assign_2.ipynb

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        "<a href=\"https://colab.research.google.com/github/dheerajpreetsingh/DAI_Assignment/blob/main/assign_2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "CJ5aNIb8Zbc1"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split, cross_val_score\n",
        "from sklearn.linear_model import LinearRegression, Ridge, Lasso\n",
        "from sklearn.tree import DecisionTreeRegressor\n",
        "from sklearn.ensemble import RandomForestRegressor\n",
        "from sklearn.svm import SVR\n",
        "from sklearn.neighbors import KNeighborsRegressor\n",
        "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score"
      ],
      "metadata": {
        "id": "sR-LKFN4Z9I-"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import statsmodels.api as sm\n",
        "from statsmodels.stats.diagnostic import linear_rainbow\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score"
      ],
      "metadata": {
        "id": "7Paky3fwezqP"
      },
      "execution_count": 14,
      "outputs": []
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        {
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              "     total_bill   tip     sex smoker   day    time  size\n",
              "0         16.99  1.01  Female     No   Sun  Dinner     2\n",
              "1         10.34  1.66    Male     No   Sun  Dinner     3\n",
              "2         21.01  3.50    Male     No   Sun  Dinner     3\n",
              "3         23.68  3.31    Male     No   Sun  Dinner     2\n",
              "4         24.59  3.61  Female     No   Sun  Dinner     4\n",
              "..          ...   ...     ...    ...   ...     ...   ...\n",
              "239       29.03  5.92    Male     No   Sat  Dinner     3\n",
              "240       27.18  2.00  Female    Yes   Sat  Dinner     2\n",
              "241       22.67  2.00    Male    Yes   Sat  Dinner     2\n",
              "242       17.82  1.75    Male     No   Sat  Dinner     2\n",
              "243       18.78  3.00  Female     No  Thur  Dinner     2\n",
              "\n",
              "[244 rows x 7 columns]"
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              "      <td>16.99</td>\n",
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              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
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              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 244,\n  \"fields\": [\n    {\n      \"column\": \"total_bill\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8.902411954856856,\n        \"min\": 3.07,\n        \"max\": 50.81,\n        \"num_unique_values\": 229,\n        \"samples\": [\n          22.12,\n          20.23,\n          14.78\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tip\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.3836381890011826,\n        \"min\": 1.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 123,\n        \"samples\": [\n          3.35,\n          1.5,\n          6.73\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Male\",\n          \"Female\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"smoker\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Yes\",\n          \"No\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"day\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Sat\",\n          \"Fri\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"time\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Lunch\",\n          \"Dinner\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"size\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 6,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          2,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "data = pd.read_csv(\"/content/drive/MyDrive/DAI Assignment 2/tips (data for regression problem).csv\")\n",
        "df = pd.DataFrame(data)\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mIoerQ92ZpF1",
        "outputId": "d7a9e924-6e51-442b-d1ae-bb3b7af344ae"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 244 entries, 0 to 243\n",
            "Data columns (total 7 columns):\n",
            " #   Column      Non-Null Count  Dtype  \n",
            "---  ------      --------------  -----  \n",
            " 0   total_bill  244 non-null    float64\n",
            " 1   tip         244 non-null    float64\n",
            " 2   sex         244 non-null    object \n",
            " 3   smoker      244 non-null    object \n",
            " 4   day         244 non-null    object \n",
            " 5   time        244 non-null    object \n",
            " 6   size        244 non-null    int64  \n",
            "dtypes: float64(2), int64(1), object(4)\n",
            "memory usage: 13.5+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "30VIQvNwZlHQ",
        "outputId": "eb25e2ef-a127-4ea7-eecc-0659bfdef308"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       total_bill         tip        size\n",
              "count  244.000000  244.000000  244.000000\n",
              "mean    19.785943    2.998279    2.569672\n",
              "std      8.902412    1.383638    0.951100\n",
              "min      3.070000    1.000000    1.000000\n",
              "25%     13.347500    2.000000    2.000000\n",
              "50%     17.795000    2.900000    2.000000\n",
              "75%     24.127500    3.562500    3.000000\n",
              "max     50.810000   10.000000    6.000000"
            ],
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              "\n",
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              "    <div>\n",
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              "        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>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>244.000000</td>\n",
              "      <td>244.000000</td>\n",
              "      <td>244.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>19.785943</td>\n",
              "      <td>2.998279</td>\n",
              "      <td>2.569672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>8.902412</td>\n",
              "      <td>1.383638</td>\n",
              "      <td>0.951100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>3.070000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>13.347500</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>17.795000</td>\n",
              "      <td>2.900000</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>24.127500</td>\n",
              "      <td>3.562500</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>50.810000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.000000</td>\n",
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              "      spin 1s steps(1) infinite;\n",
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              "  @keyframes spin {\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"total_bill\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 80.57800601480773,\n        \"min\": 3.07,\n        \"max\": 244.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          19.78594262295082,\n          17.795,\n          244.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tip\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 85.10953159599222,\n        \"min\": 1.0,\n        \"max\": 244.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          2.99827868852459,\n          2.9,\n          244.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"size\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 85.39686221774684,\n        \"min\": 0.9510998047322332,\n        \"max\": 244.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          244.0,\n          2.569672131147541,\n          3.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = df.drop('tip', axis=1)\n",
        "y = df['tip']"
      ],
      "metadata": {
        "id": "jDtT1WxOZn4n"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "numeric_features = X.select_dtypes(include=['float64', 'int64']).columns\n",
        "categorical_features = X.select_dtypes(include=['object']).columns"
      ],
      "metadata": {
        "id": "grG2_rULaCqr"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "preprocessor = ColumnTransformer(\n",
        "    transformers=[\n",
        "        ('num', StandardScaler(), numeric_features),\n",
        "        ('cat', OneHotEncoder(drop='first'), categorical_features)])"
      ],
      "metadata": {
        "id": "6EjcU2AlaI_s"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
      ],
      "metadata": {
        "id": "sTGiK0RXaYcm"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "models = {\n",
        "    'Linear Regression': LinearRegression(),\n",
        "    'Ridge Regression': Ridge(alpha=1.0),\n",
        "    'Lasso Regression': Lasso(alpha=0.1),\n",
        "    'Decision Tree Regression': DecisionTreeRegressor(max_depth=5, random_state=42),\n",
        "    'Random Forest Regression': RandomForestRegressor(n_estimators=100, random_state=42),\n",
        "    'Support Vector Regression (SVR)': SVR(kernel='rbf', C=1.0),\n",
        "    'K-Nearest Neighbors (KNN)': KNeighborsRegressor(n_neighbors=5)\n",
        "}"
      ],
      "metadata": {
        "id": "pizIpoo2aakj"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "results = {}\n",
        "for model_name, model in models.items():\n",
        "    pipeline = Pipeline(steps=[('preprocessor', preprocessor), ('regressor', model)])\n",
        "    pipeline.fit(X_train, y_train)\n",
        "    y_pred = pipeline.predict(X_test)\n",
        "    mse = mean_squared_error(y_test, y_pred)\n",
        "    mae = mean_absolute_error(y_test, y_pred)\n",
        "    r2 = r2_score(y_test, y_pred)\n",
        "    results[model_name] = {'MSE': mse, 'MAE': mae, 'R^2': r2}\n",
        "\n",
        "results_df = pd.DataFrame(results).T\n",
        "print(\"Model Evaluation Metrics:\\n\", results_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oKda_i3VaokG",
        "outputId": "c516edce-4039-4f78-f5a1-d2419d6f46d6"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Evaluation Metrics:\n",
            "                                       MSE       MAE       R^2\n",
            "Linear Regression                0.703357  0.667133  0.437302\n",
            "Ridge Regression                 0.700651  0.666859  0.439466\n",
            "Lasso Regression                 0.612210  0.654809  0.510221\n",
            "Decision Tree Regression         0.848990  0.690545  0.320792\n",
            "Random Forest Regression         0.918199  0.752882  0.265424\n",
            "Support Vector Regression (SVR)  0.709525  0.646897  0.432367\n",
            "K-Nearest Neighbors (KNN)        0.814505  0.716000  0.348381\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "best_model = Lasso(alpha=0.1)\n",
        "pipeline_lasso = Pipeline(steps=[('preprocessor', preprocessor), ('regressor', best_model)])\n",
        "pipeline_lasso.fit(X_train, y_train)\n",
        "\n",
        "# Extract coefficients as feature importances from Lasso\n",
        "coefficients = pipeline_lasso.named_steps['regressor'].coef_\n",
        "feature_names = numeric_features.tolist() + list(pipeline_lasso.named_steps['preprocessor'].transformers_[1][1].get_feature_names_out())\n",
        "feature_importance_df = pd.DataFrame({'Feature': feature_names, 'Coefficient': coefficients})\n",
        "feature_importance_df['Importance'] = feature_importance_df['Coefficient'].abs()  # Use absolute value for importance\n",
        "\n",
        "# Sort and display feature importance\n",
        "feature_importance_df = feature_importance_df.sort_values(by='Importance', ascending=False)\n",
        "print(\"\\nFeature Importance (Lasso):\\n\", feature_importance_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vRQPpcIra3bB",
        "outputId": "7fcc3f47-d051-4fde-e766-c5ca70cc53e6"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Feature Importance (Lasso):\n",
            "       Feature  Coefficient  Importance\n",
            "0  total_bill     0.731173    0.731173\n",
            "1        size     0.184788    0.184788\n",
            "2    sex_Male     0.000000    0.000000\n",
            "3  smoker_Yes    -0.000000    0.000000\n",
            "4     day_Sat    -0.000000    0.000000\n",
            "5     day_Sun     0.000000    0.000000\n",
            "6    day_Thur    -0.000000    0.000000\n",
            "7  time_Lunch    -0.000000    0.000000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### The Fators that significantly impact Tips are total_bill with a coefficient of 0.73 and size with a coefficient of 0.18"
      ],
      "metadata": {
        "id": "UbIhbW30eBIU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "*   Improving server attentiveness on larger party sizes could yield higher tips.\n",
        "*   Promotions or special service for high-spending customers could improve revenue.\n",
        "\n"
      ],
      "metadata": {
        "id": "ccQZTQ3vePrd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for feature in numeric_features:\n",
        "    plt.figure(figsize=(8, 4))\n",
        "    sns.scatterplot(data=df, x=feature, y='tip')\n",
        "    plt.title(f'Scatter Plot of {feature} vs. Tip')\n",
        "    plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 803
        },
        "id": "1PIvvgV-bFdJ",
        "outputId": "1a829118-7c4b-4137-d62d-ec6947d76c73"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x400 with 1 Axes>"
            ],
            "image/png": 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pNBosWbLErr7A5VRg99xzD+Li4jB+/HinkyLExcXh2WefxdSpUzFy5EhMmjTJmg6re/fuePjhh/0qq6syDBw4EJMnT8brr79u7e5x4MABrF+/HrfddhtGjRplt48///nPeOqpp5Cbm4v09HSMHj0a48aNw7JlyzB16lQMGzYMx48fxz//+U9cddVVfpXVmQ4dOmD48OGYOnUqLly4gJUrVyI3NxcPPPBA0I7RVnp6OkaNGoUXX3wRdXV1uPvuu+3Wb9++HbNmzcKdd96Jnj17orW1Ff/4xz8gl8sxceJE63b33Xcfdu7c6VdaNl/k5uZi+PDh+N///V80Nzdj5cqVSEtLw6OPPhrS4xJJRvgSGhBRMHz00UfCtGnThN69ewuJiYmCQqEQcnNzhdmzZwsXLlxw2H7t2rVCQUGBoFQqhdTUVGHkyJHCp59+al2/Z88e4Re/+IWgUqmEzMxMa3otAMKOHTus29XX1wu/+c1vhJSUFAGAXWqfrVu3Cn379hViY2MdUicVFxcLt99+u5CWliYolUqhW7duwl133SVs27bNuo0lHdbFixe9OgeWdEueUhq5SuX02WefCYWFhYJKpRKSk5OF8ePHC998843D65cvXy506dJFiImJ8Sod0zvvvGM91x06dBDuvfdeu1RHguBbOix3ZWhpaRGWLl0q5OTkCHFxcUJWVpawYMECuxRmgiAIP/30kzB27FghKSlJAGBNjdXU1CQ88sgjQkZGhqBSqYTCwkJh3759wsiRI+3SZwWSDmvDhg3CggULhPT0dEGlUgljx44Vzp49a7dtMNNhWfz1r38VAAhJSUl26ckEQRC+//57Ydq0aUKPHj2E+Ph4oUOHDsKoUaOEzz77zG67kSNHukxt5Yo/6bCef/554U9/+pOQlZUlKJVKoaioSPjqq698Oi5RJJMJQoj/+0hERERunTlzBjk5OXj++ecxf/78cBeHSLTYx5WIiIiIJIF9XImIyC9GoxGXLl1yu41Gown6dK5EFL0YuBIRkV/27t1rN/DLmXXr1mHKlCntUyAiinjs40pERH6pqanB4cOH3W7Tr18/ZGRktFOJiCjSMXAlIiIiIkng4CwiIiIikoSI7+NqNptRUVGBpKSkgObxJiIiIqLQEAQBdXV1yMzMREyM63bViA9cKyoqkJWVFe5iEBEREZEH586dQ9euXV2uj/jANSkpCcDlE5GcnBzm0hARERFRW3q9HllZWda4zZWID1wt3QOSk5MZuBIRERGJmKdunRycRURERESSwMCViIiIiCSBgSsRERERSQIDVyIiIiKSBAauRERERCQJDFyJiIiISBIYuBIRERGRJIQ1cN21axfGjx+PzMxMyGQybNmyxW69IAhYtGgRMjIyoFKpcOONN6KkpCQ8hSUiIiKKAjqDEacr61FcXoPTF+uhMxjDXSSrsAauDQ0NGDhwIF555RWn65977jmsXr0ar732Gvbv34+EhATcfPPNaGpqaueSEhEREUW+itpGzNpQjBte3IkJr+7FDX/aidkbilFR2xjuogEAZIIgCOEuBHB5poTNmzfjtttuA3C5tTUzMxOPPPII5s+fDwDQ6XTo1KkT3nzzTdxzzz1e7Vev10Oj0UCn03HmLCIiIiIXdAYjZm0oxhclVQ7rRuRpsWZSATRqRUiO7W28Jto+rmVlZfjpp59w4403WpdpNBpcd9112Ldvn8vXNTc3Q6/X2/0QERERkXtV9UanQSsA7CqpQlV9+LsMiDZw/emnnwAAnTp1slveqVMn6zpnVqxYAY1GY/3JysoKaTmJiIiIIoG+qcXt+joP69uDaANXfy1YsAA6nc76c+7cuXAXiYiIiEj0kuPj3K5P8rC+PYg2cO3cuTMA4MKFC3bLL1y4YF3njFKpRHJyst0PEREREbmnTVRgRJ7W6boReVpoE0PTv9UXog1cc3Jy0LlzZ2zbts26TK/XY//+/Rg6dGgYS0ZEREQUeTRqBZ6ZmO8QvI7I0+LZifkhG5jli9hwHry+vh6lpaXWv8vKynD06FF06NAB2dnZmDt3Lp566ink5eUhJycHCxcuRGZmpjXzABEREREFT2aKCmsmFaCq3oi6phYkxcdBm6gQRdAKhDlwPXToEEaNGmX9e968eQCAyZMn480338Sjjz6KhoYGPPjgg6itrcXw4cPx3//+F/Hx8eEqMhEREVFE06jFE6i2JZo8rqHCPK5ERERE4ib5PK5ERERERLYYuBIRERGRJDBwJSIiIiJJYOBKRERERJLAwJWIiIiIJIGBKxERERFJAgNXIiIiIpIEBq5EREREJAkMXImIiIhIEhi4EhEREZEkMHAlIiIiIklg4EpEREREksDAlYiIiIgkgYErEREREUkCA1ciIiIikgQGrkREREQkCQxciYiIiEgSGLgSERERkSQwcCUiIiIiSWDgSkRERESSEBvuAhARERGRI53BiKp6I/RNLUhWxUGboIBGrQh3scKKgSsRERGRyFTUNuKxTcfwRUmVddmIPC2emZiPzBRVGEsWXuwqQERERCQiOoPRIWgFgF0lVXh80zHoDMYwlSz8GLgSERERiUhVvdEhaLXYVVKFqnoGrkREREQkAvqmFrfr6zysj2QMXImIiIhEJDk+zu36JA/rIxkDVyIiIiIR0SYqMCJP63TdiDwttInRm1mAgSsRERGRiGjUCjwzMd8heB2Rp8WzE/OjOiUW02ERERERiUxmigprJhWgqt6IuqYWJMXHQZvIPK4MXImIiIhESKNmoNoWuwoQERERkSQwcCUiIiIiSWDgSkRERESSwMCViIiIiCSBgSsRERERSQIDVyIiIiKSBAauRERERCQJDFyJiIiISBIYuBIRERGRJDBwJSIiIiJJYOBKRERERJLAwJWIiIiIJIGBKxERERFJAgNXIiIiIpIEBq5EREREJAkMXImIiIhIEhi4EhEREZEkMHAlIiIiIklg4EpEREREksDAlYiIiIgkgYErEREREUmCqANXk8mEhQsXIicnByqVCj169MDy5cshCEK4i0ZERERE7Sw23AVw59lnn8Wf//xnrF+/Hv369cOhQ4cwdepUaDQazJkzJ9zFIyIiIqJ2JOrAde/evbj11lsxduxYAED37t2xYcMGHDhwIMwlIyIiIqL2JuquAsOGDcO2bdvw3XffAQC++uor7N69G2PGjHH5mubmZuj1ersfIiIiIpI+Ube4Pv7449Dr9ejduzfkcjlMJhP++Mc/4t5773X5mhUrVmDp0qXtWEoiIiIiag+ibnF999138c9//hNvvfUWjhw5gvXr1+OFF17A+vXrXb5mwYIF0Ol01p9z5861Y4mJiIiIKFRkgoiH6GdlZeHxxx/HzJkzrcueeuop/N///R++/fZbr/ah1+uh0Wig0+mQnJwcqqISERERkZ+8jddE3eJqMBgQE2NfRLlcDrPZHKYSEREREVG4iLqP6/jx4/HHP/4R2dnZ6NevH4qLi/Hiiy9i2rRp4S4aEREREbUzUXcVqKurw8KFC7F582ZUVlYiMzMTkyZNwqJFi6BQKLzaB7sKEBEREYmbt/GaqAPXYGDgSkRERCRuEdHHlYiIiIjIgoErEREREUmCqAdnERERUWjoDEZU1Ruhb2pBsioO2gQFNGrvxo8QhQsDVyIioihTUduIxzYdwxclVdZlI/K0eGZiPjJTVGEsGZF77CpAREQURXQGo0PQCgC7Sqrw+KZj0BmMYSoZkWcMXImIiKJIVb3RIWi12FVShap6Bq4kXgxciYiIooi+qcXt+joP64nCiYErERFRFEmOj3O7PsnDeqJwYuBKREQURbSJCozI0zpdNyJPC20iMwuQeDFwJSIiiiIatQLPTMx3CF5H5Gnx7MR8psQiUWM6LCIioiiTmaLCmkkFqKo3oq6pBUnxcdAmMo8riR8DVyIioiikUTNQJelhVwEiIiIikgQGrkREREQkCQxciYiIiEgSGLgSERERkSQwcCUiIiIiSWDgSkRERESSwMCViIiIiCSBgSsRERERSQIDVyIiIiKSBAauRERERCQJDFyJiIiISBIYuBIRERGRJDBwJSIiIiJJYOBKRERERJLAwJWIiIiIJIGBKxERERFJQmy4C0BEREREjnQGI6rqjdA3tSBZFQdtggIatSLcxQorBq5ERERgkEDiUlHbiMc2HcMXJVXWZSPytHhmYj4yU1RhLFl4MXAlIqKoxyCBxERnMDrcjwCwq6QKj286hjWTCqL2P1Xs40pERFHNU5CgMxjDVDKKVlX1Rof70WJXSRWq6qP3nmTgSkREUY1BAomNvqnF7fo6D+sjGQNXIiKKagwSSGyS4+Pcrk/ysD6SMXAlIqKoxiCBxEabqMCIPK3TdSPytNAmRmf/VoCBKxFFMZ3BiNOV9Sgur8Hpi/UR3ZcxmurqKwYJJDYatQLPTMx3uC9H5Gnx7MT8qB2YBQAyQRCEcBcilPR6PTQaDXQ6HZKTk8NdHCISiWgaRR5NdfVXRW0jHt90DLvanKNnJ+Yjg+eIwsSSoq2uqQVJ8XHQJkZuijZv4zUGrkQUdXQGI2ZtKHY6IGdEnjaiUs1EU10DFU1BApHYeBuvMY8rEUUdb0aRR0rAEk11DZRGzUCVSOzYx5WIok40jSKPproSUeRj4EpEUSeaRpFHU12JKPIxcCWiqBNNo8ijqa5EFPkYuBJR1ImmVDPRVFciinzMKkBEUSuaRpFHU12JSHqYVYCIyINoGkUeTXUlosjFrgJEREREJAkMXImIiIhIEhi4EhEREZEkMHAlIiIiIklg4EpEREREksDAlYiIiIgkQfSB648//ojf/va3SEtLg0qlwoABA3Do0KFwF4uIiMJAZzDidGU9istrcPpiPXQGY7iLRETtSNR5XGtqalBYWIhRo0bho48+QseOHVFSUoLU1NRwF42IiNpZRW0jHtt0DF+UVFmXjcjT4pmJ+chMUYWxZETUXkQ9c9bjjz+OPXv24IsvvvB7H5w5i4hI+nQGI2ZtKLYLWi1G5GmxZlIBJ1ggkjBv4zVRdxX417/+hcGDB+POO+9Eeno6CgoK8Ne//tXta5qbm6HX6+1+iIjIe2J8HF9Vb3QatALArpIqVNWHv4xEFHqi7irw/fff489//jPmzZuHJ554AgcPHsScOXOgUCgwefJkp69ZsWIFli5d2s4lJSKKDGJ9HK9vanG7vs7DeiKKDKLuKqBQKDB48GDs3bvXumzOnDk4ePAg9u3b5/Q1zc3NaG5utv6t1+uRlZXFrgJEFFI6gxFV9Ubom1qQrIqDNkEhuUfXYn4cf7qyHje8uNPl+m3zRqJHemI7loiIgsnbrgKibnHNyMhA37597Zb16dMHmzZtcvkapVIJpVIZ6qIREVmJtZXSV948jg9X4KpNVGBEnha7XATV2kRp/SeBiPwj6j6uhYWFOHXqlN2y7777Dt26dQtTiYiI7OkMRoegFbgc6D2+6Zgo+od6S8yP4zVqBZ6ZmI8ReVq75SPytHh2Yr7kWreJyD+ibnF9+OGHMWzYMDz99NO46667cODAAbz++ut4/fXXw100IiIA4m6l9FVyfJzb9Uke1odaZooKayYVoKreiLqmFiTFx0GbKL0uGUTkP1EHrkOGDMHmzZuxYMECLFu2DDk5OVi5ciXuvffecBeNiAiAuFspfSWFx/EaNQNVomgm6sAVAMaNG4dx48aFuxhERE6JvZXSF5bH8Y9vOmYXvPJxPBGJhegDVyKiUAskI4AUWil9wcfxRCRmDFyJKKoFmhEgElspA30cHwmpwYhInPzO43ro0CGcPHkSwOUUVYMHDw5qwYKFU74SkSvBzFtqCdaivZUyUlKDEVH7Clke1x9++AGTJk3Cnj17kJKSAgCora3FsGHD8Pbbb6Nr165+F5qIqD0FMyMABw15Tg0WzgkMiCgy+JzH9f7770dLSwtOnjyJS5cu4dKlSzh58iTMZjPuv//+UJSRiCgkIikjgBh48x8BIqJA+NziunPnTuzduxe9evWyLuvVqxfWrFmDoqKioBaOiCiUIikjgBjwPwJEFGo+t7hmZWWhpcXxw8dkMiEzMzMohSIiag+WjADOSDEjQLjxPwJEFGo+B67PP/88Zs+ejUOHDlmXHTp0CA899BBeeOGFoBaOiCiUOI1ocPE/AkQUaj5nFUhNTYXBYEBraytiYy/3NLD8npCQYLftpUuXgldSPzGrABF5wowAwVNR2+gyNVgGswoQkQshyyqwcuXKQMpFRCQ6zAgQPJzAgIhCyefAdfLkyaEoBxERRQj+R4CIQsWrwFWv11ubbfV6vdtt+TieiIiIiELBq8A1NTUV58+fR3p6OlJSUiCTyRy2EQQBMpkMJpMp6IUkIiIiIvIqcN2+fTs6dOgAAFi3bh2ysrIgl8vttjGbzSgvLw9+CYmIiIiI4EdWAblcbm19tVVdXY309HTRtbgyqwAREQXCknVC39SCZFUctAnsw0sUbCHLKmDpEtBWfX094uPjfd0diQw/oInaF99z4na+thGff3cR6UlKNLeaUWNowYGyS7i+Z0em9yIKA68D13nz5gEAZDIZFi5cCLVabV1nMpmwf/9+DBo0KOgFpPZTUduIxzYds5trfESeFs9MzEcmP6CJgk7K77loCLh1BiPOXjLgg2MV2FNabV1emJuGHG0C1Ap5xNWZSOy8DlyLi4sBXG5xPX78OBSKn9+sCoUCAwcOxPz584NfQmoXOoPR4QsUAHaVVOHxTcewZlIBP6CJgkjK7zkpB9y+qDW0YM32ErugFYD176dvGyDaa0QUqbwOXHfs2AEAmDp1KlatWsX+ohGmqt7o8AVqsaukClX1Rn5AEwWRVN9zUg64fdVgbHUIWi32lFajwdjaziUiIp/7uK5bty4U5aAw0ze1uF1f52E9EflGqu85TwH3T/qmCApc3Q82NnhYT0TB53PgSpEpOT7O7fokD+uJAhWsPpNi63vpqjyBvOfCWUdPAfcPNY3onBzvVXmCUY9QnosUlftrlBgfi+LyGlHcZ2IRyushtvd2qEVbfb3FwJUAANpEBUbkabHLSUvKiDwttIl8s1DoBKvPpNj6Xrorj7/vuXDX0VPADcCrbg7BqEeoz0V6khJFeVqnLcxFuVr898RPWPlZSdCPK1WhvB7hvu/bW7TV1xcx4S4AiYNGrcAzE/MxIk9rt3xEnhbPTszn//IoZDz1mdQZjO26n2DxVB4APr/nxFBHbaICRW3KbFGYm4bic7UeuzkEox7tcS40agWedXKNinLTMHV4d7y+6/uQHFeKQnk9xHDft6doq6+v2OJKVpkpKqyZVICqeiPqmlqQFB8HbSIfTVBoBWuQktgGO3lTnh7piT6958RQR41ageW39seTW447pIiaWpiDORuKMWFQF7f7CEY92utctP1cjI+T44Pj5zHrrWKHPq5iHlQXaqG8HmK479tTtNXXVwxcyY5GzUCV2lewBimJbbCTt+Xx5T0nljqmquMwLj8T0wpz0NxqhjI2BsXnajFnQzEGd0v12LUoGPVoz3Nhe42Ky2vw8vbSdjmulITyeojlvm8v0VZfXzFwJaKwCtbAQLENMAxFecRSR41agZE9O+LxTcfs+uh627UoGPUI17kQyzUQm1Cel2g759FWX1+xjysRhZVlkJIzvgwMDNZ+giUU5RFTHS2P0LfNG4ktM4Zh27yRWDOpwKtpUINRj3CdCzFdAzEJ5XmJtnMebfX1FQNXIgqrYA0MFNsAw1CUR4x17JGeiEHZqeiRntiu1ypc50Js10AsQnleou2cR1t9fSUTBEEIdyFCSa/XQ6PRQKfTcbYvIhGz5CwMdGBgsPYTLKEoj9jq6K9g1CNc5yJSrkGwhfK8RNs5j7b6ehuvMXAlIgohJhEnKeP9S+3F23iNg7OIiEKEScSjU6QEe7x/SYzY4kpEFAI6gxGzNhQ7zcc4Ik+LNZMKJBnMkHuREuzx/qX25m28xsFZREQh4E0ScYoskTTjEe9fEisGrkREIcAk4tEnkoI93r8kVgxciYhCgEnEo08kBXu8f0msGLgSEYUAk4hHn0gK9nj/klgxcCUiCgEmEfePzmDE6cp6FJfX4PTFekn1C42kYI/3L4kVswoQEYVQtCURD0QkjMivqG3E45uOYVebOjw7Md+r6XDFhvcvtRdOQHAFA1ciIvGLpPRLDPaIfMcJCIiISDK8GZEvleBPo2agShQq7ONKRERhF0kj8okodNjiSkTUjiJlOtBgi6QR+UQUOgxciSQsmoMgKdS9bRnjY2Ow+F9f47OTldZtpDb4KFQsI/J3uejjKqUR+UQUOgxciSQqEkZg+0sKdXdWxuG5aZhSmIO9p6thMJoA/DwdqJQGH4WCJf2SqxH50XxuiOhnzCpAJEGRNALbV1Kou7syFuamoSA7FS9vL7Vbvm3eSPRIT2yvIooWR+QTRSdmFSCKYFIagR3sR/pSqLu7Mu4prca0whyH5VIbfBSqrhockU9E7jBwJZIgqYzADsUjfSnU3VMZm1vNDsukNPhICl01iCgyMR0WkQRJYQS2zmB0CG6An/t0+juVpxTq7qmMylj7j14pDT4K1XUlIvIGA1ciCZLCnOjePNL3hxTq7q6Mw3PTUHyu1vq31AYfheq6EhF5g10FiCQo2COwQ9Ff0dtH+s6ODcBleaQw+txdGZ+eMABGkxk39k6X5OAjKXTVIKLIxcCVSKIyU1RYM6kg4BHYoeqv6M0jfWfHLsrTYuaoXEx786A1ZVTb8gSr7qEkhTL6QwpdNYgockkqcH3mmWewYMECPPTQQ1i5cmW4i0NBIIUk8oEIdf1sR2BbjnX6Yj3UyljEyGSIjZEhzc0xXfVXPHS2Bju/u4jB3VJR39zqVUtoW54SyifGx+LJzccxMCsFU4Z1R3OrGfFxchwpr8Hru05j2vAca8ooZ7lOgzH6vD2vTyiOqzMYUWtoQYOxFQ1GE1JUcUhPUob0PcSJAsQj0j8/iZyRTOB68OBB/OUvf0F+fn64i0JBEukjk9uzfs6OVZibhqmFOVjxn5NYemt/p8d01l9RrZBj9aQCrNtThgXvH7cuWztlCF7ZXoovSr2rj6dH+obmVtxzbTbW7Smzy2lqKXesTGa3v2CnugrX/Res456vbcTZSwas2V6CPaXV1uVFV85vqOogha4a0SDSPz+JXJHEBAT19fW4+uqr8eqrr+Kpp57CoEGDvG5x5QQE4iSFJPKBaM/6eZPs/ti5WqfHLC6vwYRX99otmzU6F8XlNXbBkLNl3tbHVUL57y7UYem/v3a6z8LcNMz/ZS+Hsm2ZMQyDslNdnwwvhev+C9ZxdQYj/nPiJ3xwrMKvaxIMnCggfCL985Oik7fxmiSyCsycORNjx47FjTfe6HHb5uZm6PV6ux8Sn0gfmdye9fOU7L4gK8XlMZ31VyzISnEIhpwts/BUH41agR7piRiUnYoe6YnWL1SzWXC5zz2l1YiVyxyWW/pP6gxGnK6sR3F5DU5frPc5BVO47r9gHbeq3oj0JKXf1yQYXF1XCr1I//wkckf0XQXefvttHDlyBAcPHvRq+xUrVmDp0qUhLhUFKtJHJrdn/bxNdu/smM76KzpLju9smS1/6mMwtrpdX2Ow36el/2QwHpGG6/4L1nH1TS0huSYkDZH++UnkjqhbXM+dO4eHHnoI//znPxEfH+/VaxYsWACdTmf9OXfuXIhLSf6I9JHJ7Vk/b5PdOzumpb+ibc7RtsnxXS2z5U99NCr3LXStpp97MVn6TwIISvL7cN1/wTpucnxcSK4JSUOkf34SuSPqwPXw4cOorKzE1VdfjdjYWMTGxmLnzp1YvXo1YmNjYTKZHF6jVCqRnJxs90PiI4Uk8oFoz/q5O1bhlWT37o5pSdu0bd5IbJkxDLkdEx32V3yuFoW5aU5f7299PJ2jHtoEbJkxDNvmjcSaSQXISFEF7RFpuO6/YB1Xm6hAZV1z0K8JSUOkf34SuSPqwPWGG27A8ePHcfToUevP4MGDce+99+Lo0aOQy+XhLiL5yVlLHxA5I5Pbs36ujmUZnX/qvN7jMW37K3bTJjjsb+3uMswenYeiINbH0znqpk1w6D8ZrEek4br/gnVcjVqB63t2xOzReQ7Ba1GEvIfItUj//CRyRxJZBWxdf/31zCoQQSJ9ZHJ71s9yLF1jC9QKOeQxMsg95HF1t68L+mboGluQoJRDFSdHojIWitiYoNfHl3N0urIeN7y40+W+ts0biR7piSE5ti885dcM1nFt87gajCZo2iGPK4lHpH9+UnTxNl4T/eAsimzBSCIvZqGsn7PgyJegzZWK2kY89t4xu3ythblpmD06D906qINyDFu+nKNgJ78PxfXxZvBYsI4b6e8fco/Xn6KR5FpcfcUWV4pEoUo+rjMYMeutYrug1aIwNw3j8jNxS//OYf2yrKhtdJn8PiPMideZXzOycGYqovbDFleiCOVqmlZn06L6qqre6DRoBS7nVp1WmBPU2av8YRlMJsZHpN4MHhNDOckzzkxFJE4MXIkkJpTBkTc5YcWQI1JMj0htW+Vaze4fYInh3JFnofzPIREFhoErkcSEMvm4NzlhozVHpLPHxgajCY/aBDh/mzzY7T6i9dxJDVvOicSLgSuRxIQy+bi7wU+FuWmorGvG4G6pfu9fqlw9Np4xKheHz9ZYl1ny3TqbipX5NaWDM1MRiZeo87gSkaNQJh+35Idsm6/VklVgVM+OHluadAYjTlfWo7i8Bqcv1ns9m5VYuXtsvGZ7CaYNz7EuW7u7DFMLcxxyqzK/prRwZioi8WKLK5GPwj3S2BJcuhpZbymLbTk1qjgkKGPR0NyKVrMAsyDA0NwKjVrhUP4EhRyLxvVFbWMLEhRyxMfKERsjg0Yd57GewRrQojMYUVnXbC1DgjIWKarLx/fl/F/QN6GmwQh9UyuSVbFIVSvQKdm76aMtXD02VivkKMhOxc39OqFvRjLi4+Q4Ul6Dxzcdwz3XZuPJW/rA2GoW1eAx8k5ifCyG56Zht5OW8+G5aUiM51dnJAv3Zzy5x3cfkQ/EMtLY08h623KqFXKsnlSAt/afxW+u64Z1e8rsHmXblt9d/bxpaQ3GgBZXeWTnjM5DpiYeT2w54dX5L69uwILNx+3qOjw3DU9PGIDstASP5bBw9tjYck7X7SnDy9tL7cr5zMR8zNlQjAmDuqBvpsbr45B4NDS3YkphDgTA7v4pzE3DlMIcNDS3hq9wFFJi+Ywn15jHlchLUsnR2bacs0bnori8BgXZqSgur3HZ//L5Owdi/sav/K5fMGa1cpdHtig3DWMGZOCJzSc8lu+Cvgnz3j3qtK7Dc9Pwp7sGed3y6qxelnPqbP9iyXdL/isur8G9b+zHtOE5KMhKQXOrGcrYGBSfq8Xa3WV46/7rMCg7+vp6RzqpfMZHKuZxJUJwH/lIYaSxzmDEeV0TJl2bjamFOThSXoOrs1Px8vZSTCvMsWsdtLWrpAo1DYHVLxgDWtzlkf2itBpTCnOcrmtbvpoGo9OgEgB2l1ajpsHodeDqbMBaQVaKy3O5p7Qai8b1Ddq9wMeW7S85Pg4Go8nlNWYf18gkhc94YuBKESzYj3zEPtLYWX0Lc9MwvMflgVbNrWa3r9c3uX/86al+gQ5o0RmMuORhIJe7OtiWz1NdPK235axPsadz2Wg0eb1/d/jYMjyCPbUwSYPYP+PpMmYVoIjkqb+lPyPdxTzS2FV995RWw3SlN5Ay1v3bPdnDgBNP9Qsk20FFbSNmbSiGvtH9F4O7OtiWz1NdPK1vy9KneNu8kdgyYxiu0rrvIxuMeyEU9zB5x/Kflbb3M7NDRDYxf8bTz9jiShEpFI98xNwK466++76vRlGu1mOO0dSEwOrnbbaDtmwDtIFZKS7LWJSbhkp9k9N9tC1faoLC7ajw1ATPA82cPZ63zdgQ6nuBjy3DS8xTC1NoiPkznn7GwJUiUige+fgbmLUHd/Vdu7sMm2cMw3P//RZTr/QRbZtVYNmt/VGpb8SyW/tj0dYTftfPny972wBt7e4yrJ5U4FDGwtw0zLqSVaDtF4uz8nVKjsfTEwbgic3H7YJXS1YBd/1bvXk83x73Ah9bhp+Ypham0BPzZzz9jFkFKCIFY4S7K5bWOH9bYYI92MYyIOv7qgZrLtG1u8tgsOln+fHcIqSoFWhoboXJLMBkFmAwmpCglONIeS2Wf/ANDEYT1Ao5lv66H/K7alDX1Ap1mxyqoVBcXoMJr+61/q1WyO1Gc3dLUyNREYsUtX0eV2/Of9s8rvGxMdA1tiAx3vl593VUcaD3gjuhvIeJyLVQvq/JNWYVoKgWykc+gbTCBHuwjasBWasnFWDOhmIYjCaMyNOic3K810FaaoICyz74xmWu12CwDd5VCjlmjc61BtttR3NvmzcS3Wz6lPpy/jslx6NTcrzX593Xx/OhbJHjY0ui8GBLu7hxcBZFJDEOrvB3sI2rKVTdDchat6cM04bnuK2vsyBt2vAchwkKvCmjp3pbyv/9xXr8cMmAWRuKccOLOzHh1b341covcLS8BqsnFUCtkNu9NhgBmi/nXUyP58V4D7enSJs6mIiCgy2uFLHENrjCn8E27loKG40ml/vbU1qNhWP74oHhOS7r6yxIc5ef1J8BQW1n8FozqQDxcXK7PLNrd5dZ+6FOG/5zrtlgBWi+nHexjSpuew8nKGOhkMegsq4JhhZTxOZ0ZRowInKFgStFNDE98vG1Nc9TS+HcG/Pc7q+pxeS27s6CNE/5SX1pcbQtv2WK1Df3lOGLNoOuLN0adpdW4w9j++LG3ulB/U+GL+ddjI/nLfews6lwIzGY83fqYE7UQBQdGLgSBYmnL05fW/M8tRQ+cUsft/tLUMbidGW9y/JYgrRDZ2usg6E6Jil9KqM7tuV31QVhT5uW1qYWU9Cn0vTlvIt1VLHOYHQIWoHL98Fjm47hZRFMRRmswDHYTyYiKagnIgauREHhzRenr615nloK5TEyl/sruhKQLnj/uMvyaNQKPDsxH2cvGbBmewle3l6KWaNz3eZ69aXF0bb8nqZInXYlTVcoHsX7et7F1sUEACrrml1PhVtShcq65rCWL5iBY7CfTHB+eaLIwsCVKECWL87DZ2swa3SuNY1TfJwcO7+7iFv6d7Y+7n1mYj4Wbz2BXhnJKMhKQatZQHaqCjExMpypbkBKYwtaTGaYBSA+To6/T7sWHRIUaDGZUdfYihazGXKZDIYWE8yCgBW3D8CSf32NT09WWsszIk+LGaNyMeutIy7LA1xu2dI1GiEIAgqyU1FcXusyj2pRnhbLb+tvra+rljXbdWqFHP+aVYjzuiYkKB0/amzTXqkVsdjwwHVItJnRyrIvXaMRamUsYmQyxMbIkOZjS56rVtSiPC2enjDA6b7E1MUEAGo9zCim87Ae8L5F1NeW02AHjsF+MhHJEzV4ulah6j7BbhkUTgxciQJUVW/E4bOXR8Wv21Nm17JYmJuGoVelWT/UM1NUWDy+Hxa8f8waJD71n5MoLq/F6kkFWLWtBL+5rpvDY/XC3DRMLczBhv1nMem6bpi/8StrqqunJwzAglv6QN94uXUwNkaGia/txTMT8x3KM7p3Rwy9Kg0Lt55wmUJrzoZiTBueg2mFOUhUxkKtlGPbyUo889FJPPLL3lj6r6+d9rOUAXjUSWquqYU5aLLJKQvA2ue1bfm82deK/5zE0lv7+9SSl5miworbB+BstQG1jS1Qxsag+Fwtlv77a5/3FQ4JbbIttNU2G0Nb3raI+tNyGuzAMdhPJiJ1ogZP1ypU3SfYLYPCjRMQEAWouLwG276tRHF5jfOpSvO01j6ItrlTZ43Otb7G8vvllk/n+ynMTbOuL8hOtRt9b9uq5a48tsd0tX/bQPLVe6/GP/efRcGVfqeuXjsiT4sxAzLsuibY7ndaYQ7W2gTj7srhaV8F2ak4dq7Wp5Y8XycWEJuzVQ14Ystxl9ft6dsG2OW6teVt3f09R20nkGhry4xhPvdbrqhtdNnPOKNNcBSNEzV4ulbP3zkQ8zd+FfT7XervIxI3b+M15nElClByfBwKslKcBhXA5T6IVfWXc1Datk7Zvsbyu7v92K4vyEqxLt9ls39P5fFm/7aUsTHW5e5eu6ukCukuBnbtKa2GTCbD1MIcFOameSyHp30VZKU41NkTb1oFPQlnXtEUdRxmj86znj+Lwtw0zB6dhxS168fr3tbd33MUihRiln7G2+aNxJYZw7Bt3kismVTgELQCP7fQOhOpEzV4ulY1DYHf7/4c19/9EvmCXQWIAqRNVOBMdYPbbSyPK20fa9qmnrL87ikdlavt2qZ0clUeb/cPXA6Kis/VevU6T9s0tZgwf+NXmDY8B0/e0gf1zSaX23ral2Wds0fArvreBfo4OdyPRzVqBbp1UGNcfiamFeagudUMZWwMKuua0b2D2m0rl7d19/cchSqFmLf9jMWaCSKUPF0rfVOr2/X+dp+I1m4ZJC4MXIkCpFEr0DXVffBiaXWybZ1SxsY4/G67zBlX27VN6eSqPN7u39KfdM6GYq9e52kbZWyMdSrXCYO6QBnrvk+mp30Bji157oJLjcr/VkGxjFrPSFHhlv6d7bIdDO6W6vHY3raI+ttyKobAUYyZIELJ07VKjnf/1e5v9g6xTdBB0YldBYiCoHNyvFePK20faxafq7U++rX8brusLdv1lpbQtvv3VJ7ic7UY7mL/RbladEhQ4G+TB6MgOxVzNhTDYDRZj+futSPytKisa3ZbbtuyJsbHosjN+fK0r7Z19hRcJihj/X6cLKbHoxq1Aj3SEzEoOxU90hO9Csy8fZQeyCN3Xx7th4o/50aqPF2r1ITQdJ+Ixm4ZJD4MXImCwNt55W23W7u7zNrv0/L7NxU6u76gFpYW0JNX1q/dXeZ0/57Kc+q8Hk9PGOC0nH+c0B+v7ijF9PWH8PL2UmvQajneNxU6LPl1f4eA01KG63t2dNiv7etH5Gnx3MR8NBhNeHLzcUwe1t2hnt7s69R5vUOdPQWX9U2tXl0fZ6T+eNSfe9Pddu6OEy2BY7h5uladkuMDupb+HpfXnNoDswoQecHXHJieHldatmtoboFGpYDRZEajsRUalQItZjMEATAJAhqaW5GgiIU8RgZ5jAwJylg0NLdaU195ehzq7DgGYytS1AoYW81oaG61249t+ROUsYiTy3CpwYj4ODkSFLHWQUCu6tj29Qp5DHSNRiQo46ytMZZRybZ5XJtbzUhRxaFHeiI6Jcfb7UvXeDknrOUcOMvj6u3Idm+vj61IGbXu670ZDY/cpc7TtQrVteQ9QqHgbbzGPq5EHlj6Th62mRr1TFUDslLV6JSstPvA9mVASXt80Ps6z72zcnV38mTQVdmd1+vnNE2nK+utLaOWPq+2ts0biU7J7vblnLd97/w576EafNTexHZvUuA8XatQXUveIxRO7CpA5IbtrFirJxWguLwG09cfwvT1h/DLlbswe0MxKmobw11MtzzNc9+eaZ10je6P5c0MUM6Esu8dH48SEYkHW1yJ3LD0nZw1OtdhNitAGvOhi2mee7XC/UeOpxmgXAn1yPZoG7VORCRWDFyJ3LAMzCnISnF4rG0h9vnQPc1zX2towemL9e0y33hMjAyFuWkuZ4CSx8j83neog0s+HiUiCj8GriRq3g6KChVL30lPCfhrPTwCDydP89wr42Jww592tktC/diYyzNoAbALXi0ZAwIJXAEGl0REkY6BK4lWuGcrAn7uO+kpAX9zixk6gzhbXRMUsW5bOS3ao9tDWoICK/5zEgXZqXYzQBWfq8U7B8rxwp0DQ3LcQIX7P1ChEIl1IqLIx8CVRKm9Zyty9SVu6Tu587uLKMrVOu0rWpibhr3fV6NTcrwov/gt89wDjq2cs0blYcepSuuyUHd70KgVWHprfzy+6Zhd1wsxD3QSw3+ggi0S60RE0YGBK4mSN7MVuQpyfG1JcpXuqmuqGp2Tlci8MtXmtd07YMm/TuALm+CvKDcNU4fnYNZbxbixd7rd8XWNRqiVsYiRyRDrIv9oIHQGIyrrmlHb2IIEhRwJylikqOKcTkbgbJ77C/omNLWY8Jed39ttb0moH6oWOSkNdBLLdK/BFIl1InKHTxciCwNXEiV/ZyvytSWpbbqrdXvK7FoCi660BGamqFBraMGYARmY0ib4k+Fyv8yk+Dinx7f031zxn5NYemv/oLRoOcvLWpibhtmj85CVokKXDmq77TNSVBjdOx2nK+utkxhU6Jrw1IcnYTCa7LZ1VY9gtsg564sqxi+XQP4DJVaRWCciV/h0IfIwcCVR8jahvC1/WpI8pbv64sprn79zIP6w5YTLrgILx/VFYnws5m/8yuH4ln0WZKcGpUXLVV5Wy3HGDcjAiJ4d0SXVPnitb2rFb97Yj1mjc1FcXuO0z+uIPK3LeoSyRU6sXy5Sn+7VmUisE5EzfLoQmTgBAYmSPwnlvWlJass23ZWzQM7y2poGo8tcqHtKq3F1dgoamltdHn9PaTUKslJclsMXVfXuy5KeHI+z1QaHiQUsdV27uwxTC3PsBmYBP7cuu6tHMMrflqcvl/acIKEtf/4DJXaRWCciZ/z5TiDxY4sriZI/CeX9aUnyNt2VvqnV7fpGowkGmNxuYzlGoC1anurZ3GpGc6vZ4ZGvpa4GowlzNhRj2vAcuz6vuR0TkZGiQnF5jdv9B7tFTsyPriNluldbkVgnImf4dCEyMXAl0fJ1EI8/LUnaRAWKvEh3lRzv/q3iTSuV5RiBtmh5qqflOG0/lG0DFoPR5NCXd+G4vjh9sR6JysDr6gsxf7mEekaucIjEOhE5w6cLkYmBK4maLwnlnbUkqRVyTBueg2FXpUHXaHSYIUqjVmDFhAH4ouSiy1ynI/K0SE3wrpXK1TaFuWkoPlcblBYtdy1mhblpqNQ34UJdM8bnZ9qtcxWwDM9Nw+Rh3XHbK3tgMJqw4vYBKMrTOrSCqhVyLBzXF2ZBQHF5TdAGUIn9y0VKWRC8FYl1ImqLTxcik0wQBCHchQglvV4PjUYDnU6H5OTkcBeHQqyittEamKkVcmumANuA1Nmgn4oaAwxGE5b++2v7dFd5Wjw3MR8ZKSq7fdvu69kr69se38KSVeCdA+VYdmt/67aB1tNZ9oJZo/IQIwNkMqBXpySngcjP6bpa0NRiwt7vq7F2d5k1u4BaIcfaKUPw6o5Saz0sy17ZXmrXvzYYA6h0BiNmbyh2+eXCARRE5C9vPrdJHLyN1xi4UsSxBGZmQcCyNoGohbOASGcwQmdoQatZQGOrCQajCSmqOKQnKa3bWfbtrpXKNjBUK+SQx8ggDyCPq2V/9c0tSFErYGw1w2BsRQe1AtUNLWhqNUF9ZVrXHacq8Zed3+Oabql42UPAd7qyHje8uNPpOrVCjo/mFKHVLKCuqQWpaoXLrArBCC4rahuxeOsJ9MpIRkFWCppbzUhVxyG7g9ohOwIRkS+8+dym8PM2XmNXAYo4lu4FpyvrnQataoUc+VkpOK9rwvdVDXaPvBuMJjzpJi2TN10XPG3jS75S28kRVk8qwHMfn7K2Hv9t8mBMX3/I6eu+8GJQk7u+pQajCTUGIwZlpwLAlXMZugFUmSkqLB7fDwved5xRK9wpsYhI2nzpckbix8CVIpazwMy2+0DbAOnpCQOw5N9fhzTnny/5Sm3TRDnLM+spE4KnQU2+9C0N9QAqncGIBZuPO/xHI9j5FsU4yQEREXmPeVwpYjkLzKYNz3E60cCukios2HwcvTOcP54IRs4/X/OV2qaJcpZn1lMmBE+DmnzJlRvqAVTtkW+xorYRszYU44YXd2LCq3txw592YvaGYlTUNga8byIiah8MXCliOQvM3E008EVJFQqyUlzuL9BWRV+DM9tWTmetq8Xnah0mEbDwZsSsJctA23PkLC2SPxNC+KI9WnTFOskBERF5j10FKGI5S//k6fG6u/WBtip6Cs5qDEboDD/3FbVt5XTWurp2dxlWTyoAAIesCd7m4/Q2LVKoc3+KoUWXXQaIiMSPgStFtLaBWXyc3O32KSrnAVIwWhU9BWe6xhbM3lBs7e9qm4PQ0rpqG6BaZsBaOK4vlozvh4bmVr9GzHo7cCGUuT9DnW9RzJMchBP7/BKR1DAdFrnl7xdboF+Itq9PUMYiLkaG6gYjkuJjoYyNga6xBYnxzvfr7tjucoYW5WmxYsKAy4OEbNYX5WmxeHw/tJrNUMpjYIYARUwM6ppb0XAlZVaCMhZ1TS3QNbZCo4pFUnwcmlpM0DW2QKOKQ3ycHPrGFtQaWpAYH4sL+iY8tumYtXtAYW4aCrJT8fL2UtzUJx1PTRiA+qZW1BiMaDGZcaS8BqN7pSNWHoNWkxkymQwCAH1jC1LUcVDHydFsMqOuqTXg8x3MAMbVfp0tbzCaQpZv8WxVA0ov1qO51Yz4ODmOlNfY5a7dNm8keqQnelWPRGUsFPIY1DYakRgfh0RlLBqaW6FrbP/gL5Dr5stAQV/LEc5zQkTSFBF5XFesWIH3338f3377LVQqFYYNG4Znn30WvXr18nofDFz95+8XW6BfiK6S608tzMGcDcUoyE6x/j64WyqenjAARpMZdU0t0KgUWNgm32jbY/9wyeAQnBbmpmH68Bwkx8ei5EI9OmlUUCvkMJkF7LNJ0D88Nw3Lb+uPpz74Btu+vWh9/fDcNEy5UibLdlMKc/D4pmN4ZmK+w4Cw4blpWDiuH+5940v06pxkrQ8ArJ5UgPV7yhwmQlg8vi/+9MkpTLwmy+n+bI8f6PkORhoqV/t96rb+WPbBN/jsZKXd8mcn5kOtkAe9RbeithGPvXfM7p6wvZ8Gd0t1m7XA0/14dXaK3+c+4Hr5ed10BiNmbSh22n3C17y8zsoRyP1IRNEpIgLXX/3qV7jnnnswZMgQtLa24oknnsCJEyfwzTffICEhwat9MHD1j79fbIF+Ibp7vW2rpO3vw3PTrPlGi8trXE7bumZSARqMJizaegKTrs1GfJwcusYWKGNjUHyuFnFyGQ6UXcKe0mrMGp3rcl+W49mm02pbPsvf0wpzsNZJFgPLfhb/uh+2Hq2wBsaejjvVzf7aHj/Q8x3IxALu9uvq/IVilixP99O4/Exc37OjyxZdf+7HUNXF23J5c2x3k08AnlugvSlHe58TIpI2b+M1UWcV+O9//4spU6agX79+GDhwIN58802Ul5fj8OHDLl/T3NwMvV5v90O+8zc9Ua2hBVOGdcer916NtVOGYNboXOusTt6kNXJ33D2l1dZR/7a/777yu7uMAbtKqlBZ14zHNh2ztvTd+8Z+zPjnEUxffwgvby9F/0yN9fXu9rXb5tiuymf5Oz1Z6XY/TS0mvLy91PrI2tNx3e2v7fEDPd+BpKFyt19X5y9Yaa+8Lcee0moM7pbqthuCP/cjEJq6eFsub44drD6/3p4fb8tFROSJpAZn6XQ6AECHDh1cbrNixQosXbq0vYoUsfz5YquobcQfttgnkS/MTcPqSQXWR4aevhA9Hdd21L+r313RNbZYv2Sdbe/L/lytb7u8vsnkdj9t13s6rqf9tX19oOfb30FLvlzHYBzP33I0NLcG9Hp390woB3wFet2ClcXB1+scrYPgiCh4RN3iastsNmPu3LkoLCxE//79XW63YMEC6HQ668+5c+fasZSRw9cvNmuezDatgXtKq7FuTxmmDc9x+jpfj2ubFqrt754S8ltaftu+1tO+PZXD3fLEePdZDJLj7f/vqHGR1cDb/bU9fqDn2980VL5cx2Acz99yhOp+9GbfgQi0XsHKy+vrdQ7lOSGi6CCZwHXmzJk4ceIE3n77bbfbKZVKJCcn2/2Q73z9YvPmkaE3X4jujluYm4bic7Uuf/eUkD9B8XOQ6Gxb22Xu9jXc5tiuymf5u1Lf7HY/JkHA3yYPxqv3Xo2/TR6MphaT2+3d7a/t8QM934GkoXK3X1fnLxhpr3wpR6juR2/3HYhA6+XL5BP+lqO9zwkRRQdJBK6zZs3CBx98gB07dqBr167hLk5U8PWLzdMjQwBefSFq1Ao8dVt/DG8TnFlGca/dXWb3+3Cb39fuLsPUwhyHwM5S5hR1nLU+zrZdu7sMs0fnoShP63Jfl7MKDMDJCp3Dcks5bP9+bNMxTC3McajP8Nw0LBrfD9PePIjp6w9Z+9rO3lCMqYU5KGpz3ovytFjy6/547/A5l+WyPb63AUiwAhhf9vv0hAE4dV7vsDwYExn4Uo5Azo+rezCUdfGmXP5MPrFt3khsmTEM2+aNxJpJBT6lHnNVjnCcEyKKDqLOKiAIAmbPno3Nmzfj888/R15ens/7YFaBwFjyM3pKT+RplPKnD49AXqckr473yMav0DsjGQVZKWgxCeiSGg9VnBw1DUYkqeIQHxsDfWMLEpRxiI+LwZJ/fY1Prwy4UivkWDiuLwqyU1Df1AqNKg7pSUprmStqG625QtUKOR4ccRVu6tMJP+mbAAAnKnQQBODa7h0QHxeDVLUCzSYz9I2X6x8fa5/H1WA0QdMmj2uyKhbJV/K46q/ksYyPk0Pf1AJ9YyuS42ORrIrD0x9+gw+O/+RwDmzzuNqed+Dy7FqNLSbIcDmPa0NzKxKUciQqYtFsMqO+yfdJCHQGIyrrmlHb2IJEhRxqRSxS1HFBzePa9v7x9r4KlkCPZ/v6hCt5XHWNRiQo45AYfzlnqeUeCXVdXJWrvY/trhzhPCdEJE0RkQ5rxowZeOutt7B161a73K0ajQYqlXetAgxc24e7xP7epmWqqjfiksGIuqZWhwTxFs4CYMtraxuNaG4xY69N3lVn+SNtv2RT1Qr8oU3eV1/KHQjbINr2mMFIuO9LGUKRw5WIiMgXERG4ymQyp8vXrVuHKVOmeLUPBq7tx99AzFOCd9vg9W+TB6NPRrJDUOVvXkt/8lkGc5apcLaYhSqHKxERka+8jddEnQ5LxDE1OeHPXPbWbARtgidLrtJpw3PsEtWnJ8dj53cXcUv/znb79SavpbNy+JpWKNgtlBp1+B6h+nvOiIiIwkXUgStJj6+BmKdsBNMKc6x/F+am4eOvf0JxeQ1+cVUHu+N4ztfZ4ryl1EP6Kdv0Pa6C7F0lVXh807GgtFAGszXXk1DlcCUiIgoVBq4UVt4mMC/MTcP9w6/CVz/UYlphDr6/2IAWk4BOVwZeucsnqVbIkaxSODwWt4xwv6lPunVwl6226XtC3ULZ3v1NQ5XDlYiIKFQYuFJYeQqesjuosXbKEBz/sRYCBBw8cwkrPyuxrrcEdpZ8ks4Ghy0c1xcLnQzA2lVShSc2H8eK2wegudXstG9u21ZdtUKOacNzUJCVguZWM+Lj5NaBZIG0ULZHa25b7s4Zc24SEZEYiXpwVjBwcJa4uctGUJibhrEDMpCeHI8TP+pw8Mwla99XW5aBRA1Gk9PBYU+O7YObV37hsgzb5o2ENlHhsW/u9xfr8X1VA9btKbMrh2Ug2VXaBFzVMbHt7r3iaZDYx3OL0Ktz8O9fMWQ2ICIiiojBWSQNgfTLtCQwbxs82WYVKMhOwcM39rRrabVleUyvTVRg4bi+1nykCYpYKBVyVNc349V7r7ZrHbXNVKBrbLG2LgoA4DyZBRKUsQ5BK3C5L64MwJ/uGuRVnZ1x1mXCtnW3pqEFJRfq7HLSBoM/A+pstWef3GjDc0tE5IiBKwXEWb/Mojwtlt/aH6leJrHPTFFh+a39UXqxHs2tZihjY1B8rtaaCmtPaTVmj/r5wYCzx/WtZjMe2fgVPrOZiGDtlCF4ZXupXReBwtw0rJ5UYJdmSxkbg1lvFdtt56xvaX1Tq9MWXwDYXVqN+qZWdPKzUbRtlwm1Qo7Vkwqwbk+ZXVaFUPR59TezAXPAhg7PLRGRcwxcyS2dwYjqBiNazQLMggBDcys0agW0CZcDHWf9Mr8oqcKTW45jXH4mRvbs6PaL1tKqVN1gxPT1h1xup1bKL//rIqArytVicmF37D1dDYPRhGnDc7Bme4nT1lHg5zRbRblp+OqHWqf9X9v2LQ3lKHxtogJFeVrruZw2PMdp624o+7z6Ihx9cqMFzy0RkWsx4S4AiVdFbSMe2fgVvq9qwNJ/f41frfwCt/95H274007M3lCMGkMLDp+tcfraPaXVSE9S4vFNx6AzGF3uf9aGYtzw4k6PQV+iMhZFeVqXAd0XpVVYt6cM04ZfTp9VkJXisnV0T2k1CrJSUJibhoXj++GpD0863c7SBcEilKPwNWoFlt/aH4W5aQDcl79tucLBmwwL5B+eWyIi1xi4klOWVp/eGckuW/4Wbj1hDRSdsYzUd/ZF27ZVqfhcrTVoa2tEnhZpCQos+XU/DL0qzWNAajm2OwnKWBRkp6KsqsFhWllbtgG1ZRS+qzIGOgo/VR2HcfmZ+NvkwVAr3D8MCUeOVZ3BiNOV9Sgur0FzqwmzRudCrZA73ZY5YP3H/LpERK4xcCWnLK0+7lr+LOtdUcZevr2cfdG2bVVau7sMUwtzHIJX27RUMgAms/skGJaA1XJsVxqaW/Hy9lLExrgYiXWFbSuqZSBZ2+DVWeosf2jUCozs2RHr956Bwdjqdbnag23r+IRX9+KW1btRXF6D1ZMKnAavzAHrP+bXJSJyjX1cySlLq4+nlktXCnPTUHyuFoDzL1rL/m0HWrWaBTz+qz5objXBLABpCQq7Ee5pCQr8pGtye1xLwGppwXUWdNuWzd12zlpRAx2F74ll/7WGFrs+r57KFUq+TsvLHLCBYX5dIiLX2OJKTllafTy1XHZNVTm0QFpSWa3dXebyizY5Ps460Kq4vAbT1x/C7/5xGONf3o2XPvsO6UlK9EhPtAsINWoFuqWpMdxFl4LhNgHp2t1lmD06D0VtylaUp8Xs0XlYu7vM7XbuWlE1agV6pCdiUHaqQxmDQaNWoJs2Ac+GsHXXF56m5bVtdQ9H+SJNqFv2iYikjBMQkFOWiQHys1JQXF7jNvE/APykb0J1vRFJqli0mgToG1tRoWvEqJ4d0dlJVgGdwYj/nPgJHxyrcNi3WiHHwnF9MbhbKuqbW605LAHgUoMRkAGLtn7tdPpWo8kMfePPLaEAHFpHvV0mhgDBknUhnOUqLq/BhFf3ulz/3u+HIjZGJqrzFgnEcO2JiNoLJyCggFhafRZvPYGphZcHYNkGmG1bfxqMJjz1wUmHXKgje3Z0uf+rs1Ow4P3jdstt013ZrivK02LmqFxMe/MggMuPp/93ZA8o42KQolK4/VJ31WrqzbJw8zfHajB56nOZeqUFmoJLDNeeiEhs2OJKblnyuJrMAkxmAQajCRqVfeuPzmDErA3FLvtjuso76awlb9boXJctvIW5aSjITnXoT8m8lqHlblpenn8SA84yRiR9bHGloPCm1cebvJPO9uGsJa8gK8UuMLW1p7Qa0wrt02+52z8Fh6tpednnksSAs4wRRRcGrhQwf/NOOhs97SmLgbP1ocpryVacn4U6mwKRPzjLGFH0YeBKAfM376SzljxPWQycrQ9FXku24jhin0sSG3+f9hCRdDEdFgUskBmlLC152+aNxJYZw5DbMdHlvmzzr3q7f394asVxNYUtEbUvzjJGFH0YuFLAAs07aZsXtZs2wem+2uZf9WX/voqUueJtp2g9fbGeATdFHM4yRhR92FUgiMLdJzIYx/d3H8HsA+lqXwDw71nDQ9rHUmcwornVhFfvvRrxcXIcKa/B2t1lMBhN1m2k0IrDrg4UDTjLGFH0YTqsIAl3oBCM44e7DuHmrP6WWcDmbCi2Bq/b5o0Udd5Sf9OTEUlRRW2jy4wXGVHwuUUUKbyN1xi4BkG4A4VgHD/cdQg3d/W3zR8rhXNxurIeN7y40+V6sQfeRL7iLGNE0sc8ru0o3CNbg3H8cNch3NzV35I/Vip5SzlghaINM14QRQ8GrkEQ7kAhGMcPdx3CzVP9Nao40be0WnDAChERRSpmFQiCcAcKwTh+uOsQbp7qnyqhFp1A0pMRERGJGQPXIAh3oBCM44e7DuEWSfUPND0ZERGRWHFwVpCEe2RrMI4f7jqEW6TVnwNWiIhIKphV4Ir2ClyB8AcKwTh+uOsQbtFefyIionBgVoEwCPfI1mAcP9x1CLdorz8REZGYsY8rEREREUkCA1ciIiIikgQGrkREREQkCQxciYiIiEgSGLgSERERkSQwcCUiIiIiSWDgSkRERESSEPF5XC3zK+j1+jCXhIiIiIicscRpnubFivjAta6uDgCQlZUV5pIQERERkTt1dXXQaDQu10f8lK9msxkVFRVISkqCTCYLd3HIS3q9HllZWTh37lzIp+ql9sPrGpl4XSMTr2tkEut1FQQBdXV1yMzMREyM656sEd/iGhMTg65du4a7GOSn5ORkUb2xKDh4XSMTr2tk4nWNTGK8ru5aWi04OIuIiIiIJIGBKxERERFJAgNXEiWlUonFixdDqVSGuygURLyukYnXNTLxukYmqV/XiB+cRURERESRgS2uRERERCQJDFyJiIiISBIYuBIRERGRJDBwJSIiIiJJYOBKYbVr1y6MHz8emZmZkMlk2LJli916QRCwaNEiZGRkQKVS4cYbb0RJSUl4CkteWbFiBYYMGYKkpCSkp6fjtttuw6lTp+y2aWpqwsyZM5GWlobExERMnDgRFy5cCFOJyRt//vOfkZ+fb01aPnToUHz00UfW9bymkeGZZ56BTCbD3Llzrct4baVnyZIlkMlkdj+9e/e2rpfyNWXgSmHV0NCAgQMH4pVXXnG6/rnnnsPq1avx2muvYf/+/UhISMDNN9+Mpqamdi4peWvnzp2YOXMmvvzyS3z66adoaWnBL3/5SzQ0NFi3efjhh/Hvf/8bGzduxM6dO1FRUYHbb789jKUmT7p27YpnnnkGhw8fxqFDhzB69Gjceuut+PrrrwHwmkaCgwcP4i9/+Qvy8/PtlvPaSlO/fv1w/vx568/u3but6yR9TQUikQAgbN682fq32WwWOnfuLDz//PPWZbW1tYJSqRQ2bNgQhhKSPyorKwUAws6dOwVBuHwN4+LihI0bN1q3OXnypABA2LdvX7iKSX5ITU0V3njjDV7TCFBXVyfk5eUJn376qTBy5EjhoYceEgSB71epWrx4sTBw4ECn66R+TdniSqJVVlaGn376CTfeeKN1mUajwXXXXYd9+/aFsWTkC51OBwDo0KEDAODw4cNoaWmxu669e/dGdnY2r6tEmEwmvP3222hoaMDQoUN5TSPAzJkzMXbsWLtrCPD9KmUlJSXIzMzEVVddhXvvvRfl5eUApH9NY8NdACJXfvrpJwBAp06d7JZ36tTJuo7EzWw2Y+7cuSgsLET//v0BXL6uCoUCKSkpdtvyuorf8ePHMXToUDQ1NSExMRGbN29G3759cfToUV5TCXv77bdx5MgRHDx40GEd36/SdN111+HNN99Er169cP78eSxduhRFRUU4ceKE5K8pA1ciCpmZM2fixIkTdn2rSLp69eqFo0ePQqfT4b333sPkyZOxc+fOcBeLAnDu3Dk89NBD+PTTTxEfHx/u4lCQjBkzxvp7fn4+rrvuOnTr1g3vvvsuVCpVGEsWOHYVINHq3LkzADiMdLxw4YJ1HYnXrFmz8MEHH2DHjh3o2rWrdXnnzp1hNBpRW1trtz2vq/gpFArk5ubimmuuwYoVKzBw4ECsWrWK11TCDh8+jMrKSlx99dWIjY1FbGwsdu7cidWrVyM2NhadOnXitY0AKSkp6NmzJ0pLSyX/fmXgSqKVk5ODzp07Y9u2bdZler0e+/fvx9ChQ8NYMnJHEATMmjULmzdvxvbt25GTk2O3/pprrkFcXJzddT116hTKy8t5XSXGbDajubmZ11TCbrjhBhw/fhxHjx61/gwePBj33nuv9XdeW+mrr6/H6dOnkZGRIfn3K7sKUFjV19ejtLTU+ndZWRmOHj2KDh06IDs7G3PnzsVTTz2FvLw85OTkYOHChcjMzMRtt90WvkKTWzNnzsRbb72FrVu3IikpydpnSqPRQKVSQaPRYPr06Zg3bx46dOiA5ORkzJ49G0OHDsUvfvGLMJeeXFmwYAHGjBmD7Oxs1NXV4a233sLnn3+Ojz/+mNdUwpKSkqz9zy0SEhKQlpZmXc5rKz3z58/H+PHj0a1bN1RUVGDx4sWQy+WYNGmS9N+v4U5rQNFtx44dAgCHn8mTJwuCcDkl1sKFC4VOnToJSqVSuOGGG4RTp06Ft9DklrPrCUBYt26ddZvGxkZhxowZQmpqqqBWq4UJEyYI58+fD1+hyaNp06YJ3bp1ExQKhdCxY0fhhhtuED755BPrel7TyGGbDksQeG2l6O677xYyMjIEhUIhdOnSRbj77ruF0tJS63opX1OZIAhCmGJmIiIiIiKvsY8rEREREUkCA1ciIiIikgQGrkREREQkCQxciYiIiEgSGLgSERERkSQwcCUiIiIiSWDgSkRERESSwMCViIiIiCSBgSsRkcRMmTLF62mPr7/+esydO9ftNt27d8fKlSutf8tkMmzZsgUAcObMGchkMhw9etSvshIRBRMDVyKiIPAmQAzGa0Lh4MGDePDBB8NdDCIij2LDXQAiIgqvjh07hrsIREReYYsrEVGApkyZgp07d2LVqlWQyWSQyWQ4c+YMdu7ciWuvvRZKpRIZGRl4/PHH0dra6vY1JpMJ06dPR05ODlQqFXr16oVVq1YFVL7W1lbMmjULGo0GWq0WCxcuhCAI1vVtuwoQEYkVW1yJiAK0atUqfPfdd+jfvz+WLVsGADCZTLjlllswZcoU/P3vf8e3336LBx54APHx8ViyZInT13Ts2BFmsxldu3bFxo0bkZaWhr179+LBBx9ERkYG7rrrLr/Kt379ekyfPh0HDhzAoUOH8OCDDyI7OxsPPPBA0M4BEVF7YOBKRBQgjUYDhUIBtVqNzp07AwCefPJJZGVl4eWXX4ZMJkPv3r1RUVGBxx57DIsWLXL6GgCQy+VYunSp9e+cnBzs27cP7777rt+Ba1ZWFl566SXIZDL06tULx48fx0svvcTAlYgkh10FiIhC4OTJkxg6dChkMpl1WWFhIerr6/HDDz+4fe0rr7yCa665Bh07dkRiYiJef/11lJeX+12WX/ziF3blGDp0KEpKSmAymfzeJxFRODBwJSISkbfffhvz58/H9OnT8cknn+Do0aOYOnUqjEZjuItGRBR27CpARBQECoXCrgWzT58+2LRpEwRBsLZ27tmzB0lJSejatavT11i2GTZsGGbMmGFddvr06YDKtn//fru/v/zyS+Tl5UEulwe0XyKi9sYWVyKiIOjevTv279+PM2fOoKqqCjNmzMC5c+cwe/ZsfPvtt9i6dSsWL16MefPmISYmxulrzGYz8vLycOjQIXz88cf47rvvsHDhQhw8eDCgspWXl2PevHk4deoUNmzYgDVr1uChhx4KRrWJiNoVA1cioiCYP38+5HI5+vbti44dO6KlpQX/+c9/cODAAQwcOBC///3vMX36dPzhD39w+Zry8nL87ne/w+233467774b1113Haqrq+1aX/1x3333obGxEddeey1mzpyJhx56iBMOEJEkyQTbZH5ERERERCLFFlciIiIikgQGrkREElVeXo7ExESXP4Gk0CIiEiN2FSAikqjW1lacOXPG5fru3bsjNpbJY4gocjBwJSIiIiJJYFcBIiIiIpIEBq5EREREJAkMXImIiIhIEhi4EhEREZEkMHAlIiIiIklg4EpEREREksDAlYiIiIgk4f8Dt5pcSZZYk4QAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.pairplot(df, diag_kind='kde')\n",
        "plt.suptitle(\"Pair Plot of Features\", y=1.02)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 787
        },
        "id": "5Ttz2rCne4Dk",
        "outputId": "6d2af362-99ff-4c79-e2ec-e9a0f762236b"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 750x750 with 12 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(5, 4))\n",
        "numeric_df = df.select_dtypes(include=[np.number])  # Select only numeric columns\n",
        "correlation_matrix = numeric_df.corr()  # Compute correlation matrix for numeric columns only\n",
        "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', linewidths=0.5)\n",
        "plt.title(\"Correlation Matrix (Numeric Features Only)\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "id": "jIteb2_He-oE",
        "outputId": "df16c34c-268b-4182-a59b-cedf3c509a10"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x400 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_numeric = df[numeric_features]\n",
        "X_numeric = sm.add_constant(X_numeric)\n",
        "y = df['tip']\n",
        "model = sm.OLS(y, X_numeric).fit()"
      ],
      "metadata": {
        "id": "dkwRu8mxfHnh"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "rainbow_stat, rainbow_p_value = linear_rainbow(model)\n",
        "print(f\"Rainbow Test: Statistic={rainbow_stat}, p-value={rainbow_p_value}\")\n",
        "if rainbow_p_value < 0.05:\n",
        "    print(\"The Rainbow test suggests that linearity is likely violated.\")\n",
        "else:\n",
        "    print(\"The Rainbow test suggests a linear relationship is appropriate.\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1RsxBDaLfXFW",
        "outputId": "eb2f071f-360f-4dd9-d75c-36a8e5ca68eb"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Rainbow Test: Statistic=1.1902656646832817, p-value=0.17048935693447634\n",
            "The Rainbow test suggests a linear relationship is appropriate.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(6, 4))\n",
        "sns.residplot(x=model.predict(X_numeric), y=model.resid, lowess=True, line_kws={'color': 'red'})\n",
        "plt.xlabel(\"Fitted Values\")\n",
        "plt.ylabel(\"Residuals\")\n",
        "plt.title(\"Residuals Plot\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 410
        },
        "id": "04OOnujrfc6y",
        "outputId": "4a2ffc1b-7c9d-4db2-876a-fd315546f3c9"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "linear_model = LinearRegression()\n",
        "pipeline_linear = Pipeline(steps=[('preprocessor', preprocessor), ('regressor', linear_model)])\n",
        "pipeline_linear.fit(X_train, y_train)\n",
        "\n",
        "y_pred_linear = pipeline_linear.predict(X_test)\n",
        "mse_linear = mean_squared_error(y_test, y_pred_linear)\n",
        "mae_linear = mean_absolute_error(y_test, y_pred_linear)\n",
        "r2_linear = r2_score(y_test, y_pred_linear)\n",
        "\n",
        "print(\"\\nLinear Regression Model Performance:\")\n",
        "print(f\"Mean Squared Error: {mse_linear}\")\n",
        "print(f\"Mean Absolute Error: {mae_linear}\")\n",
        "print(f\"R^2 Score: {r2_linear}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ajlOnEPHfiby",
        "outputId": "d1bbfafd-5559-44c7-b89b-56bf53c374ab"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Linear Regression Model Performance:\n",
            "Mean Squared Error: 0.7033566017436105\n",
            "Mean Absolute Error: 0.6671331480264895\n",
            "R^2 Score: 0.43730181943482505\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "yAAoUT7pfqBc"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}