INLAND</td>\n",
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              "    <tr>\n",
              "      <th>19263</th>\n",
              "      <td>&lt;1H OCEAN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19140</th>\n",
              "      <td>&lt;1H OCEAN</td>\n",
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              "      <th>19773</th>\n",
              "      <td>INLAND</td>\n",
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              "<p>16512 rows × 1 columns</p>\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a09c4596-1b5a-4b74-8cc1-1d113d13bf76');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "      ocean_proximity\n",
              "12655          INLAND\n",
              "15502      NEAR OCEAN\n",
              "2908           INLAND\n",
              "14053      NEAR OCEAN\n",
              "20496       <1H OCEAN\n",
              "...               ...\n",
              "15174       <1H OCEAN\n",
              "12661          INLAND\n",
              "19263       <1H OCEAN\n",
              "19140       <1H OCEAN\n",
              "19773          INLAND\n",
              "\n",
              "[16512 rows x 1 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 139
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cat_encoder = OneHotEncoder(sparse=False)\n",
        "housing_cat_1hot = cat_encoder.fit_transform(housing_cat)\n",
        "print(housing_cat_1hot)\n",
        "print(cat_encoder.categories_)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4mZAaO-kyD7j",
        "outputId": "a2e73386-5f2e-4c68-ff82-753adc13bff4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0. 1. 0. 0. 0.]\n",
            " [0. 0. 0. 0. 1.]\n",
            " [0. 1. 0. 0. 0.]\n",
            " ...\n",
            " [1. 0. 0. 0. 0.]\n",
            " [1. 0. 0. 0. 0.]\n",
            " [0. 1. 0. 0. 0.]]\n",
            "[array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
            "      dtype=object)]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Resumen de las transformaciones paso a paso\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "3KfEJpcJ1i4l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Read Data\n",
        "data_link = \"https://raw.githubusercontent.com/hernansalinas/Curso_aprendizaje_estadistico/main/datasets/Sesion_07_housing.csv\"\n",
        "df = pd.read_csv(data_link)"
      ],
      "metadata": {
        "id": "bXoD0mgT1iPB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 1. Clasification \n",
        "df[\"income_cat\"] = pd.cut(df[\"median_income\"],\n",
        "                               bins=[0., 1.5, 3.0, 4.5, 6., np.inf],\n",
        "                               labels=[1, 2, 3, 4, 5])\n",
        "\n",
        "df_ = df.copy()\n",
        "\n",
        "\n",
        "split = StratifiedShuffleSplit(n_splits=1, test_size=0.2, random_state=42)\n",
        "for train_index, test_index in split.split(df_, df_[\"income_cat\"]):\n",
        " strat_train_set = df_.loc[train_index]\n",
        " strat_test_set = df_.loc[test_index]\n"
      ],
      "metadata": {
        "id": "YSoNVC_91vFV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for set in (strat_train_set, strat_test_set):\n",
        " set.drop([\"income_cat\"], axis=1, inplace=True)"
      ],
      "metadata": {
        "id": "6Tfq3o8Y9X4B"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "strat_train_set"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "IXBuTdMZ-PD9",
        "outputId": "a855f4c7-1254-4428-e1a9-5914914ff1c0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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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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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
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              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "      <th>ocean_proximity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12655</th>\n",
              "      <td>-121.46</td>\n",
              "      <td>38.52</td>\n",
              "      <td>29.0</td>\n",
              "      <td>3873.0</td>\n",
              "      <td>797.0</td>\n",
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              "      <td>706.0</td>\n",
              "      <td>2.1736</td>\n",
              "      <td>72100.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15502</th>\n",
              "      <td>-117.23</td>\n",
              "      <td>33.09</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5320.0</td>\n",
              "      <td>855.0</td>\n",
              "      <td>2015.0</td>\n",
              "      <td>768.0</td>\n",
              "      <td>6.3373</td>\n",
              "      <td>279600.0</td>\n",
              "      <td>NEAR OCEAN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2908</th>\n",
              "      <td>-119.04</td>\n",
              "      <td>35.37</td>\n",
              "      <td>44.0</td>\n",
              "      <td>1618.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>667.0</td>\n",
              "      <td>300.0</td>\n",
              "      <td>2.8750</td>\n",
              "      <td>82700.0</td>\n",
              "      <td>INLAND</td>\n",
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              "    <tr>\n",
              "      <th>14053</th>\n",
              "      <td>-117.13</td>\n",
              "      <td>32.75</td>\n",
              "      <td>24.0</td>\n",
              "      <td>1877.0</td>\n",
              "      <td>519.0</td>\n",
              "      <td>898.0</td>\n",
              "      <td>483.0</td>\n",
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              "      <td>112500.0</td>\n",
              "      <td>NEAR OCEAN</td>\n",
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              "    <tr>\n",
              "      <th>20496</th>\n",
              "      <td>-118.70</td>\n",
              "      <td>34.28</td>\n",
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              "      <td>3536.0</td>\n",
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              "      <td>580.0</td>\n",
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              "      <td>238300.0</td>\n",
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              "      <th>15174</th>\n",
              "      <td>-117.07</td>\n",
              "      <td>33.03</td>\n",
              "      <td>14.0</td>\n",
              "      <td>6665.0</td>\n",
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              "      <td>268500.0</td>\n",
              "      <td>&lt;1H OCEAN</td>\n",
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              "      <td>-121.42</td>\n",
              "      <td>38.51</td>\n",
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              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19263</th>\n",
              "      <td>-122.72</td>\n",
              "      <td>38.44</td>\n",
              "      <td>48.0</td>\n",
              "      <td>707.0</td>\n",
              "      <td>166.0</td>\n",
              "      <td>458.0</td>\n",
              "      <td>172.0</td>\n",
              "      <td>3.1797</td>\n",
              "      <td>140400.0</td>\n",
              "      <td>&lt;1H OCEAN</td>\n",
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              "      <td>-122.70</td>\n",
              "      <td>38.31</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3155.0</td>\n",
              "      <td>580.0</td>\n",
              "      <td>1208.0</td>\n",
              "      <td>501.0</td>\n",
              "      <td>4.1964</td>\n",
              "      <td>258100.0</td>\n",
              "      <td>&lt;1H OCEAN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19773</th>\n",
              "      <td>-122.14</td>\n",
              "      <td>39.97</td>\n",
              "      <td>27.0</td>\n",
              "      <td>1079.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>625.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>3.1319</td>\n",
              "      <td>62700.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16512 rows × 10 columns</p>\n",
              "</div>\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "          const element = document.querySelector('#df-9264a96d-0c06-47a1-982d-8ad2c97ae262');\n",
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              "            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",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       longitude  latitude  ...  median_house_value  ocean_proximity\n",
              "12655    -121.46     38.52  ...             72100.0           INLAND\n",
              "15502    -117.23     33.09  ...            279600.0       NEAR OCEAN\n",
              "2908     -119.04     35.37  ...             82700.0           INLAND\n",
              "14053    -117.13     32.75  ...            112500.0       NEAR OCEAN\n",
              "20496    -118.70     34.28  ...            238300.0        <1H OCEAN\n",
              "...          ...       ...  ...                 ...              ...\n",
              "15174    -117.07     33.03  ...            268500.0        <1H OCEAN\n",
              "12661    -121.42     38.51  ...             90400.0           INLAND\n",
              "19263    -122.72     38.44  ...            140400.0        <1H OCEAN\n",
              "19140    -122.70     38.31  ...            258100.0        <1H OCEAN\n",
              "19773    -122.14     39.97  ...             62700.0           INLAND\n",
              "\n",
              "[16512 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 144
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 2 Add New variables to data\n",
        "housing = strat_train_set.copy()\n",
        "housing[\"rooms_per_household\"] = housing[\"total_rooms\"]/housing[\"households\"]\n",
        "housing[\"bedrooms_per_room\"] = housing[\"total_bedrooms\"]/housing[\"total_rooms\"]\n",
        "housing[\"population_per_household\"]=housing[\"population\"]/housing[\"households\"]\n"
      ],
      "metadata": {
        "id": "wS4gbfJz2Be5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "housing"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "7nSd_FV0-s0t",
        "outputId": "3b617f89-e4d6-493f-dfc7-80886abd12b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>longitude</th>\n",
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              "      <td>768.0</td>\n",
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              "      <td>279600.0</td>\n",
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              "      <td>0.160714</td>\n",
              "      <td>2.623698</td>\n",
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              "      <th>2908</th>\n",
              "      <td>-119.04</td>\n",
              "      <td>35.37</td>\n",
              "      <td>44.0</td>\n",
              "      <td>1618.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>667.0</td>\n",
              "      <td>300.0</td>\n",
              "      <td>2.8750</td>\n",
              "      <td>82700.0</td>\n",
              "      <td>INLAND</td>\n",
              "      <td>5.393333</td>\n",
              "      <td>0.191595</td>\n",
              "      <td>2.223333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14053</th>\n",
              "      <td>-117.13</td>\n",
              "      <td>32.75</td>\n",
              "      <td>24.0</td>\n",
              "      <td>1877.0</td>\n",
              "      <td>519.0</td>\n",
              "      <td>898.0</td>\n",
              "      <td>483.0</td>\n",
              "      <td>2.2264</td>\n",
              "      <td>112500.0</td>\n",
              "      <td>NEAR OCEAN</td>\n",
              "      <td>3.886128</td>\n",
              "      <td>0.276505</td>\n",
              "      <td>1.859213</td>\n",
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              "    <tr>\n",
              "      <th>20496</th>\n",
              "      <td>-118.70</td>\n",
              "      <td>34.28</td>\n",
              "      <td>27.0</td>\n",
              "      <td>3536.0</td>\n",
              "      <td>646.0</td>\n",
              "      <td>1837.0</td>\n",
              "      <td>580.0</td>\n",
              "      <td>4.4964</td>\n",
              "      <td>238300.0</td>\n",
              "      <td>&lt;1H OCEAN</td>\n",
              "      <td>6.096552</td>\n",
              "      <td>0.182692</td>\n",
              "      <td>3.167241</td>\n",
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              "      <th>...</th>\n",
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              "      <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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              "    <tr>\n",
              "      <th>15174</th>\n",
              "      <td>-117.07</td>\n",
              "      <td>33.03</td>\n",
              "      <td>14.0</td>\n",
              "      <td>6665.0</td>\n",
              "      <td>1231.0</td>\n",
              "      <td>2026.0</td>\n",
              "      <td>1001.0</td>\n",
              "      <td>5.0900</td>\n",
              "      <td>268500.0</td>\n",
              "      <td>&lt;1H OCEAN</td>\n",
              "      <td>6.658342</td>\n",
              "      <td>0.184696</td>\n",
              "      <td>2.023976</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12661</th>\n",
              "      <td>-121.42</td>\n",
              "      <td>38.51</td>\n",
              "      <td>15.0</td>\n",
              "      <td>7901.0</td>\n",
              "      <td>1422.0</td>\n",
              "      <td>4769.0</td>\n",
              "      <td>1418.0</td>\n",
              "      <td>2.8139</td>\n",
              "      <td>90400.0</td>\n",
              "      <td>INLAND</td>\n",
              "      <td>5.571932</td>\n",
              "      <td>0.179977</td>\n",
              "      <td>3.363188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19263</th>\n",
              "      <td>-122.72</td>\n",
              "      <td>38.44</td>\n",
              "      <td>48.0</td>\n",
              "      <td>707.0</td>\n",
              "      <td>166.0</td>\n",
              "      <td>458.0</td>\n",
              "      <td>172.0</td>\n",
              "      <td>3.1797</td>\n",
              "      <td>140400.0</td>\n",
              "      <td>&lt;1H OCEAN</td>\n",
              "      <td>4.110465</td>\n",
              "      <td>0.234795</td>\n",
              "      <td>2.662791</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19140</th>\n",
              "      <td>-122.70</td>\n",
              "      <td>38.31</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3155.0</td>\n",
              "      <td>580.0</td>\n",
              "      <td>1208.0</td>\n",
              "      <td>501.0</td>\n",
              "      <td>4.1964</td>\n",
              "      <td>258100.0</td>\n",
              "      <td>&lt;1H OCEAN</td>\n",
              "      <td>6.297405</td>\n",
              "      <td>0.183835</td>\n",
              "      <td>2.411178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19773</th>\n",
              "      <td>-122.14</td>\n",
              "      <td>39.97</td>\n",
              "      <td>27.0</td>\n",
              "      <td>1079.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>625.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>3.1319</td>\n",
              "      <td>62700.0</td>\n",
              "      <td>INLAND</td>\n",
              "      <td>5.477157</td>\n",
              "      <td>0.205746</td>\n",
              "      <td>3.172589</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16512 rows × 13 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4f7155ca-0cf6-4f3c-9cf7-5e0b3bfe1f16')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4f7155ca-0cf6-4f3c-9cf7-5e0b3bfe1f16 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-4f7155ca-0cf6-4f3c-9cf7-5e0b3bfe1f16');\n",
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              "            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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       longitude  latitude  ...  bedrooms_per_room  population_per_household\n",
              "12655    -121.46     38.52  ...           0.205784                  3.168555\n",
              "15502    -117.23     33.09  ...           0.160714                  2.623698\n",
              "2908     -119.04     35.37  ...           0.191595                  2.223333\n",
              "14053    -117.13     32.75  ...           0.276505                  1.859213\n",
              "20496    -118.70     34.28  ...           0.182692                  3.167241\n",
              "...          ...       ...  ...                ...                       ...\n",
              "15174    -117.07     33.03  ...           0.184696                  2.023976\n",
              "12661    -121.42     38.51  ...           0.179977                  3.363188\n",
              "19263    -122.72     38.44  ...           0.234795                  2.662791\n",
              "19140    -122.70     38.31  ...           0.183835                  2.411178\n",
              "19773    -122.14     39.97  ...           0.205746                  3.172589\n",
              "\n",
              "[16512 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 146
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "housing_labels = housing[\"median_house_value\"].copy()\n",
        "housing = housing.drop(\"median_house_value\", axis=1)\n"
      ],
      "metadata": {
        "id": "x2wSweWP9hEa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "housing.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rn7EP8yv9stA",
        "outputId": "4668c7f5-5038-442c-b429-acc5941541c8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "longitude                     0\n",
              "latitude                      0\n",
              "housing_median_age            0\n",
              "total_rooms                   0\n",
              "total_bedrooms              158\n",
              "population                    0\n",
              "households                    0\n",
              "median_income                 0\n",
              "ocean_proximity               0\n",
              "rooms_per_household           0\n",
              "bedrooms_per_room           158\n",
              "population_per_household      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 148
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "housing_num = housing.drop(\"ocean_proximity\", axis=1)\n",
        "housing_num\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "ozUFxlwB-DXu",
        "outputId": "67642cbd-4bb3-4b95-f302-593ee876b153"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>rooms_per_household</th>\n",
              "      <th>bedrooms_per_room</th>\n",
              "      <th>population_per_household</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12655</th>\n",
              "      <td>-121.46</td>\n",
              "      <td>38.52</td>\n",
              "      <td>29.0</td>\n",
              "      <td>3873.0</td>\n",
              "      <td>797.0</td>\n",
              "      <td>2237.0</td>\n",
              "      <td>706.0</td>\n",
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              "      <td>5.485836</td>\n",
              "      <td>0.205784</td>\n",
              "      <td>3.168555</td>\n",
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              "      <th>15502</th>\n",
              "      <td>-117.23</td>\n",
              "      <td>33.09</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5320.0</td>\n",
              "      <td>855.0</td>\n",
              "      <td>2015.0</td>\n",
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              "      <td>667.0</td>\n",
              "      <td>300.0</td>\n",
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              "      <td>0.191595</td>\n",
              "      <td>2.223333</td>\n",
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              "      <th>14053</th>\n",
              "      <td>-117.13</td>\n",
              "      <td>32.75</td>\n",
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              "      <td>519.0</td>\n",
              "      <td>898.0</td>\n",
              "      <td>483.0</td>\n",
              "      <td>2.2264</td>\n",
              "      <td>3.886128</td>\n",
              "      <td>0.276505</td>\n",
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              "      <th>20496</th>\n",
              "      <td>-118.70</td>\n",
              "      <td>34.28</td>\n",
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              "      <td>646.0</td>\n",
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              "      <td>580.0</td>\n",
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              "      <td>6.096552</td>\n",
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              "      <th>15174</th>\n",
              "      <td>-117.07</td>\n",
              "      <td>33.03</td>\n",
              "      <td>14.0</td>\n",
              "      <td>6665.0</td>\n",
              "      <td>1231.0</td>\n",
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              "      <td>166.0</td>\n",
              "      <td>458.0</td>\n",
              "      <td>172.0</td>\n",
              "      <td>3.1797</td>\n",
              "      <td>4.110465</td>\n",
              "      <td>0.234795</td>\n",
              "      <td>2.662791</td>\n",
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              "      <th>19140</th>\n",
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              "      <th>19773</th>\n",
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              "      <td>0.205746</td>\n",
              "      <td>3.172589</td>\n",
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              "<p>16512 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8a66ecda-5503-454a-b91b-d6bf2be30d8a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "      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",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\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",
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              "\n",
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              "          const element = document.querySelector('#df-8a66ecda-5503-454a-b91b-d6bf2be30d8a');\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",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       longitude  latitude  ...  bedrooms_per_room  population_per_household\n",
              "12655    -121.46     38.52  ...           0.205784                  3.168555\n",
              "15502    -117.23     33.09  ...           0.160714                  2.623698\n",
              "2908     -119.04     35.37  ...           0.191595                  2.223333\n",
              "14053    -117.13     32.75  ...           0.276505                  1.859213\n",
              "20496    -118.70     34.28  ...           0.182692                  3.167241\n",
              "...          ...       ...  ...                ...                       ...\n",
              "15174    -117.07     33.03  ...           0.184696                  2.023976\n",
              "12661    -121.42     38.51  ...           0.179977                  3.363188\n",
              "19263    -122.72     38.44  ...           0.234795                  2.662791\n",
              "19140    -122.70     38.31  ...           0.183835                  2.411178\n",
              "19773    -122.14     39.97  ...           0.205746                  3.172589\n",
              "\n",
              "[16512 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 149
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Imputer\n",
        "imp_mean = SimpleImputer( strategy='mean')\n",
        "imp_mean.fit(housing_num)\n",
        "imp_mean.statistics_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pgQt88vt_mhC",
        "outputId": "368a1abd-76e2-4f4e-f465-d2309b229868"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-1.19575635e+02,  3.56393144e+01,  2.86534036e+01,  2.62253979e+03,\n",
              "        5.34914639e+02,  1.41968738e+03,  4.97011810e+02,  3.87588428e+00,\n",
              "        5.44040595e+00,  2.12872772e-01,  3.09646921e+00])"
            ]
          },
          "metadata": {},
          "execution_count": 150
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = imp_mean.transform(housing_num)\n",
        "housing_tr = pd.DataFrame(X, columns = housing_num.columns)\n"
      ],
      "metadata": {
        "id": "5uirXRU7_6Gx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "housing_tr.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w6pdUi6mAIXN",
        "outputId": "6531fdb2-6a20-4f8c-e35d-21c0780d5ae7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "longitude                   0\n",
              "latitude                    0\n",
              "housing_median_age          0\n",
              "total_rooms                 0\n",
              "total_bedrooms              0\n",
              "population                  0\n",
              "households                  0\n",
              "median_income               0\n",
              "rooms_per_household         0\n",
              "bedrooms_per_room           0\n",
              "population_per_household    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 152
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 3. One hot encoder\n",
        "housing_cat = housing[[\"ocean_proximity\"]]\n",
        "cat_encoder = OneHotEncoder(sparse=False)\n",
        "housing_cat_1hot = cat_encoder.fit_transform(housing_cat)\n",
        "print(housing_cat_1hot)\n",
        "print(cat_encoder.categories_)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D0GMp0uP2q0S",
        "outputId": "11d04721-a2d3-4828-b5fc-c8f92a7cb634"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0. 1. 0. 0. 0.]\n",
            " [0. 0. 0. 0. 1.]\n",
            " [0. 1. 0. 0. 0.]\n",
            " ...\n",
            " [1. 0. 0. 0. 0.]\n",
            " [1. 0. 0. 0. 0.]\n",
            " [0. 1. 0. 0. 0.]]\n",
            "[array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
            "      dtype=object)]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "housing_cat_1hot"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yKrrWmpJAkt9",
        "outputId": "c34e8345-aefb-4517-8e53-2a4e12e56481"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0., 1., 0., 0., 0.],\n",
              "       [0., 0., 0., 0., 1.],\n",
              "       [0., 1., 0., 0., 0.],\n",
              "       ...,\n",
              "       [1., 0., 0., 0., 0.],\n",
              "       [1., 0., 0., 0., 0.],\n",
              "       [0., 1., 0., 0., 0.]])"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cat_encoder.categories_[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nc0h8-f7BKbe",
        "outputId": "10a80fe7-1f0b-487c-bc90-db2f6814a642"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 154
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_cat_1hot = pd.DataFrame(housing_cat_1hot, columns = cat_encoder.categories_[0])"
      ],
      "metadata": {
        "id": "TN9BnyzyBAVH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_cat_1hot"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "ynX0ijZVBWVA",
        "outputId": "29d46e6d-b735-48d9-d0c8-85c767f56699"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<p>16512 rows × 5 columns</p>\n",
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              "\n",
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              "\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6c4f3f3e-4911-4e6d-8052-a20349ea0fbb button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6c4f3f3e-4911-4e6d-8052-a20349ea0fbb');\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",
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              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       <1H OCEAN  INLAND  ISLAND  NEAR BAY  NEAR OCEAN\n",
              "0            0.0     1.0     0.0       0.0         0.0\n",
              "1            0.0     0.0     0.0       0.0         1.0\n",
              "2            0.0     1.0     0.0       0.0         0.0\n",
              "3            0.0     0.0     0.0       0.0         1.0\n",
              "4            1.0     0.0     0.0       0.0         0.0\n",
              "...          ...     ...     ...       ...         ...\n",
              "16507        1.0     0.0     0.0       0.0         0.0\n",
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              "16511        0.0     1.0     0.0       0.0         0.0\n",
              "\n",
              "[16512 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 156
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "housing_tr_ = housing_tr.join(df_cat_1hot)"
      ],
      "metadata": {
        "id": "L0V2IDSkA73v"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Escalamiento de variables"
      ],
      "metadata": {
        "id": "nuqTEA2KKMuP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cols=[\"longitude\", \"latitude\",\t\"housing_median_age\",\t\"total_rooms\",\\\n",
        "      \"total_bedrooms\",\t\"population\",\t\"households\",\t\"median_income\",\\\n",
        "      \"<1H OCEAN\",\t\"INLAND\",\t\"ISLAND\",\t\"NEAR BAY\", \"NEAR OCEAN\"]"
      ],
      "metadata": {
        "id": "gV-3PrxgBiQG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "housing_scale=housing_tr_[cols]"
      ],
      "metadata": {
        "id": "9o7BCU1mFX93"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
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          "data": {
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              "      <th></th>\n",
              "      <th>longitude</th>\n",
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            ],
            "text/plain": [
              "       longitude  latitude  housing_median_age  ...  ISLAND  NEAR BAY  NEAR OCEAN\n",
              "0        -121.46     38.52                29.0  ...     0.0       0.0         0.0\n",
              "1        -117.23     33.09                 7.0  ...     0.0       0.0         1.0\n",
              "2        -119.04     35.37                44.0  ...     0.0       0.0         0.0\n",
              "3        -117.13     32.75                24.0  ...     0.0       0.0         1.0\n",
              "4        -118.70     34.28                27.0  ...     0.0       0.0         0.0\n",
              "...          ...       ...                 ...  ...     ...       ...         ...\n",
              "16507    -117.07     33.03                14.0  ...     0.0       0.0         0.0\n",
              "16508    -121.42     38.51                15.0  ...     0.0       0.0         0.0\n",
              "16509    -122.72     38.44                48.0  ...     0.0       0.0         0.0\n",
              "16510    -122.70     38.31                14.0  ...     0.0       0.0         0.0\n",
              "16511    -122.14     39.97                27.0  ...     0.0       0.0         0.0\n",
              "\n",
              "[16512 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 161
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import MinMaxScaler\n",
        "\n",
        "scaler = MinMaxScaler()\n",
        "scaler.fit(housing_scale)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T_PP43ELBiSs",
        "outputId": "c07c34b5-0089-497c-94a5-6a659b3f5ebd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MinMaxScaler()"
            ]
          },
          "metadata": {},
          "execution_count": 165
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = scaler.transform(housing_scale)\n",
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R9prgk_KBiVr",
        "outputId": "95487878-7e20-45e9-cd08-3f8f2644903b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.28784861, 0.63549416, 0.54901961, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       [0.70916335, 0.05844846, 0.11764706, ..., 0.        , 0.        ,\n",
              "        1.        ],\n",
              "       [0.52888446, 0.30074389, 0.84313725, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       ...,\n",
              "       [0.1623506 , 0.62699256, 0.92156863, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       [0.16434263, 0.61317747, 0.25490196, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       [0.22011952, 0.78958555, 0.50980392, ..., 0.        , 0.        ,\n",
              "        0.        ]])"
            ]
          },
          "metadata": {},
          "execution_count": 166
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "housing_prepared = pd.DataFrame(X, columns = housing_scale.columns)"
      ],
      "metadata": {
        "id": "Ly0agGfdDLcc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(housing_prepared)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lvh0Q9t5DLfH",
        "outputId": "dd755706-0eb9-47ca-eb17-2c1df65ce74d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16512"
            ]
          },
          "metadata": {},
          "execution_count": 168
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(housing_labels)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_BMD0pf_DLix",
        "outputId": "7a680136-d23f-46f5-a6e4-9ba35ccada42"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16512"
            ]
          },
          "metadata": {},
          "execution_count": 169
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Consideremos las siguientes columnas: \n",
        "cols=[\"longitude\", \"latitude\",\t\"housing_median_age\",\t\"total_rooms\",\\\n",
        "      \"total_bedrooms\",\t\"population\",\t\"households\",\t\"median_income\"]\n",
        "housing_prep = housing_prepared[cols]"
      ],
      "metadata": {
        "id": "X9qgLpcUHprj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "housing_prep"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "MYol-pa8H4vu",
        "outputId": "58e07ea8-b448-4634-d07e-d509a3dff3ae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<style scoped>\n",
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              "\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
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              "      <td>0.549020</td>\n",
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              "      <td>0.128061</td>\n",
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              "      <td>0.131441</td>\n",
              "      <td>0.115426</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.709163</td>\n",
              "      <td>0.058448</td>\n",
              "      <td>0.117647</td>\n",
              "      <td>0.135168</td>\n",
              "      <td>0.137403</td>\n",
              "      <td>0.056392</td>\n",
              "      <td>0.143017</td>\n",
              "      <td>0.402574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.528884</td>\n",
              "      <td>0.300744</td>\n",
              "      <td>0.843137</td>\n",
              "      <td>0.041003</td>\n",
              "      <td>0.049613</td>\n",
              "      <td>0.018610</td>\n",
              "      <td>0.055639</td>\n",
              "      <td>0.163798</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.719124</td>\n",
              "      <td>0.022317</td>\n",
              "      <td>0.450980</td>\n",
              "      <td>0.047591</td>\n",
              "      <td>0.083280</td>\n",
              "      <td>0.025085</td>\n",
              "      <td>0.089806</td>\n",
              "      <td>0.119067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.562749</td>\n",
              "      <td>0.184910</td>\n",
              "      <td>0.509804</td>\n",
              "      <td>0.089790</td>\n",
              "      <td>0.103737</td>\n",
              "      <td>0.051403</td>\n",
              "      <td>0.107916</td>\n",
              "      <td>0.275617</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16507</th>\n",
              "      <td>0.725100</td>\n",
              "      <td>0.052072</td>\n",
              "      <td>0.254902</td>\n",
              "      <td>0.169380</td>\n",
              "      <td>0.197970</td>\n",
              "      <td>0.056700</td>\n",
              "      <td>0.186520</td>\n",
              "      <td>0.316554</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16508</th>\n",
              "      <td>0.291833</td>\n",
              "      <td>0.634431</td>\n",
              "      <td>0.274510</td>\n",
              "      <td>0.200819</td>\n",
              "      <td>0.228737</td>\n",
              "      <td>0.133580</td>\n",
              "      <td>0.264376</td>\n",
              "      <td>0.159584</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16509</th>\n",
              "      <td>0.162351</td>\n",
              "      <td>0.626993</td>\n",
              "      <td>0.921569</td>\n",
              "      <td>0.017831</td>\n",
              "      <td>0.026418</td>\n",
              "      <td>0.012753</td>\n",
              "      <td>0.031740</td>\n",
              "      <td>0.184811</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16510</th>\n",
              "      <td>0.164343</td>\n",
              "      <td>0.613177</td>\n",
              "      <td>0.254902</td>\n",
              "      <td>0.080099</td>\n",
              "      <td>0.093106</td>\n",
              "      <td>0.033773</td>\n",
              "      <td>0.093167</td>\n",
              "      <td>0.254928</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16511</th>\n",
              "      <td>0.220120</td>\n",
              "      <td>0.789586</td>\n",
              "      <td>0.509804</td>\n",
              "      <td>0.027293</td>\n",
              "      <td>0.035438</td>\n",
              "      <td>0.017433</td>\n",
              "      <td>0.036408</td>\n",
              "      <td>0.181515</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16512 rows × 8 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5640c433-8f64-4dfe-8c16-ea133adc2d6d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5640c433-8f64-4dfe-8c16-ea133adc2d6d');\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",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       longitude  latitude  ...  households  median_income\n",
              "0       0.287849  0.635494  ...    0.131441       0.115426\n",
              "1       0.709163  0.058448  ...    0.143017       0.402574\n",
              "2       0.528884  0.300744  ...    0.055639       0.163798\n",
              "3       0.719124  0.022317  ...    0.089806       0.119067\n",
              "4       0.562749  0.184910  ...    0.107916       0.275617\n",
              "...          ...       ...  ...         ...            ...\n",
              "16507   0.725100  0.052072  ...    0.186520       0.316554\n",
              "16508   0.291833  0.634431  ...    0.264376       0.159584\n",
              "16509   0.162351  0.626993  ...    0.031740       0.184811\n",
              "16510   0.164343  0.613177  ...    0.093167       0.254928\n",
              "16511   0.220120  0.789586  ...    0.036408       0.181515\n",
              "\n",
              "[16512 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 174
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "\n",
        "model = LinearRegression()\n",
        "model.fit(housing_prep, housing_labels)\n",
        "housing_predictions = model.predict(housing_prep)"
      ],
      "metadata": {
        "id": "s_wtBtmQDK62"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.score(housing_prep, housing_labels)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GaEAkKSDIpTY",
        "outputId": "ad705741-856d-42c3-b428-330d2be5eb6b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.6343991933140793"
            ]
          },
          "metadata": {},
          "execution_count": 176
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#¿Como autmatizar todo el proceso?\n",
        "#¿El modelo de regresion lineal es valido para lo construido, \n",
        "#que informacion nos da el score?\n",
        "#¿Se puede mejorar agregando nuevas caracteristicas?\n",
        "# ¿Puede ser ajustado a otro modelo?"
      ],
      "metadata": {
        "id": "RKkLt8lkIH3m"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}