{"metadata":{"kernelspec":{"display_name":"kaggle","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.9.23"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":105399,"databundleVersionId":12733338,"sourceType":"competition"}],"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":5,"nbformat":4,"cells":[{"id":"3bd76c7b","cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport warnings\nwarnings.filterwarnings('ignore')","metadata":{},"outputs":[],"execution_count":1},{"id":"209c6ceb","cell_type":"code","source":"# Load the parquet files\ntrain_df = pd.read_parquet('/kaggle/input/aeroclub-recsys-2025/train.parquet')\ntest_df = pd.read_parquet('/kaggle/input/aeroclub-recsys-2025/test.parquet')\n\nprint(f\"Train shape: {train_df.shape}, Test shape: {test_df.shape}\")\nprint(f\"Unique ranker_ids in train: {train_df['ranker_id'].nunique():,}\")\nprint(f\"Selected rate: {train_df['selected'].mean():.3f}\")","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Train shape: (18145372, 126), Test shape: (6897776, 125)\n","Unique ranker_ids in train: 105,539\n","Selected rate: 0.006\n"]}],"execution_count":2},{"id":"89bb2b18","cell_type":"code","source":"train_df.head()","metadata":{},"outputs":[{"data":{"text/html":["<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>Id</th>\n","      <th>bySelf</th>\n","      <th>companyID</th>\n","      <th>corporateTariffCode</th>\n","      <th>frequentFlyer</th>\n","      <th>nationality</th>\n","      <th>isAccess3D</th>\n","      <th>isVip</th>\n","      <th>legs0_arrivalAt</th>\n","      <th>legs0_departureAt</th>\n","      <th>...</th>\n","      <th>pricingInfo_isAccessTP</th>\n","      <th>pricingInfo_passengerCount</th>\n","      <th>profileId</th>\n","      <th>ranker_id</th>\n","      <th>requestDate</th>\n","      <th>searchRoute</th>\n","      <th>sex</th>\n","      <th>taxes</th>\n","      <th>totalPrice</th>\n","      <th>selected</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>True</td>\n","      <td>57323</td>\n","      <td>&lt;NA&gt;</td>\n","      <td>S7/SU/UT</td>\n","      <td>36</td>\n","      <td>False</td>\n","      <td>False</td>\n","      <td>2024-06-15T16:20:00</td>\n","      <td>2024-06-15T15:40:00</td>\n","      <td>...</td>\n","      <td>1.0</td>\n","      <td>1</td>\n","      <td>2087645</td>\n","      <td>98ce0dabf6964640b63079fbafd42cbe</td>\n","      <td>2024-05-17 03:03:08</td>\n","      <td>TLKKJA/KJATLK</td>\n","      <td>True</td>\n","      <td>370.0</td>\n","      <td>16884.0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>True</td>\n","      <td>57323</td>\n","      <td>123</td>\n","      <td>S7/SU/UT</td>\n","      <td>36</td>\n","      <td>True</td>\n","      <td>False</td>\n","      <td>2024-06-15T14:50:00</td>\n","      <td>2024-06-15T09:25:00</td>\n","      <td>...</td>\n","      <td>1.0</td>\n","      <td>1</td>\n","      <td>2087645</td>\n","      <td>98ce0dabf6964640b63079fbafd42cbe</td>\n","      <td>2024-05-17 03:03:08</td>\n","      <td>TLKKJA/KJATLK</td>\n","      <td>True</td>\n","      <td>2240.0</td>\n","      <td>51125.0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>True</td>\n","      <td>57323</td>\n","      <td>&lt;NA&gt;</td>\n","      <td>S7/SU/UT</td>\n","      <td>36</td>\n","      <td>False</td>\n","      <td>False</td>\n","      <td>2024-06-15T14:50:00</td>\n","      <td>2024-06-15T09:25:00</td>\n","      <td>...</td>\n","      <td>1.0</td>\n","      <td>1</td>\n","      <td>2087645</td>\n","      <td>98ce0dabf6964640b63079fbafd42cbe</td>\n","      <td>2024-05-17 03:03:08</td>\n","      <td>TLKKJA/KJATLK</td>\n","      <td>True</td>\n","      <td>2240.0</td>\n","      <td>53695.0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>True</td>\n","      <td>57323</td>\n","      <td>123</td>\n","      <td>S7/SU/UT</td>\n","      <td>36</td>\n","      <td>True</td>\n","      <td>False</td>\n","      <td>2024-06-15T14:50:00</td>\n","      <td>2024-06-15T09:25:00</td>\n","      <td>...</td>\n","      <td>1.0</td>\n","      <td>1</td>\n","      <td>2087645</td>\n","      <td>98ce0dabf6964640b63079fbafd42cbe</td>\n","      <td>2024-05-17 03:03:08</td>\n","      <td>TLKKJA/KJATLK</td>\n","      <td>True</td>\n","      <td>2240.0</td>\n","      <td>81880.0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>True</td>\n","      <td>57323</td>\n","      <td>&lt;NA&gt;</td>\n","      <td>S7/SU/UT</td>\n","      <td>36</td>\n","      <td>False</td>\n","      <td>False</td>\n","      <td>2024-06-15T14:50:00</td>\n","      <td>2024-06-15T09:25:00</td>\n","      <td>...</td>\n","      <td>1.0</td>\n","      <td>1</td>\n","      <td>2087645</td>\n","      <td>98ce0dabf6964640b63079fbafd42cbe</td>\n","      <td>2024-05-17 03:03:08</td>\n","      <td>TLKKJA/KJATLK</td>\n","      <td>True</td>\n","      <td>2240.0</td>\n","      <td>86070.0</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 126 columns</p>\n","</div>"],"text/plain":["   Id  bySelf  companyID  corporateTariffCode frequentFlyer  nationality  \\\n","0   0    True      57323                 <NA>      S7/SU/UT           36   \n","1   1    True      57323                  123      S7/SU/UT           36   \n","2   2    True      57323                 <NA>      S7/SU/UT           36   \n","3   3    True      57323                  123      S7/SU/UT           36   \n","4   4    True      57323                 <NA>      S7/SU/UT           36   \n","\n","   isAccess3D  isVip      legs0_arrivalAt    legs0_departureAt  ...  \\\n","0       False  False  2024-06-15T16:20:00  2024-06-15T15:40:00  ...   \n","1        True  False  2024-06-15T14:50:00  2024-06-15T09:25:00  ...   \n","2       False  False  2024-06-15T14:50:00  2024-06-15T09:25:00  ...   \n","3        True  False  2024-06-15T14:50:00  2024-06-15T09:25:00  ...   \n","4       False  False  2024-06-15T14:50:00  2024-06-15T09:25:00  ...   \n","\n","  pricingInfo_isAccessTP pricingInfo_passengerCount profileId  \\\n","0                    1.0                          1   2087645   \n","1                    1.0                          1   2087645   \n","2                    1.0                          1   2087645   \n","3                    1.0                          1   2087645   \n","4                    1.0                          1   2087645   \n","\n","                          ranker_id         requestDate    searchRoute   sex  \\\n","0  98ce0dabf6964640b63079fbafd42cbe 2024-05-17 03:03:08  TLKKJA/KJATLK  True   \n","1  98ce0dabf6964640b63079fbafd42cbe 2024-05-17 03:03:08  TLKKJA/KJATLK  True   \n","2  98ce0dabf6964640b63079fbafd42cbe 2024-05-17 03:03:08  TLKKJA/KJATLK  True   \n","3  98ce0dabf6964640b63079fbafd42cbe 2024-05-17 03:03:08  TLKKJA/KJATLK  True   \n","4  98ce0dabf6964640b63079fbafd42cbe 2024-05-17 03:03:08  TLKKJA/KJATLK  True   \n","\n","    taxes totalPrice selected  \n","0   370.0    16884.0        1  \n","1  2240.0    51125.0        0  \n","2  2240.0    53695.0        0  \n","3  2240.0    81880.0        0  \n","4  2240.0    86070.0        0  \n","\n","[5 rows x 126 columns]"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"execution_count":7},{"id":"e3174c6d","cell_type":"code","source":"train_df.info()","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","Index: 18145372 entries, 0 to 18146431\n","Columns: 126 entries, Id to selected\n","dtypes: Int64(2), bool(4), datetime64[ns](1), float64(41), int64(5), object(73)\n","memory usage: 16.7+ GB\n"]}],"execution_count":10},{"id":"f77d7ad3","cell_type":"markdown","source":"## Missing values Percent","metadata":{}},{"id":"42c54288","cell_type":"code","source":"# Check for missing values\nprint(\"\\n=== MISSING VALUES ===\")\nprint(\"Train missing values:\")\nprint(train_df.isnull().sum())\nprint(\"\\nSample submission missing values:\")\nprint(sample_submission.isnull().sum())","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["\n","=== MISSING VALUES ===\n","Train missing values:\n","Id                            0\n","bySelf                        0\n","companyID                     0\n","corporateTariffCode     9233925\n","frequentFlyer          12012727\n","                         ...   \n","searchRoute                   0\n","sex                           0\n","taxes                         0\n","totalPrice                    0\n","selected                      0\n","Length: 126, dtype: int64\n","\n","Sample submission missing values:\n","Id           0\n","ranker_id    0\n","selected     0\n","dtype: int64\n"]}],"execution_count":12},{"id":"2b0cacc1","cell_type":"code","source":"# Check if there are any missing values left\ntrain_na = (train_df.isnull().sum() / len(train_df)) * 100\ntrain_na = train_na.drop(train_na[train_na == 0].index).sort_values(ascending=False)\nmissing_data = pd.DataFrame({'Missing Ratio' :train_na})\nmissing_data.head()","metadata":{},"outputs":[{"data":{"text/html":["<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>Missing Ratio</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>legs1_segments3_baggageAllowance_weightMeasurementType</th>\n","      <td>99.999967</td>\n","    </tr>\n","    <tr>\n","      <th>legs1_segments3_aircraft_code</th>\n","      <td>99.999967</td>\n","    </tr>\n","    <tr>\n","      <th>legs1_segments3_seatsAvailable</th>\n","      <td>99.999967</td>\n","    </tr>\n","    <tr>\n","      <th>legs1_segments3_operatingCarrier_code</th>\n","      <td>99.999967</td>\n","    </tr>\n","    <tr>\n","      <th>legs1_segments3_marketingCarrier_code</th>\n","      <td>99.999967</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                    Missing Ratio\n","legs1_segments3_baggageAllowance_weightMeasurem...      99.999967\n","legs1_segments3_aircraft_code                           99.999967\n","legs1_segments3_seatsAvailable                          99.999967\n","legs1_segments3_operatingCarrier_code                   99.999967\n","legs1_segments3_marketingCarrier_code                   99.999967"]},"execution_count":3,"metadata":{},"output_type":"execute_result"}],"execution_count":3},{"id":"54a62d7d","cell_type":"code","source":"missing_data.info()","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","Index: 103 entries, legs1_segments3_marketingCarrier_code to legs0_segments0_departureFrom_airport_iata\n","Data columns (total 1 columns):\n"," #   Column         Non-Null Count  Dtype  \n","---  ------         --------------  -----  \n"," 0   Missing Ratio  103 non-null    float64\n","dtypes: float64(1)\n","memory usage: 1.6+ KB\n"]}],"execution_count":14},{"id":"d74bb748","cell_type":"code","source":"missing_data.plot(kind='bar', figsize=(12, 6), color='skyblue')\nplt.title('Missing Values in Train Dataset')","metadata":{},"outputs":[{"data":{"text/plain":["Text(0.5, 1.0, 'Missing Values in Train Dataset')"]},"execution_count":15,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":15},{"id":"05ca3fc0","cell_type":"code","source":"print(\"number of columns with missing ratios larger than 90%:\", missing_data[missing_data['Missing Ratio'] > 90].shape[0])\nprint(\"number of columns with missing ratios larger than 80%:\", missing_data[missing_data['Missing Ratio'] > 80].shape[0])\nprint(\"number of columns with missing ratios larger than 50%:\", missing_data[missing_data['Missing Ratio'] > 50].shape[0])","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["number of columns with missing ratios larger than 90%: 50\n","number of columns with missing ratios larger than 80%: 62\n","number of columns with missing ratios larger than 50%: 76\n"]}],"execution_count":17},{"id":"ad54dfd9","cell_type":"code","source":"columns_with_missing_data = set(missing_data.index.values.tolist())\ncolumns_without_missing_data = set(train_df.columns.tolist()) - columns_with_missing_data","metadata":{},"outputs":[],"execution_count":14},{"id":"4eb98bef","cell_type":"code","source":"columns_with_few_missing_data = set(missing_data[missing_data['Missing Ratio'] < 50].index.values.tolist()) ^ columns_without_missing_data","metadata":{},"outputs":[],"execution_count":25},{"id":"8e1eb47c","cell_type":"code","source":"len(columns_without_missing_data), len(columns_with_few_missing_data)","metadata":{},"outputs":[{"data":{"text/plain":["(23, 50)"]},"execution_count":27,"metadata":{},"output_type":"execute_result"}],"execution_count":27},{"id":"42e42383","cell_type":"code","source":"print(\"number of columns containg 'segments3' in missing_data:\", missing_data[missing_data.index.str.contains('segments3')].shape[0])\nprint(\"number of columns containg 'segments3' in train_data:\", train_df.columns.str.contains('segments3').sum())","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["number of columns containg 'segments3' in missing_data: 24\n","number of columns containg 'segments3' in train_data: 24\n"]}],"execution_count":30},{"id":"2ec2d79e","cell_type":"code","source":"cat_cols = train_df.select_dtypes(include=['bool', 'int', 'object']).columns.tolist()\nlen(cat_cols)","metadata":{},"outputs":[{"data":{"text/plain":["84"]},"execution_count":94,"metadata":{},"output_type":"execute_result"}],"execution_count":94},{"id":"94a8eebf","cell_type":"markdown","source":"## All Features","metadata":{}},{"id":"5827b308","cell_type":"markdown","source":"### Identifiers and Metadata\n\n- Id - Unique identifier for each flight option\n- ranker_id -Group identifier for each search session (key grouping variable for ranking)\n- profileId -User identifier\n- companyID -Company identifier","metadata":{}},{"id":"a90713a8","cell_type":"code","source":"print('total row:', len(train_df))\nprint('Unique ids:', train_df.Id.nunique())","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["total row: 18145372\n","Unique ids: 18145372\n"]}],"execution_count":7},{"id":"91e4eb96","cell_type":"code","source":"print('Unique ranker_ids in train:', train_df.ranker_id.nunique())\nprint('Unique ranker_ids in test:', test_df.ranker_id.nunique())\nprint('Intersection of ranker_ids:', len(set(train_df.ranker_id) & set(test_df.ranker_id)))","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Unique ranker_ids in train: 105539\n","Unique ranker_ids in test: 45231\n","Intersection of ranker_ids: 0\n"]}],"execution_count":8},{"id":"424532a6","cell_type":"code","source":"group_df = train_df.groupby('ranker_id').size().reset_index(name='count').sort_values(by='count', ascending=False)\ngroup_df['count'].describe()","metadata":{},"outputs":[{"data":{"text/plain":["count    105539.000000\n","mean        171.930490\n","std         445.940118\n","min           1.000000\n","25%          19.000000\n","50%          50.000000\n","75%         154.000000\n","max        8236.000000\n","Name: count, dtype: float64"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"execution_count":10},{"id":"90e6da40","cell_type":"code","source":"np.log(group_df['count']).plot(kind='hist', bins=500, color='skyblue')","metadata":{},"outputs":[{"data":{"text/plain":["<Axes: ylabel='Frequency'>"]},"execution_count":35,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAkQAAAGdCAYAAADzOWwgAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8ekN5oAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAqNUlEQVR4nO3dfVjUdb7/8ReiILqAIgFySWqamfd3xZI3l64c0ciT6XVOpqYZa6c9WCqlK+e02pVueLOyVppuZ1P0qOvNtdW2VhqL5k1iJop326qZhcadpjJCKyDM749+zHG8Zxj4zvB5Pq7reynz/TDz/sruznO/8x3Gx2632wUAAGCwBlYPAAAAYDWCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxGlo9gDeorKxUbm6uAgMD5ePjY/U4AADgLtjtdl2+fFmRkZFq0OD254AIoruQm5urqKgoq8cAAAAuOHPmjFq1anXbNQTRXQgMDJT00z9oUFCQxdMAAIC7YbPZFBUV5Xgevx2C6C5UvUwWFBREEAEA4GXu5nIXLqoGAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8SwNopSUFD300EMKDAxUWFiYRowYoePHjzutGThwoHx8fJy2559/3mlNTk6O4uPj1aRJE4WFhWn69Om6evWq05rPPvtMvXr1kr+/v9q3b6+0tLTaPjwAAOAlLA2iHTt2KDExUXv37lV6errKy8s1ZMgQlZSUOK2bNGmS8vLyHNuCBQsc+yoqKhQfH6+ysjLt2bNHq1atUlpammbNmuVYc/r0acXHx2vQoEHKzs7W1KlT9ctf/lJbt26ts2MFAACey8dut9utHqLKuXPnFBYWph07dmjAgAGSfjpD1KNHDy1evPim3/PJJ5/oscceU25ursLDwyVJy5cv169//WudO3dOfn5++vWvf62PPvpIR48edXzf6NGjdenSJW3ZsuWOc9lsNgUHB6uoqIgPdwUAwEtU5/nbo64hKioqkiSFhIQ43b527VqFhoaqS5cuSk5O1o8//ujYl5mZqa5duzpiSJLi4uJks9l07Ngxx5rY2Fin+4yLi1NmZuZN5ygtLZXNZnPaAABA/eUxQVRZWampU6eqb9++6tKli+P2MWPGaM2aNdq+fbuSk5P1v//7vxo3bpxjf35+vlMMSXJ8nZ+ff9s1NptN//znP2+YJSUlRcHBwY4tKirKbcdpknkHz1s9AgAAd6Wh1QNUSUxM1NGjR7V7926n25977jnH37t27aqWLVtq8ODBOnXqlNq1a1crsyQnJyspKcnxtc1mI4oAAKjHPOIM0eTJk7V582Zt375drVq1uu3a6OhoSdLXX38tSYqIiFBBQYHTmqqvIyIibrsmKChIAQEBNzyGv7+/goKCnDYAAFB/WRpEdrtdkydP1vvvv69t27apbdu2d/ye7OxsSVLLli0lSTExMTpy5IgKCwsda9LT0xUUFKROnTo51mRkZDjdT3p6umJiYtx0JAAAwJtZGkSJiYlas2aN1q1bp8DAQOXn5ys/P99xXc+pU6c0Z84cZWVl6dtvv9WHH36o8ePHa8CAAerWrZskaciQIerUqZOefvppHTp0SFu3btUrr7yixMRE+fv7S5Kef/55ffPNN5oxY4b+8Y9/6O2339bGjRs1bdo0y44dAAB4ELuFJN10W7lypd1ut9tzcnLsAwYMsIeEhNj9/f3t7du3t0+fPt1eVFTkdD/ffvutfdiwYfaAgAB7aGio/aWXXrKXl5c7rdm+fbu9R48edj8/P/t9993neIy7UVRUZJd0w+Pi9lIOnLN6BACAwarz/O1Rv4fIU/F7iFwz7+B5zewZavUYAABDee3vIQIAALACQQTUIX43EwB4JoIIAAAYjyCCA2cvAACmIogAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIIIR5h08b/UIAAAPRhABAADjEUQAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEQAAMB5BBAAAjEcQAQAA4xFEAADAeAQRAAAwHkEEAACMRxABAADjEUQAAMB4BBEAADCepUGUkpKihx56SIGBgQoLC9OIESN0/PhxpzVXrlxRYmKiWrRooZ/97GcaNWqUCgoKnNbk5OQoPj5eTZo0UVhYmKZPn66rV686rfnss8/Uq1cv+fv7q3379kpLS6vtwwMAAF7C0iDasWOHEhMTtXfvXqWnp6u8vFxDhgxRSUmJY820adP017/+VZs2bdKOHTuUm5urkSNHOvZXVFQoPj5eZWVl2rNnj1atWqW0tDTNmjXLseb06dOKj4/XoEGDlJ2dralTp+qXv/yltm7dWqfHCwAAPJTdgxQWFtol2Xfs2GG32+32S5cu2Rs1amTftGmTY81XX31ll2TPzMy02+12+8cff2xv0KCBPT8/37Fm2bJl9qCgIHtpaandbrfbZ8yYYe/cubPTYz355JP2uLi4u5qrqKjILsleVFRUo+PzdCkHznn0/dWEp8ziKXMAgAmq8/ztUdcQFRUVSZJCQkIkSVlZWSovL1dsbKxjTceOHXXvvfcqMzNTkpSZmamuXbsqPDzcsSYuLk42m03Hjh1zrLn2PqrWVN3H9UpLS2Wz2Zw2AABQf3lMEFVWVmrq1Knq27evunTpIknKz8+Xn5+fmjVr5rQ2PDxc+fn5jjXXxlDV/qp9t1tjs9n0z3/+84ZZUlJSFBwc7NiioqLccowAAMAzeUwQJSYm6ujRo1q/fr3Voyg5OVlFRUWO7cyZM1aPBAAAalFDqweQpMmTJ2vz5s3auXOnWrVq5bg9IiJCZWVlunTpktNZooKCAkVERDjW7Nu3z+n+qt6Fdu2a69+ZVlBQoKCgIAUEBNwwj7+/v/z9/d1ybAAAwPNZeobIbrdr8uTJev/997Vt2za1bdvWaX/v3r3VqFEjZWRkOG47fvy4cnJyFBMTI0mKiYnRkSNHVFhY6FiTnp6uoKAgderUybHm2vuoWlN1HwAAwGyWniFKTEzUunXr9Je//EWBgYGOa36Cg4MVEBCg4OBgJSQkKCkpSSEhIQoKCtILL7ygmJgY/fznP5ckDRkyRJ06ddLTTz+tBQsWKD8/X6+88ooSExMdZ3mef/55LVmyRDNmzNCzzz6rbdu2aePGjfroo48sO3YAAOA5LD1DtGzZMhUVFWngwIFq2bKlY9uwYYNjze9//3s99thjGjVqlAYMGKCIiAi99957jv2+vr7avHmzfH19FRMTo3Hjxmn8+PF67bXXHGvatm2rjz76SOnp6erevbsWLVqkP/7xj4qLi6vT4wUAAJ7J0jNEdrv9jmsaN26spUuXaunSpbdc07p1a3388ce3vZ+BAwfq4MGD1Z4RAADUfx7zLjMAAACrEEQAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEQAAMB5BBAAAjEcQAQAA4xFEAADAeAQRAAAwHkEEAACMRxABAADjEUQAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEQAAMB5BBAAAjEcQAQAA4xFEAADAeAQRAAAwHkEEjzPv4HmrRwAAGIYgAgAAxiOIAACA8QgiAABgPIIIAAAYjyACvBwXoQNAzRFEAADAeAQRAAAwHkEEAACMRxABAADjEUQAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEQAAMB5BBAAAjEcQAQAA4xFEAADAeAQRAAAwHkEEAACMRxABAADjEUQAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEeDB5h08b/UIAGAEgggAABiPIAIAAMYjiACD8ZIcAPyEIAIAAMYjiAAAgPEIIgAAYDyCCAAAGM+lIPrmm2/cPQcAAIBlXAqi9u3ba9CgQVqzZo2uXLni7pkAAADqlEtBdODAAXXr1k1JSUmKiIjQf/zHf2jfvn3Vvp+dO3dq+PDhioyMlI+Pjz744AOn/c8884x8fHyctqFDhzqtuXDhgsaOHaugoCA1a9ZMCQkJKi4udlpz+PBh9e/fX40bN1ZUVJQWLFhQ7VkBAED95VIQ9ejRQ2+88YZyc3O1YsUK5eXlqV+/furSpYtSU1N17ty5u7qfkpISde/eXUuXLr3lmqFDhyovL8+x/elPf3LaP3bsWB07dkzp6enavHmzdu7cqeeee86x32azaciQIWrdurWysrK0cOFCvfrqq3rnnXdcOXQAAFAP1eii6oYNG2rkyJHatGmT5s+fr6+//lovv/yyoqKiNH78eOXl5d32+4cNG6a5c+fqiSeeuOUaf39/RUREOLbmzZs79n311VfasmWL/vjHPyo6Olr9+vXTW2+9pfXr1ys3N1eStHbtWpWVlWnFihXq3LmzRo8erRdffFGpqak1OXQAAFCP1CiI9u/fr//8z/9Uy5YtlZqaqpdfflmnTp1Senq6cnNz9fjjj9d4wM8++0xhYWF64IEH9Ktf/Uo//PCDY19mZqaaNWumPn36OG6LjY1VgwYN9MUXXzjWDBgwQH5+fo41cXFxOn78uC5evHjTxywtLZXNZnPaAABA/eVSEKWmpqpr16565JFHlJubq9WrV+u7777T3Llz1bZtW/Xv319paWk6cOBAjYYbOnSoVq9erYyMDM2fP187duzQsGHDVFFRIUnKz89XWFiY0/c0bNhQISEhys/Pd6wJDw93WlP1ddWa66WkpCg4ONixRUVF1eg44N1u9vEWfOQFANQvDV35pmXLlunZZ5/VM888o5YtW950TVhYmN59990aDTd69GjH37t27apu3bqpXbt2+uyzzzR48OAa3fftJCcnKykpyfG1zWYjigAAqMdcCqKTJ0/ecY2fn58mTJjgyt3f0n333afQ0FB9/fXXGjx4sCIiIlRYWOi05urVq7pw4YIiIiIkSRERESooKHBaU/V11Zrr+fv7y9/f362zAwAAz+XSS2YrV67Upk2bbrh906ZNWrVqVY2HupWzZ8/qhx9+cJyViomJ0aVLl5SVleVYs23bNlVWVio6OtqxZufOnSovL3esSU9P1wMPPOB0gTYAADCXS0GUkpKi0NDQG24PCwvT66+/ftf3U1xcrOzsbGVnZ0uSTp8+rezsbOXk5Ki4uFjTp0/X3r179e233yojI0OPP/642rdvr7i4OEnSgw8+qKFDh2rSpEnat2+fPv/8c02ePFmjR49WZGSkJGnMmDHy8/NTQkKCjh07pg0bNuiNN95wekkMAACYzaUgysnJUdu2bW+4vXXr1srJybnr+9m/f7969uypnj17SpKSkpLUs2dPzZo1S76+vjp8+LD+9V//VR06dFBCQoJ69+6tXbt2Ob2ctXbtWnXs2FGDBw/Wo48+qn79+jn9jqHg4GB9+umnOn36tHr37q2XXnpJs2bNcvpdRQAAwGwuXUMUFhamw4cPq02bNk63Hzp0SC1atLjr+xk4cKDsdvst92/duvWO9xESEqJ169bddk23bt20a9euu54LAACYxaUzRE899ZRefPFFbd++XRUVFaqoqNC2bds0ZcoUp3eGAQAAeAOXzhDNmTNH3377rQYPHqyGDX+6i8rKSo0fP75a1xABAAB4ApeCyM/PTxs2bNCcOXN06NAhBQQEqGvXrmrdurW75wMAAKh1LgVRlQ4dOqhDhw7umgUAAMASLgVRRUWF0tLSlJGRocLCQlVWVjrt37Ztm1uGAwAAqAsuBdGUKVOUlpam+Ph4denSRT4+Pu6eCwAAoM64FETr16/Xxo0b9eijj7p7HgAAgDrn0tvu/fz81L59e3fPAgAAYAmXguill17SG2+8cdtfqggAAOAtXHrJbPfu3dq+fbs++eQTde7cWY0aNXLa/95777llOAA1M+/gec3seePnDgIAnLkURM2aNdMTTzzh7lkAAAAs4VIQrVy50t1zAAAAWMala4gk6erVq/rb3/6mP/zhD7p8+bIkKTc3V8XFxW4bDgAAoC64dIbou+++09ChQ5WTk6PS0lL9y7/8iwIDAzV//nyVlpZq+fLl7p4TAACg1rh0hmjKlCnq06ePLl68qICAAMftTzzxhDIyMtw2HAAAQF1w6QzRrl27tGfPHvn5+Tnd3qZNG33//fduGQwAAKCuuHSGqLKyUhUVFTfcfvbsWQUGBtZ4KAAAgLrkUhANGTJEixcvdnzt4+Oj4uJizZ49m4/zAAAAXsell8wWLVqkuLg4derUSVeuXNGYMWN08uRJhYaG6k9/+pO7ZwQAAKhVLgVRq1atdOjQIa1fv16HDx9WcXGxEhISNHbsWKeLrAEAALyBS0EkSQ0bNtS4cePcOQsAAIAlXAqi1atX33b/+PHjXRoGAADACi4F0ZQpU5y+Li8v148//ig/Pz81adKEIAIAAF7FpXeZXbx40WkrLi7W8ePH1a9fPy6qBgAAXsflzzK73v3336958+bdcPYIAADA07ktiKSfLrTOzc11510CAADUOpeuIfrwww+dvrbb7crLy9OSJUvUt29ftwwGAABQV1wKohEjRjh97ePjo3vuuUe/+MUvtGjRInfMBQAAUGdcCqLKykp3zwEAAGAZt15DBAAA4I1cOkOUlJR012tTU1NdeQgAFpl38Lxm9gy1egwAqFMuBdHBgwd18OBBlZeX64EHHpAknThxQr6+vurVq5djnY+Pj3umBGApIglAfedSEA0fPlyBgYFatWqVmjdvLumnX9Y4ceJE9e/fXy+99JJbhwQAAKhNLl1DtGjRIqWkpDhiSJKaN2+uuXPn8i4zAADgdVwKIpvNpnPnzt1w+7lz53T58uUaDwUAAFCXXAqiJ554QhMnTtR7772ns2fP6uzZs/rzn/+shIQEjRw50t0zAgAA1CqXriFavny5Xn75ZY0ZM0bl5eU/3VHDhkpISNDChQvdOiAAAEBtcymImjRporffflsLFy7UqVOnJEnt2rVT06ZN3TocAABAXajRL2bMy8tTXl6e7r//fjVt2lR2u91dcwEAANQZl4Lohx9+0ODBg9WhQwc9+uijysvLkyQlJCTwlnsAAOB1XAqiadOmqVGjRsrJyVGTJk0ctz/55JPasmWL24YDAACoCy5dQ/Tpp59q69atatWqldPt999/v7777ju3DAYAAFBXXDpDVFJS4nRmqMqFCxfk7+9f46EAAADqkktB1L9/f61evdrxtY+PjyorK7VgwQINGjTIbcMBJpp38LzVIwCAcVx6yWzBggUaPHiw9u/fr7KyMs2YMUPHjh3ThQsX9Pnnn7t7RgAAgFrl0hmiLl266MSJE+rXr58ef/xxlZSUaOTIkTp48KDatWvn7hkBiDNHAFCbqn2GqLy8XEOHDtXy5cv13//937Uxk3HmHTyvmT1DrR4DAABjVfsMUaNGjXT48OHamAUAAMASLr1kNm7cOL377rvungUAAMASLl1UffXqVa1YsUJ/+9vf1Lt37xs+wyw1NdUtwwEAANSFagXRN998ozZt2ujo0aPq1auXJOnEiRNOa3x8fNw3HXAXuAYLAFBT1Qqi+++/X3l5edq+fbuknz6q480331R4eHitDAfAdbwrDQDuXrWuIbr+0+w/+eQTlZSUuHUgwFsRIADgvVy6qLrK9YEEAADgjaoVRD4+PjdcI8Q1QwAAwNtV6xoiu92uZ555xvEBrleuXNHzzz9/w7vM3nvvPfdNCAAAUMuqFUQTJkxw+nrcuHFuHQYAAMAK1QqilStX1tYcAAAAlqnRRdUAAAD1gaVBtHPnTg0fPlyRkZHy8fHRBx984LTfbrdr1qxZatmypQICAhQbG6uTJ086rblw4YLGjh2roKAgNWvWTAkJCSouLnZac/jwYfXv31+NGzdWVFSUFixYUNuHBgAAvIilQVRSUqLu3btr6dKlN92/YMECvfnmm1q+fLm++OILNW3aVHFxcbpy5YpjzdixY3Xs2DGlp6dr8+bN2rlzp5577jnHfpvNpiFDhqh169bKysrSwoUL9eqrr+qdd96p9eMDAADewaXPMnOXYcOGadiwYTfdZ7fbtXjxYr3yyit6/PHHJUmrV69WeHi4PvjgA40ePVpfffWVtmzZoi+//FJ9+vSRJL311lt69NFH9bvf/U6RkZFau3atysrKtGLFCvn5+alz587Kzs5WamqqUzgBAABzeew1RKdPn1Z+fr5iY2MdtwUHBys6OlqZmZmSpMzMTDVr1swRQ5IUGxurBg0a6IsvvnCsGTBggPz8/Bxr4uLidPz4cV28ePGmj11aWiqbzea0AQCA+stjgyg/P1+SbvictPDwcMe+/Px8hYWFOe1v2LChQkJCnNbc7D6ufYzrpaSkKDg42LFFRUXV/IAAAIDH8tggslJycrKKiooc25kzZ6weCbgrfJ4aALjGY4MoIiJCklRQUOB0e0FBgWNfRESECgsLnfZfvXpVFy5ccFpzs/u49jGu5+/vr6CgIKcNAADUXx4bRG3btlVERIQyMjIct9lsNn3xxReKiYmRJMXExOjSpUvKyspyrNm2bZsqKysVHR3tWLNz506Vl5c71qSnp+uBBx5Q8+bN6+hoAOu5++wRZ6MA1CeWBlFxcbGys7OVnZ0t6acLqbOzs5WTkyMfHx9NnTpVc+fO1YcffqgjR45o/PjxioyM1IgRIyRJDz74oIYOHapJkyZp3759+vzzzzV58mSNHj1akZGRkqQxY8bIz89PCQkJOnbsmDZs2KA33nhDSUlJFh01AADwNJa+7X7//v0aNGiQ4+uqSJkwYYLS0tI0Y8YMlZSU6LnnntOlS5fUr18/bdmyRY0bN3Z8z9q1azV58mQNHjxYDRo00KhRo/Tmm2869gcHB+vTTz9VYmKievfurdDQUM2aNYu33AMAAAdLg2jgwIGy2+233O/j46PXXntNr7322i3XhISEaN26dbd9nG7dumnXrl0uzwnAs8w7eF4ze4ZaPQaAesRjryECUP9w3REAT0UQAQAA4xFEAADAeAQRAAAwHkEEAACMRxABAADjEUQAAMB4BBEASbwlHoDZCCIAtYbIAuAtCCIAAGA8gghAtXHmB0B9QxABAADjEUQAAMB4BBEAADAeQQRYjOtxAMB6BBEAADAeQQQAAIxHEAEAAOMRRIBhuGYJAG5EEAG4KcIJgEkIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAPUSF4UDqA6CCDCcJ4SDJ8wAwGwEEQAAMB5BBAAAjEcQAQAA4xFEAADAeAQRgNvylguevWVOAJ6JIILxeCIFABBEAO4a8QigviKIAACA8QgiADVy/VkjziIB8EYEEQAAMB5BBKBWccYIgDcgiABYglAC4EkIIqAW8aQPAN6BIAIAAMYjiAAAgPEIIgBuce3Lg7xUCMDbEEQAAMB4BBEAADAeQQQAAIxHEAGoU9W5vohrkQDUFYIIAAAYjyACANQJzvjBkxFEAIzDEzOA6xFEAADAeAQRAAAwHkEEwOO48yUtXh4DcDcIIgAAYDyCCAAAGI8gAmAMXj4DcCsEEQBjEUgAqhBEAGA4whAgiADUgVs94fJEDMBTEEQAAMB4BBEAj8EZIwBW8eggevXVV+Xj4+O0dezY0bH/ypUrSkxMVIsWLfSzn/1Mo0aNUkFBgdN95OTkKD4+Xk2aNFFYWJimT5+uq1ev1vWhAAAAD+bRQSRJnTt3Vl5enmPbvXu3Y9+0adP017/+VZs2bdKOHTuUm5urkSNHOvZXVFQoPj5eZWVl2rNnj1atWqW0tDTNmjXLikMB4CU4UwWYx+ODqGHDhoqIiHBsoaGhkqSioiK9++67Sk1N1S9+8Qv17t1bK1eu1J49e7R3715J0qeffqq///3vWrNmjXr06KFhw4Zpzpw5Wrp0qcrKyqw8LADVQKAAqG0eH0QnT55UZGSk7rvvPo0dO1Y5OTmSpKysLJWXlys2NtaxtmPHjrr33nuVmZkpScrMzFTXrl0VHh7uWBMXFyebzaZjx47d8jFLS0tls9mcNgDWIooA1CaPDqLo6GilpaVpy5YtWrZsmU6fPq3+/fvr8uXLys/Pl5+fn5o1a+b0PeHh4crPz5ck5efnO8VQ1f6qfbeSkpKi4OBgxxYVFeXeAwMAAB6lodUD3M6wYcMcf+/WrZuio6PVunVrbdy4UQEBAbX2uMnJyUpKSnJ8bbPZiCIAAOoxjz5DdL1mzZqpQ4cO+vrrrxUREaGysjJdunTJaU1BQYEiIiIkSRERETe866zq66o1N+Pv76+goCCnDQAA1F9eFUTFxcU6deqUWrZsqd69e6tRo0bKyMhw7D9+/LhycnIUExMjSYqJidGRI0dUWFjoWJOenq6goCB16tSpzucHUL9wXRNQf3j0S2Yvv/yyhg8frtatWys3N1ezZ8+Wr6+vnnrqKQUHByshIUFJSUkKCQlRUFCQXnjhBcXExOjnP/+5JGnIkCHq1KmTnn76aS1YsED5+fl65ZVXlJiYKH9/f4uPDoBEVADwDB4dRGfPntVTTz2lH374Qffcc4/69eunvXv36p577pEk/f73v1eDBg00atQolZaWKi4uTm+//bbj+319fbV582b96le/UkxMjJo2baoJEybotddes+qQAHigeQfPa2bPUKvHAGAhjw6i9evX33Z/48aNtXTpUi1duvSWa1q3bq2PP/7Y3aMBqCOcQQJQF7zqGiIAAIDaQBAB8Bp1cbbItDNSph0vcCsEEQCP4GlPzJ42D4DaRRABAADjEUQAPFJ9O0NT344HqG8IIgBe6drAuFVs3E2EECoAJIIIACTVbhgRXYDnI4gA1HsEyZ3xbwTTEUQAvMr1T9x19UQ+7+D5Gj+W1dFh9eMDnowgAgAPYXWwWP34gJUIIgD1hjvO4tzNY7hjTW3PAKB6CCIAXqsuXy6z4nsB1B2CCAAAGI8gAoDbqK0zPFX3yxkkwDMQRACAWkf4wdMRRADqnbp48vXEJ3jOOgGuI4gAoJaYGmaANyKIAKCaavLZadVZVxvq4lcTAN6IIAIAD0CkANZqaPUAAFAfuHJ2yMqPAiHAAGecIQIAD3W7aKnOb8wmfoA7I4gAGIU4AHAzBBEAWIx3owHWI4gAoAauDw0rwoPYAWqOIAKAGvLEIPHEmQBPRhABgIdz5zvTANwcQQTACHUdEu5+S7y3vBR3p+8h6OCpCCIARjLlidmU4wRqiiACAA/kasgQQIBrCCIAAGA8gggA/j9PeAs9AGsQRABQD7gz3upjCNbHY4J7EUQA4CW85UndW+YErkUQAQDcghCCNyOIAMCDeUJk1HQGTzgG4E4IIgDwIJ4WD7z9H6YgiAAA1VKd2CGM4C0IIgBArSCG4E0IIgCAQ3U/i8yboqdq1nkHz3vV3KgbBBEAADAeQQQAuMHNzqB489kh4E4IIgDAHVX3pTRPcu1snjwnrEUQAQBqhMhAfUAQAQBQx4hIz0MQAQDqnCcEgSfMAM9BEAEAAOMRRAAAS3CxMzwJQQQAqLaaBAzxA09EEAEALGXamSITjtEbEUQAAI9gRSgQJ6hCEAEALONKkBAxqA0EEQDAo137oaxAbSGIAAAe5WbXFN0qhtwRS4QWJIIIAOChbvcBs3e6ELu6kVNbUURseQ+CCADgcWpybRERAlcQRAAAr+SOM0Om49/r/xBEAIB6iSf7ujHv4Pl68W9NEAEA6q368ESNukEQAQAg98dTfX9Jr76cGapiVBAtXbpUbdq0UePGjRUdHa19+/ZZPRIAwANd/0Tvjnet1fQ+PZ23H48xQbRhwwYlJSVp9uzZOnDggLp37664uDgVFhZaPRoAwINc/261a/+805P+rULI22PhevXteCSDgig1NVWTJk3SxIkT1alTJy1fvlxNmjTRihUrrB4NAOAh7uYszq2CyR2P58mqws6bZq6OhlYPUBfKysqUlZWl5ORkx20NGjRQbGysMjMzb1hfWlqq0tJSx9dFRUWSJJvNVivzXSm+LJvNr1bu28o5XL2/6n7f3ay/3Zo7ff/N9rt6W3XX3Orvt/r+6/8u6YZ9t1pz/f5r/7zZmtt937X7qtxu37Vutw/wFK/uunzTP6//e3XuS5KSureQJKUe+sHxd1dc+/2ph35w2nft/d7pf/+q7uf6+7iVW91XTY/HVVXP23a7/c6L7Qb4/vvv7ZLse/bscbp9+vTp9ocffviG9bNnz7ZLYmNjY2NjY6sH25kzZ+7YCkacIaqu5ORkJSUlOb6urKzUhQsX1KJFC/n4+Lj1sWw2m6KionTmzBkFBQW59b5Rffw8PAs/D8/Cz8Oz8PO4M7vdrsuXLysyMvKOa40IotDQUPn6+qqgoMDp9oKCAkVERNyw3t/fX/7+/k63NWvWrDZHVFBQEP+B9iD8PDwLPw/Pws/Ds/DzuL3g4OC7WmfERdV+fn7q3bu3MjIyHLdVVlYqIyNDMTExFk4GAAA8gRFniCQpKSlJEyZMUJ8+ffTwww9r8eLFKikp0cSJE60eDQAAWMyYIHryySd17tw5zZo1S/n5+erRo4e2bNmi8PBwS+fy9/fX7Nmzb3iJDtbg5+FZ+Hl4Fn4enoWfh3v52O138140AACA+suIa4gAAABuhyACAADGI4gAAIDxCCIAAGA8gshCS5cuVZs2bdS4cWNFR0dr3759Vo9krJSUFD300EMKDAxUWFiYRowYoePHj1s9FiTNmzdPPj4+mjp1qtWjGO3777/XuHHj1KJFCwUEBKhr167av3+/1WMZqaKiQr/5zW/Utm1bBQQEqF27dpozZ87dfV4XbokgssiGDRuUlJSk2bNn68CBA+revbvi4uJUWFho9WhG2rFjhxITE7V3716lp6ervLxcQ4YMUUlJidWjGe3LL7/UH/7wB3Xr1s3qUYx28eJF9e3bV40aNdInn3yiv//971q0aJGaN29u9WhGmj9/vpYtW6YlS5boq6++0vz587VgwQK99dZbVo/m1XjbvUWio6P10EMPacmSJZJ++s3ZUVFReuGFFzRz5kyLp8O5c+cUFhamHTt2aMCAAVaPY6Ti4mL16tVLb7/9tubOnasePXpo8eLFVo9lpJkzZ+rzzz/Xrl27rB4Fkh577DGFh4fr3Xffddw2atQoBQQEaM2aNRZO5t04Q2SBsrIyZWVlKTY21nFbgwYNFBsbq8zMTAsnQ5WioiJJUkhIiMWTmCsxMVHx8fFO/z2BNT788EP16dNH//Zv/6awsDD17NlT//M//2P1WMZ65JFHlJGRoRMnTkiSDh06pN27d2vYsGEWT+bdjPlN1Z7k/PnzqqiouOG3ZIeHh+sf//iHRVOhSmVlpaZOnaq+ffuqS5cuVo9jpPXr1+vAgQP68ssvrR4Fkr755hstW7ZMSUlJ+q//+i99+eWXevHFF+Xn56cJEyZYPZ5xZs6cKZvNpo4dO8rX11cVFRX67W9/q7Fjx1o9mlcjiIDrJCYm6ujRo9q9e7fVoxjpzJkzmjJlitLT09W4cWOrx4F++j8Jffr00euvvy5J6tmzp44eParly5cTRBbYuHGj1q5dq3Xr1qlz587Kzs7W1KlTFRkZyc+jBggiC4SGhsrX11cFBQVOtxcUFCgiIsKiqSBJkydP1ubNm7Vz5061atXK6nGMlJWVpcLCQvXq1ctxW0VFhXbu3KklS5aotLRUvr6+Fk5onpYtW6pTp05Otz344IP685//bNFEZps+fbpmzpyp0aNHS5K6du2q7777TikpKQRRDXANkQX8/PzUu3dvZWRkOG6rrKxURkaGYmJiLJzMXHa7XZMnT9b777+vbdu2qW3btlaPZKzBgwfryJEjys7Odmx9+vTR2LFjlZ2dTQxZoG/fvjf8GooTJ06odevWFk1kth9//FENGjg/ffv6+qqystKiieoHzhBZJCkpSRMmTFCfPn308MMPa/HixSopKdHEiROtHs1IiYmJWrdunf7yl78oMDBQ+fn5kqTg4GAFBARYPJ1ZAgMDb7h2q2nTpmrRogXXdFlk2rRpeuSRR/T666/r3//937Vv3z698847euedd6wezUjDhw/Xb3/7W917773q3LmzDh48qNTUVD377LNWj+bVeNu9hZYsWaKFCxcqPz9fPXr00Jtvvqno6GirxzKSj4/PTW9fuXKlnnnmmbodBjcYOHAgb7u32ObNm5WcnKyTJ0+qbdu2SkpK0qRJk6wey0iXL1/Wb37zG73//vsqLCxUZGSknnrqKc2aNUt+fn5Wj+e1CCIAAGA8riECAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAY7/8B1PwL9KQrmwMAAAAASUVORK5CYII=","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":35},{"id":"7c6665af","cell_type":"code","source":"print(f'Missing ratio of profileId in train: {train_df.profileId.isnull().mean():.2%}')\nprint(f'Missing ratio of profileId in test: {test_df.profileId.isnull().mean():.2%}')\nprint('Unique profileIds in train:', train_df.profileId.nunique())\nprint('Unique profileIds in test:', test_df.profileId.nunique())\nprint('Intersection of profileIds:', len(set(train_df.profileId) & set(test_df.profileId)))","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of profileId in train: 0.00%\n","Missing ratio of profileId in test: 0.00%\n","Unique profileIds in train: 32922\n","Unique profileIds in test: 18981\n","Intersection of profileIds: 10700\n"]}],"execution_count":58},{"id":"8ece1993","cell_type":"markdown","source":"There are shared users in training set and test set which means that we can make use of the profileIds.","metadata":{}},{"id":"7d55a1ba","cell_type":"code","source":"col = 'companyID'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')\nprint('Unique companyIds in train:', train_df.companyID.nunique())\nprint('Unique companyIds in test:', test_df.companyID.nunique())\nprint('Intersection of companyIds:', len(set(train_df.companyID) & set(test_df.companyID)))","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of companyID in train: 0.00%\n","Missing ratio of companyID in test: 0.00%\n","Unique companyIds in train: 641\n","Unique companyIds in test: 495\n","Intersection of companyIds: 454\n"]}],"execution_count":57},{"id":"27bf238e","cell_type":"markdown","source":"Same with profileIDs, we can also use companyIDs as a feature.","metadata":{}},{"id":"00d4f27b","cell_type":"markdown","source":"### User Information\n- sex - User gender\n- nationality - User nationality/citizenship\n- frequentFlyer - Frequent flyer program status\n- isVip - VIP status indicator\n- bySelf - Whether user books flights independently\n- isAccess3D - Binary marker for internal feature","metadata":{}},{"id":"c9ec4666","cell_type":"code","source":"col = 'sex'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of sex in train: 0.00%\n","Missing ratio of sex in test: 0.00%\n"]}],"execution_count":50},{"id":"35bae485","cell_type":"code","source":"plt.figure(figsize=(10,4))\n\n# Create subplots in a 1x2 grid\nax1 = plt.subplot(1, 2, 1)\ntrain_df.sex.value_counts().plot(kind='barh', color='skyblue', ax=ax1)\nax1.set_title('Distribution of sex (Train)')\n\nax2 = plt.subplot(1, 2, 2)\ntest_df.sex.value_counts().plot(kind='barh', color='lightgreen', ax=ax2)\nax2.set_title('Distribution of sex (Test)')\n\nplt.tight_layout()\nplt.show()","metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1000x400 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":22},{"id":"fbfc24e8","cell_type":"code","source":"col = 'nationality'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')\nprint('Unique nationalities in train:', train_df.nationality.nunique())\nprint('Unique nationalities in test:', test_df.nationality.nunique())\nprint('Intersection of nationalities:', len(set(train_df.nationality) & set(test_df.nationality)))","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of nationality in train: 0.00%\n","Missing ratio of nationality in test: 0.00%\n","Unique nationalities in train: 48\n","Unique nationalities in test: 34\n","Intersection of nationalities: 33\n"]}],"execution_count":56},{"id":"27eee4d0","cell_type":"code","source":"plt.figure(figsize=(10,4))\n\n# Create subplots in a 1x2 grid\nax1 = plt.subplot(1, 2, 1)\ntrain_df.nationality.value_counts().plot(kind='bar', color='skyblue', ax=ax1)\nax1.set_title('Distribution of nationality (Train)')\n\nax2 = plt.subplot(1, 2, 2)\ntest_df.nationality.value_counts().plot(kind='bar', color='lightgreen', ax=ax2)\nax2.set_title('Distribution of nationality (Test)')\n\nplt.tight_layout()\nplt.show()","metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1000x400 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":25},{"id":"71439fac","cell_type":"markdown","source":"It seems that this an domestic airlines company from. According to the sponsor's information on Kaggle we can infer that the majority of the passengers are from Khazakstan.","metadata":{}},{"id":"6d381e3f","cell_type":"code","source":"col = 'frequentFlyer'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')\nprint(f'Unique {col} in train:', train_df[col].nunique())\nprint(f'Unique {col} in test:', test_df[col].nunique())\nprint(f'Intersection of {col}:', len(set(train_df[col]) & set(test_df[col])))","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of frequentFlyer in train: 66.20%\n","Missing ratio of frequentFlyer in test: 57.63%\n","Unique frequentFlyer in train: 371\n","Unique frequentFlyer in test: 324\n","Intersection of frequentFlyer: 267\n"]}],"execution_count":55},{"id":"69fcc1df","cell_type":"code","source":"train_df.frequentFlyer.value_counts()[:10]","metadata":{},"outputs":[{"data":{"text/plain":["frequentFlyer\n","SU          3774329\n","SU/S7        817344\n","S7/SU        284528\n","S7           188968\n","SU/TK        112820\n","SU/S7/UT      88032\n","SU/S7/U6      56794\n","SU/UT         50948\n","SU/U6         36299\n","S7/SU/U6      34809\n","Name: count, dtype: int64"]},"execution_count":33,"metadata":{},"output_type":"execute_result"}],"execution_count":33},{"id":"cf2ee35b","cell_type":"code","source":"col = 'isVip'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of isVip in train: 0.00%\n","Missing ratio of isVip in test: 0.00%\n"]}],"execution_count":60},{"id":"e8e8e74a","cell_type":"code","source":"plt.figure(figsize=(10,4))\n\n# Create subplots in a 1x2 grid\nax1 = plt.subplot(1, 2, 1)\ntrain_df.isVip.value_counts().plot(kind='barh', color='skyblue', ax=ax1)\nax1.set_title('Distribution of isVip (Train)')\n\nax2 = plt.subplot(1, 2, 2)\ntest_df.isVip.value_counts().plot(kind='barh', color='lightgreen', ax=ax2)\nax2.set_title('Distribution of isVip (Test)')\n\nplt.tight_layout()\nplt.show()","metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1000x400 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":3},{"id":"bb97ab4c","cell_type":"code","source":"col = 'bySelf'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of bySelf in train: 0.00%\n","Missing ratio of bySelf in test: 0.00%\n"]}],"execution_count":61},{"id":"7435c2e7","cell_type":"code","source":"plt.figure(figsize=(10,4))\n\n# Create subplots in a 1x2 grid\nax1 = plt.subplot(1, 2, 1)\ntrain_df.bySelf.value_counts().plot(kind='barh', color='skyblue', ax=ax1)\nax1.set_title('Distribution of bySelf (Train)')\n\nax2 = plt.subplot(1, 2, 2)\ntest_df.bySelf.value_counts().plot(kind='barh', color='lightgreen', ax=ax2)\nax2.set_title('Distribution of bySelf (Test)')\n\nplt.tight_layout()\nplt.show()","metadata":{},"outputs":[{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA90AAAGGCAYAAABmGOKbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8ekN5oAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA96ElEQVR4nO3deXiM5/7H8c8QmSCLaGKJRuxaO2mLqloaW1XpdUopRVunjtJajiptNZa24VQVPUoXtdfag272tVR7UHtLbQ0OSrUSsQTJ/fvDlfkZ2WZiHjOJ9+u65mKeueeZ7z33TL75ZOaZsRljjAAAAAAAgMfl83YBAAAAAADkVYRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG7kSsOGDZPNZrstt9W4cWM1btzYcX7dunWy2WxauHDhbbn97t27q0yZMrfltnIqKSlJPXr0UIkSJWSz2dSvX79Mx9psNvXp0+f2FZcDN6+5JP3+++968sknddddd8lms2ncuHFZ7uPYsWMKCAjQpk2brCs0A2XKlFH37t1zdN169epp0KBBni0IADJBL/ct9PL0vNXLs0O/zn0I3fC6adOmyWazOU4BAQGKiIhQixYtNGHCBJ0/f94jt3PixAkNGzZMO3bs8Mj+PMmXa3PFO++8o2nTpqlXr16aOXOmnnnmmdt6+xs3blSrVq1UqlQpBQQEqHTp0mrTpo0+//xzj91G//79tXz5cg0ZMkQzZ85Uy5Ytsxw/YsQI1a1bVw0aNHD8cufKyZteffVVTZw4UadOnfJqHQByH3q5b9fmCnp5et7s5T///LOGDRum3377Ld1l9Ovcx8/bBQBpRowYobJly+rq1as6deqU1q1bp379+mns2LH68ssvVaNGDcfYN954Q4MHD3Zr/ydOnNDw4cNVpkwZ1apVy+XrrVixwq3byYmsavvkk0+UmppqeQ23Ys2aNapXr55iY2Nv+20vWLBATz31lGrVqqW+ffsqNDRUR44c0YYNG/TJJ5/o6aef9sjtrFmzRm3bttXAgQOzHXvmzBlNnz5d06dPlyTde++9mjlzptOYIUOGKDAwUK+//rpH6kuzf/9+5cuXs7+ntm3bVsHBwfrwww81YsQIj9YF4M5AL6eX5wS9PL2ff/5Zw4cPV+PGjdO9S4J+nfsQuuEzWrVqpfvuu89xfsiQIVqzZo0ee+wxPf744/rll19UsGBBSZKfn5/8/Kx9+F68eFGFChWSv7+/pbeTnQIFCnj19l1x+vRpValSxSu3PWzYMFWpUkU//PBDurU6ffq0x27n9OnTKlKkiEtjZ82aJT8/P7Vp00aSVLx4cXXp0sVpzKhRoxQWFpZu+41SU1N15coVBQQEuFyn3W53eezN8uXLpyeffFIzZszQ8OHDvf7KO4Dch16eMXp51vJyL7cC/Tr34e3l8GlNmzbV0KFDFR8fr1mzZjm2Z3Qc2MqVK/XQQw+pSJEiCgwMVOXKlfXaa69Jun7s1v333y9JevbZZx1v/5k2bZqk68f9VKtWTdu2bdPDDz+sQoUKOa6b0TFBkpSSkqLXXntNJUqUUOHChfX444/r2LFjTmMyO772xn1mV1tGx4FduHBB//znPxUZGSm73a7KlStrzJgxMsY4jUs75mrx4sWqVq2a7Ha7qlatqmXLlmV8h9/k9OnTev7551W8eHEFBASoZs2ajr/4ptVus9l05MgRffPNN47aM3or1M1mz56typUrKyAgQNHR0dqwYYPjsrVr18pms2nRokXprvf555/LZrNp8+bNkqRDhw7p/vvvz/AXqmLFijmdT01N1bhx41S1alUFBASoePHi6tmzp/76669M60x7y6QxRhMnTnTprWOLFy9W3bp1FRgYmOW4m6Wt1+zZs1W1alXZ7XbHWo0ZM0YPPvig7rrrLhUsWFDR0dEZHot482Murf5NmzZpwIABCg8PV+HChfXEE0/ozJkz6a7frFkzxcfH59q3RwLwPfRyevnN8nIvP3funPr16+dY1woVKmj06NHp3ukwd+5cRUdHKygoSMHBwapevbrGjx/vqLd9+/aSpCZNmjjqXbduneP69OvchdANn5d2TFFWbw3bu3evHnvsMSUnJ2vEiBF677339Pjjjzs++OLee+91vP3mhRde0MyZMzVz5kw9/PDDjn2cPXtWrVq1Uq1atTRu3Dg1adIky7refvttffPNN3r11Vf18ssva+XKlYqJidGlS5fcmp8rtd3IGKPHH39c77//vlq2bKmxY8eqcuXKeuWVVzRgwIB04zdu3KgXX3xRHTt21L/+9S9dvnxZf/vb33T27Nks67p06ZIaN26smTNnqnPnznr33XcVEhKi7t27O5pC2lutwsLCVKtWLUft4eHhWe57/fr16tevn7p06aIRI0bo7Nmzatmypfbs2SPp+i8ykZGRmj17drrrzp49W+XLl1f9+vUlSVFRUVq9erWOHz+e5W1KUs+ePfXKK6+oQYMGGj9+vJ599lnNnj1bLVq00NWrVzO8zsMPP+x4O1mzZs0cc8zM1atXtWXLFtWpUyfbejKyZs0a9e/fX0899ZTGjx/v+CVt/Pjxql27tkaMGKF33nlHfn5+at++vb755huX9vvSSy9p586dio2NVa9evfTVV19l+CE40dHRkuRzHxoDIHejlzujl+fNXn7x4kU1atRIs2bNUteuXTVhwgQ1aNBAQ4YMcVrXlStXqlOnTgoNDdXo0aM1atQoNW7c2PFYf/jhh/Xyyy9Lkl577TVHvffee69jH/TrXMYAXjZ16lQjyWzZsiXTMSEhIaZ27dqO87GxsebGh+/7779vJJkzZ85kuo8tW7YYSWbq1KnpLmvUqJGRZCZPnpzhZY0aNXKcX7t2rZFkSpUqZRITEx3b58+fbySZ8ePHO7ZFRUWZbt26ZbvPrGrr1q2biYqKcpxfvHixkWTeeustp3FPPvmksdls5uDBg45tkoy/v7/Ttp07dxpJ5oMPPkh3WzcaN26ckWRmzZrl2HblyhVTv359ExgY6DT3qKgo07p16yz3d2NNkszWrVsd2+Lj401AQIB54oknHNuGDBli7Ha7OXfunGPb6dOnjZ+fn4mNjXVsmzJlimOeTZo0MUOHDjXfffedSUlJcbrd7777zkgys2fPdtq+bNmydNtvXp+0unv37p3t/A4ePOjS/Vu1atUMbyNfvnxm79696cZfvHjR6fyVK1dMtWrVTNOmTZ223/yYS3t+xcTEmNTUVMf2/v37m/z58zvdv2n8/f1Nr169sqwfAG5EL6eX08uNGTlypClcuLD59ddfncYNHjzY5M+f3xw9etQYY0zfvn1NcHCwuXbtWqb7XrBggZFk1q5dm+kY+nXuwSvdyBUCAwOz/OTTtONzlixZkuMPKrHb7Xr22WddHt+1a1cFBQU5zj/55JMqWbKkvv322xzdvqu+/fZb5c+f3/EX0DT//Oc/ZYzR0qVLnbbHxMSofPnyjvM1atRQcHCwDh8+nO3tlChRQp06dXJsK1CggF5++WUlJSVp/fr1OZ5D/fr1HX+hlaTSpUurbdu2Wr58uVJSUiRdv3+Tk5Od3kI9b948Xbt2zenYqeeee07Lli1T48aNtXHjRo0cOVINGzZUxYoV9f333zvGLViwQCEhIWrWrJn++OMPxyk6OlqBgYFau3Ztjudzo7RXHUJDQ3N0/UaNGmV4TF3aMZCS9NdffykhIUENGzbUTz/95NJ+X3jhBae30jVs2FApKSmKj49PNzY0NFR//PFHDqoHgMzRy/8fvTxv9vIFCxaoYcOGjj6adoqJiVFKSorj7fdFihTRhQsXtHLlyluqk36dexC6kSskJSU5NcWbPfXUU2rQoIF69Oih4sWLq2PHjpo/f75bTbtUqVJufdBKxYoVnc7bbDZVqFDBpWOgbkV8fLwiIiLS3R9pbzm6OUSVLl063T5CQ0OzPPYpbT8VK1ZM90nYmd2OO26+7ySpUqVKunjxouM443vuuUf333+/09vSZs+erXr16qlChQpO123RooWWL1+uc+fOacOGDerdu7fi4+P12GOPOT6A5cCBA0pISFCxYsUUHh7udEpKSvLoB7VISndMnqvKli2b4favv/5a9erVU0BAgIoWLarw8HBNmjRJCQkJLu335sdB2i8SGT0OjDF8KAsAj6OX/z96ed7s5QcOHNCyZcvS1RYTEyPp/z8U7sUXX1SlSpXUqlUr3X333Y4/OuSkPvp17sCnl8PnHT9+XAkJCel+ON+oYMGC2rBhg9auXatvvvlGy5Yt07x589S0aVOtWLFC+fPnz/Z2bnwl0VMy+0GYkpLiUk2ekNnt5DQU3k5du3ZV3759dfz4cSUnJ+uHH37Qv//970zHFypUSA0bNlTDhg0VFham4cOHa+nSperWrZtSU1NVrFixDI8tk5TtsWuuuuuuuyRlHGZdkdHj8LvvvtPjjz+uhx9+WB9++KFKliypAgUKaOrUqS5/f6k7j4Nz584pLCzMvcIBIAv08ltDL88dvTw1NVXNmjXToEGDMry8UqVKkq5/ONyOHTu0fPlyLV26VEuXLtXUqVPVtWtXpw+5yw79OvcgdMPnpX3QRYsWLbIcly9fPj3yyCN65JFHNHbsWL3zzjt6/fXXtXbtWsXExHj8L4EHDhxwOm+M0cGDB52+gzQ0NFTnzp1Ld934+HiVK1fOcd6d2qKiorRq1SqdP3/e6S/k+/btc1zuCVFRUdq1a5dSU1Od/kLuidu5+b6TpF9//VWFChVyapgdO3bUgAEDNGfOHF26dEkFChTQU0895dJtpH1lzcmTJyVJ5cuX16pVq9SgQQNLfilLU7p0aRUsWFBHjhzx2D6/+OILBQQEaPny5U5fCTZ16lSP3Uaa//3vf7py5YrTh7UAwK2ilzujl+fNXl6+fHklJSU5XtnOir+/v9q0aaM2bdooNTVVL774oj766CMNHTpUFSpUyPbxRL/OXXh7OXzamjVrNHLkSJUtW1adO3fOdNyff/6ZblutWrUkScnJyZKkwoULS1KGjTMnZsyY4XRs2sKFC3Xy5Em1atXKsa18+fL64YcfdOXKFce2r7/+Ot3XkbhT26OPPqqUlJR0fyV+//33ZbPZnG7/Vjz66KM6deqU5s2b59h27do1ffDBBwoMDFSjRo1yvO/Nmzc7HYt87NgxLVmyRM2bN3f6a35YWJhatWqlWbNmafbs2WrZsmW6v+iuXr06w9tIOx6vcuXKkqQOHTooJSVFI0eOTDf22rVrHntcFChQQPfdd5+2bt3qkf1J11/hsNlsjmPkJOm3337T4sWLPXYbabZt2yZJevDBBz2+bwB3Jnp5evTyvNnLO3TooM2bN2v58uXpLjt37pyuXbsmSek+dT5fvnyOP/S4+linX+cuvNINn7F06VLt27dP165d0++//641a9Zo5cqVioqK0pdffqmAgIBMrztixAht2LBBrVu3VlRUlE6fPq0PP/xQd999tx566CFJ15tmkSJFNHnyZAUFBalw4cKqW7dupsfQZqdo0aJ66KGH9Oyzz+r333/XuHHjVKFCBf397393jOnRo4cWLlyoli1bqkOHDjp06JBmzZrl9GEo7tbWpk0bNWnSRK+//rp+++031axZUytWrNCSJUvUr1+/dPvOqRdeeEEfffSRunfvrm3btqlMmTJauHChNm3apHHjxmV5XF52qlWrphYtWujll1+W3W7Xhx9+KEkaPnx4urFdu3bVk08+KUkZNtm2bduqbNmyatOmjcqXL68LFy5o1apV+uqrr3T//ferTZs2kq5/QFnPnj0VFxenHTt2qHnz5ipQoIAOHDigBQsWaPz48Y7buVVt27bV66+/rsTERAUHB9/y/lq3bq2xY8eqZcuWevrpp3X69GlNnDhRFSpU0K5duzxQ8f9buXKlSpcurdq1a3t0vwDuDPRyevmd3MtfeeUVffnll3rsscfUvXt3RUdH68KFC9q9e7cWLlyo3377TWFhYerRo4f+/PNPNW3aVHfffbfi4+P1wQcfqFatWo5XrmvVqqX8+fNr9OjRSkhIkN1uV9OmTR3fW06/zmW89KnpgEPa14yknfz9/U2JEiVMs2bNzPjx452+ziLNzV8zsnr1atO2bVsTERFh/P39TUREhOnUqVO6r2xYsmSJqVKlivHz83P6Wo9GjRqZqlWrZlhfZl8zMmfOHDNkyBBTrFgxU7BgQdO6dWsTHx+f7vrvvfeeKVWqlLHb7aZBgwZm69atGX6NRWa13fw1I8YYc/78edO/f38TERFhChQoYCpWrGjeffddp6+EMibzr8bI7OtPbvb777+bZ5991oSFhRl/f39TvXr1DL8Kxd2vGendu7eZNWuWqVixorHb7aZ27dqZfiVGcnKyCQ0NNSEhIebSpUvpLp8zZ47p2LGjKV++vClYsKAJCAgwVapUMa+//nqGj52PP/7YREdHm4IFC5qgoCBTvXp1M2jQIHPixAnHmFv5mhFjrt9vfn5+ZubMmZmOyewrwzK7jSlTpjjur3vuucdMnTo13fPAmMy/Muzmr/FJexzfeL+npKSYkiVLmjfeeMOleQJAGnp51rXRy++cXn7+/HkzZMgQU6FCBePv72/CwsLMgw8+aMaMGWOuXLlijDFm4cKFpnnz5qZYsWLG39/flC5d2vTs2dOcPHnSaV+ffPKJKVeunMmfP79Tz6Zf5z42Y3LBJzAAuGNdu3ZNERERatOmjaZMmeLtclz2/PPP69dff9V3333n7VJctnjxYj399NM6dOiQSpYs6e1yAAB5BL3cs+jXuQ/HdAPwaYsXL9aZM2fUtWtXb5filtjYWG3ZskWbNm3ydikuGz16tPr06UMDBwB4FL3cs+jXuQ+vdAPwST/++KN27dqlkSNHKiwszOnDWgAAgO+jlwPX8Uo3AJ80adIk9erVS8WKFdOMGTO8XQ4AAHATvRy4jle6AQAAAACwCK90AwAAAABgEUI3AAAAAAAW8fN2Ab4mNTVVJ06cUFBQkGw2m7fLAQDcIYwxOn/+vCIiIpQvH38Tdwe9GwDgDa72bkL3TU6cOKHIyEhvlwEAuEMdO3ZMd999t7fLyFXo3QAAb8qudxO6bxIUFCTp+h0XHBzs5WoAAHeKxMRERUZGOvoQXEfvBgB4g6u9m9B9k7S3pQUHB9O4AQC3HW+Pdh+9GwDgTdn1bg4aAwAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALOLn7QIAAAA8YdJfkxSQEuDtMgAgT+gb2tfbJeQZvNINAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAFxis9myPA0bNszbJQIA4HP8vF0AAADIHU6ePOn4/7x58/Tmm29q//79jm2BgYGO/xtjlJKSIj8/ftUAANzZeKUbAAC4pESJEo5TSEiIbDab4/y+ffsUFBSkpUuXKjo6Wna7XRs3blT37t3Vrl07p/3069dPjRs3dpxPTU1VXFycypYtq4IFC6pmzZpauHDh7Z0cAAAW4c/PAADAYwYPHqwxY8aoXLlyCg0Ndek6cXFxmjVrliZPnqyKFStqw4YN6tKli8LDw9WoUSOLKwYAwFqEbgAA4DEjRoxQs2bNXB6fnJysd955R6tWrVL9+vUlSeXKldPGjRv10UcfZRi6k5OTlZyc7DifmJh464UDAGARQncmxu48q4DAK94uAwDgwwbXDvN2CT7nvvvuc2v8wYMHdfHixXRB/cqVK6pdu3aG14mLi9Pw4cNzXCMAALcToRsAAHhM4cKFnc7ny5dPxhinbVevXnX8PykpSZL0zTffqFSpUk7j7HZ7hrcxZMgQDRgwwHE+MTFRkZGRt1Q3AABWIXQDAADLhIeHa8+ePU7bduzYoQIFCkiSqlSpIrvdrqNHj7p8/Lbdbs80kAMA4GsI3QAAwDJNmzbVu+++qxkzZqh+/fqaNWuW9uzZ43jreFBQkAYOHKj+/fsrNTVVDz30kBISErRp0yYFBwerW7duXp4BAAC3htANAAAs06JFCw0dOlSDBg3S5cuX9dxzz6lr167avXu3Y8zIkSMVHh6uuLg4HT58WEWKFFGdOnX02muvebFyAAA8w2ZuPtDqDpeYmKiQkBDFbjisgMAgb5cDAPBhnvwgtbT+k5CQoODgYI/t906Qdt+N+m2UAoIDvF0OAOQJfUP7ersEn+dq7853G2sCAAAAAOCOQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAift4uAAAAwBN6hfZScHCwt8sAAMAJr3QDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWcTl0T5gwQZcvX5YkHT16VMYYy4oCAADuoU8DAOCbXA7dAwYMUGJioiSpbNmyOnPmjGVFAQAA99CnAQDwTX6uDoyIiNAXX3yhRx99VMYYHT9+3PEX9ZuVLl3aYwUCAIDs0acBAPBNNuPi+88+/vhjvfTSS7p27VqmY4wxstlsSklJ8ViBt1tiYqJCQkIUu+GwAgKDvF0OAMCHDa4d5rF9pfWfhIQEBQcHu339O6VPZ+RW7zsAAHLC1f7j8ivdL7zwgjp16qT4+HjVqFFDq1at0l133eWRYgEAwK2hTwMA4JtcDt2SFBQUpGrVqmnq1Klq0KCB7Ha7VXUBAAA30acBAPA9boXuNN26dfN0HQAAwEPo0wAA+A6XQ3doaKhsNptLY//8888cFwQAANxHnwYAwDe5HLrHjRtnYRkAAOBW0KcBAPBNLodu3qoGAIDvok8DAOCb8uX0iocOHdIbb7yhTp066fTp05KkpUuXau/evR4rDgAA5Ax9GgAA35Cj0L1+/XpVr15dP/74o/7zn/8oKSlJkrRz507FxsZ6tEAAAOAe+jQAAL4jR6F78ODBeuutt7Ry5Ur5+/s7tjdt2lQ//PCDx4oDAADuo08DAOA7chS6d+/erSeeeCLd9mLFiumPP/645aIAAEDO0acBAPAdOQrdRYoU0cmTJ9Nt3759u0qVKnXLRQEAgJyjTwMA4DtyFLo7duyoV199VadOnZLNZlNqaqo2bdqkgQMHqmvXri7tw2azZXkaNmxYTkoDAOCO54k+DQAAPMPlrwy70TvvvKPevXsrMjJSKSkpqlKlilJSUvT000/rjTfecGkfN/4Fft68eXrzzTe1f/9+x7bAwEDH/40xSklJkZ9fjsoFAOCO4ok+DQAAPCNHr3T7+/vrk08+0eHDh/X1119r1qxZ2rdvn2bOnKn8+fO7tI8SJUo4TiEhIbLZbI7z+/btU1BQkJYuXaro6GjZ7XZt3LhR3bt3V7t27Zz2069fPzVu3NhxPjU1VXFxcSpbtqwKFiyomjVrauHChTmZJgAAuZIn+jQAAPCMW3rpODIyUpGRkbp27ZouX77sqZocBg8erDFjxqhcuXIKDQ116TpxcXGaNWuWJk+erIoVK2rDhg3q0qWLwsPD1ahRo3Tjk5OTlZyc7DifmJjosfoBAPAmq/s0AADInluvdH/11VeaNm2a07a3335bgYGBKlKkiJo3b66//vrLY8WNGDFCzZo1U/ny5VW0aNFsxycnJ+udd97RZ599phYtWqhcuXLq3r27unTpoo8++ijD68TFxSkkJMRxioyM9Fj9AADcTre7TwMAgOy5FbrHjh2rCxcuOM5///33evPNNzV06FDNnz9fx44d08iRIz1W3H333efW+IMHD+rixYtq1qyZAgMDHacZM2bo0KFDGV5nyJAhSkhIcJyOHTvmidIBALjtbnefBgAA2XPr7eV79+7V2LFjHecXLlyoZs2a6fXXX5ckBQQEqG/fvk5jbkXhwoWdzufLl0/GGKdtV69edfw/KSlJkvTNN9+k+0oUu92e4W3Y7fZMLwMAIDe53X0aAABkz63Qff78ed11112O8xs3blT79u0d56tWraoTJ054rrqbhIeHa8+ePU7bduzYoQIFCkiSqlSpIrvdrqNHj2Z4/DYAAHmZt/s0AABIz623l5cqVUq//PKLpOuvKu/cuVMPPvig4/KzZ8+qUKFCnq3wBk2bNtXWrVs1Y8YMHThwQLGxsU4hPCgoSAMHDlT//v01ffp0HTp0SD/99JM++OADTZ8+3bK6AADwBd7u0wAAID23Xulu3769+vXrp9dee03ffvutSpQooXr16jku37p1qypXruzxItO0aNFCQ4cO1aBBg3T58mU999xz6tq1q3bv3u0YM3LkSIWHhysuLk6HDx9WkSJFVKdOHb322muW1QUAgC/wdp8GAADp2czNB0ln4dKlS+rZs6e++uorlShRQh9//LEaNmzouLxJkyZq2bKlXn31VUuKvR0SExMVEhKi2A2HFRAY5O1yAAA+bHDtMI/tK63/JCQkKDg4OEf7uBP6dEY8cd8BAOAuV/uPW690FyxYUDNmzMj08rVr17qzOwAA4EH0aQAAfI9bx3SniY2NVXx8vKdrAQAAHkCfBgDAd+QodC9ZskTly5fXI488os8//1zJycmergsAAOQQfRoAAN+Ro9C9Y8cObdmyRVWrVlXfvn1VokQJ9erVS1u2bPF0fQAAwE30aQAAfEeOQrck1a5dWxMmTNCJEyc0ZcoUHT9+XA0aNFCNGjU0fvx4JSQkeLJOAADgBvo0AAC+IcehO40xRlevXtWVK1dkjFFoaKj+/e9/KzIyUvPmzfNEjQAAIIfo0wAAeFeOQ/e2bdvUp08flSxZUv3791ft2rX1yy+/aP369Tpw4IDefvttvfzyy56sFQAAuIg+DQCAb8hR6K5evbrq1aunI0eOaMqUKTp27JhGjRqlChUqOMZ06tRJZ86c8VihAADANfRpAAB8h1vf052mQ4cOeu6551SqVCkZYzIcExYWptTU1FsqDgAAuI8+DQCA78jRK91Dhw7VsmXLVK1aNQUEBCggIEDVqlXTp59+6un6AACAm+jTAAD4jhy90v3mm29q7Nixeumll1S/fn1J0ubNm9W/f38dPXpUI0aM8GiRAADAdfRpAAB8h81k9r6zLISHh2vChAnq1KmT0/Y5c+bopZde0h9//OGxAm+3xMREhYSEKHbDYQUEBnm7HACADxtcO8xj+0rrPwkJCQoODr6lfeXlPp0RT953AAC4ytX+k6O3l1+9elX33Xdfuu3R0dG6du1aTnYJAAA8hD4NAIDvyFHofuaZZzRp0qR02z/++GN17tz5losCAAA5R58GAMB3uHxM94ABAxz/t9ls+vTTT7VixQrVq1dPkvTjjz/q6NGj6tq1q+erBAAAWaJPAwDgm1wO3du3b3c6Hx0dLUk6dOiQpOtfPRIWFqa9e/d6sDwAAOAK+jQAAL7J5dC9du1aK+sAAAC3gD4NAIBvytEx3QAAAAAAIHuEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALOLn7QIAAAA8YdJfkxSQEuDtMgAAPqxvaN/bfpu80g0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAPGratGkqUqSIt8sAAMAnELoBAECGunfvLpvNlu508OBBb5cGAECu4eftAgAAgO9q2bKlpk6d6rQtPDzcS9UAAJD78Eo3AADIlN1uV4kSJZxO48ePV/Xq1VW4cGFFRkbqxRdfVFJSUqb72Llzp5o0aaKgoCAFBwcrOjpaW7dudVy+ceNGNWzYUAULFlRkZKRefvllXbhw4XZMDwAAyxG6AQCAW/Lly6cJEyZo7969mj59utasWaNBgwZlOr5z5866++67tWXLFm3btk2DBw9WgQIFJEmHDh1Sy5Yt9be//U27du3SvHnztHHjRvXp0+d2TQcAAEvx9nIAAJCpr7/+WoGBgY7zrVq10oIFCxzny5Qpo7feekv/+Mc/9OGHH2a4j6NHj+qVV17RPffcI0mqWLGi47K4uDh17txZ/fr1c1w2YcIENWrUSJMmTVJAQEC6/SUnJys5OdlxPjEx8ZbmCACAlQjdmRhQ8y4FBwd7uwwAALyqSZMmmjRpkuN84cKFtWrVKsXFxWnfvn1KTEzUtWvXdPnyZV28eFGFChVKt48BAwaoR48emjlzpmJiYtS+fXuVL19e0vW3nu/atUuzZ892jDfGKDU1VUeOHNG9996bbn9xcXEaPny4BbMFAMDzeHs5AADIVOHChVWhQgXHKTk5WY899phq1KihL774Qtu2bdPEiRMlSVeuXMlwH8OGDdPevXvVunVrrVmzRlWqVNGiRYskSUlJSerZs6d27NjhOO3cuVMHDhxwBPObDRkyRAkJCY7TsWPHrJk8AAAewCvdAADAZdu2bVNqaqree+895ct3/W/38+fPz/Z6lSpVUqVKldS/f3916tRJU6dO1RNPPKE6dero559/VoUKFVyuwW63y26353gOAADcTrzSDQAAXFahQgVdvXpVH3zwgQ4fPqyZM2dq8uTJmY6/dOmS+vTpo3Xr1ik+Pl6bNm3Sli1bHG8bf/XVV/X999+rT58+2rFjhw4cOKAlS5bwQWoAgDyD0A0AAFxWs2ZNjR07VqNHj1a1atU0e/ZsxcXFZTo+f/78Onv2rLp27apKlSqpQ4cOatWqleOY7Bo1amj9+vX69ddf1bBhQ9WuXVtvvvmmIiIibteUAACwlM0YY7xdhC9JTExUSEiIEhIS+CA1AMBtQ//JubT7btRvoxQQnP7TzgEASNM3tK/H9uVq7+aVbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIn7eLgAAAMATeoX2UnBwsLfLAADACa90AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFvHzdgG+xhgjSUpMTPRyJQCAO0la30nrQ3AdvRsA4A2u9m5C903Onj0rSYqMjPRyJQCAO9H58+cVEhLi7TJyFXo3AMCbsuvdhO6bFC1aVJJ09OjRPPVLT2JioiIjI3Xs2DEFBwd7uxyPYm65T16dl5R355ZX5yX5ztyMMTp//rwiIiK8VkNulRd7t688Lj0tL84rL85JypvzyotzkpiXN7nauwndN8mX7/ph7iEhIT67uLciODg4T85LYm65UV6dl5R355ZX5yX5xtzySmC83fJy7/aFx6UV8uK88uKcpLw5r7w4J4l5eYsrvZsPUgMAAAAAwCKEbgAAAAAALELovondbldsbKzsdru3S/GovDovibnlRnl1XlLenVtenZeUt+d2p8iLa5gX5yTlzXnlxTlJeXNeeXFOEvPKDWyG7yYBAAAAAMASvNINAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWCTPh+6JEyeqTJkyCggIUN26dfXf//43y/ELFizQPffco4CAAFWvXl3ffvut0+XGGL355psqWbKkChYsqJiYGB04cMDKKWTKnbl98sknatiwoUJDQxUaGqqYmJh047t37y6bzeZ0atmypdXTyJA7c5s2bVq6ugMCApzG+Mq6uTOvxo0bp5uXzWZT69atHWN8Yc02bNigNm3aKCIiQjabTYsXL872OuvWrVOdOnVkt9tVoUIFTZs2Ld0Yd5+7VnB3bv/5z3/UrFkzhYeHKzg4WPXr19fy5cudxgwbNizdmt1zzz0WziJj7s5t3bp1GT4eT5065TTO2+vm7rwyeg7ZbDZVrVrVMcZX1uxO5+l+7gs83et8gVU9wZus+nnpTXFxcbr//vsVFBSkYsWKqV27dtq/f3+21/P151VO5uXrz61JkyapRo0aCg4OdvxusXTp0iyv4+vrJLk/L19fp+zk6dA9b948DRgwQLGxsfrpp59Us2ZNtWjRQqdPn85w/Pfff69OnTrp+eef1/bt29WuXTu1a9dOe/bscYz517/+pQkTJmjy5Mn68ccfVbhwYbVo0UKXL1++XdOS5P7c1q1bp06dOmnt2rXavHmzIiMj1bx5c/3vf/9zGteyZUudPHnScZozZ87tmI4Td+cmScHBwU51x8fHO13uC+vm7rz+85//OM1pz549yp8/v9q3b+80zttrduHCBdWsWVMTJ050afyRI0fUunVrNWnSRDt27FC/fv3Uo0cPp3Cak8eAFdyd24YNG9SsWTN9++232rZtm5o0aaI2bdpo+/btTuOqVq3qtGYbN260ovwsuTu3NPv373eqvVixYo7LfGHd3J3X+PHjneZz7NgxFS1aNN3zzBfW7E5mRT/3Nit6nS+woid4mxU/L71t/fr16t27t3744QetXLlSV69eVfPmzXXhwoVMr5Mbnlc5mZfk28+tu+++W6NGjdK2bdu0detWNW3aVG3bttXevXszHJ8b1klyf16Sb69Ttkwe9sADD5jevXs7zqekpJiIiAgTFxeX4fgOHTqY1q1bO22rW7eu6dmzpzHGmNTUVFOiRAnz7rvvOi4/d+6csdvtZs6cORbMIHPuzu1m165dM0FBQWb69OmObd26dTNt27b1dKluc3duU6dONSEhIZnuz1fW7VbX7P333zdBQUEmKSnJsc1X1iyNJLNo0aIsxwwaNMhUrVrVadtTTz1lWrRo4Th/q/eVFVyZW0aqVKlihg8f7jgfGxtratas6bnCPMCVua1du9ZIMn/99VemY3xt3XKyZosWLTI2m8389ttvjm2+uGZ3Gk/3c1/g6V7nizzVE3yJp35e+prTp08bSWb9+vWZjskNz6ubuTKv3PjcCg0NNZ9++mmGl+XGdUqT1bxy4zrdKM++0n3lyhVt27ZNMTExjm358uVTTEyMNm/enOF1Nm/e7DReklq0aOEYf+TIEZ06dcppTEhIiOrWrZvpPq2Qk7nd7OLFi7p69aqKFi3qtH3dunUqVqyYKleurF69euns2bMerT07OZ1bUlKSoqKiFBkZme6vZL6wbp5YsylTpqhjx44qXLiw03Zvr5m7snueeeK+8hWpqak6f/58uufZgQMHFBERoXLlyqlz5846evSolyp0X61atVSyZEk1a9ZMmzZtcmzPK+s2ZcoUxcTEKCoqyml7bl6z3M6Kfu5tVvS63MrX1+pWZPbz0hclJCRIUrp+daPcuFauzEvKPc+tlJQUzZ07VxcuXFD9+vUzHJMb18mVeUm5Z50ykmdD9x9//KGUlBQVL17caXvx4sUzPabm1KlTWY5P+9edfVohJ3O72auvvqqIiAinJ2XLli01Y8YMrV69WqNHj9b69evVqlUrpaSkeLT+rORkbpUrV9Znn32mJUuWaNasWUpNTdWDDz6o48ePS/KNdbvVNfvvf/+rPXv2qEePHk7bfWHN3JXZ8ywxMVGXLl3yyOPbV4wZM0ZJSUnq0KGDY1vdunU1bdo0LVu2TJMmTdKRI0fUsGFDnT9/3ouVZq9kyZKaPHmyvvjiC33xxReKjIxU48aN9dNPP0nyzM8lbztx4oSWLl2a7nmWW9csr7Cin3ubFb0ut8quJ+RG2f289DWpqanq16+fGjRooGrVqmU6ztefVzdzdV654bm1e/duBQYGym636x//+IcWLVqkKlWqZDg2N62TO/PKDeuUFT9vF4Dbb9SoUZo7d67WrVvn9AEEHTt2dPy/evXqqlGjhsqXL69169bpkUce8UapLqlfv77TX8UefPBB3Xvvvfroo480cuRIL1bmOVOmTFH16tX1wAMPOG3PrWt2J/j88881fPhwLVmyxOk4vlatWjn+X6NGDdWtW1dRUVGaP3++nn/+eW+U6pLKlSurcuXKjvMPPvigDh06pPfff18zZ870YmWeM336dBUpUkTt2rVz2p5b1wx5y53Q6/KK3Pbzsnfv3tqzZ0+e+6wKV+eVG55blStX1o4dO5SQkKCFCxeqW7duWr9+faYBNbdwZ165YZ2ykmdf6Q4LC1P+/Pn1+++/O23//fffVaJEiQyvU6JEiSzHp/3rzj6tkJO5pRkzZoxGjRqlFStWqEaNGlmOLVeunMLCwnTw4MFbrtlVtzK3NAUKFFDt2rUddfvCut3KvC5cuKC5c+e69Mu9N9bMXZk9z4KDg1WwYEGPPAa8be7cuerRo4fmz5+f7i1eNytSpIgqVark02uWmQceeMBRd25fN2OMPvvsMz3zzDPy9/fPcmxuXrPcyIp+7m1W9LrcKruekFfc+PPSl/Tp00dff/211q5dq7vvvjvLsb7+vLqRO/O6mS8+t/z9/VWhQgVFR0crLi5ONWvW1Pjx4zMcm5vWyZ153cwX1ykreTZ0+/v7Kzo6WqtXr3ZsS01N1erVqzM9VqB+/fpO4yVp5cqVjvFly5ZViRIlnMYkJibqxx9/zPL4A0/Lydyk65/gPXLkSC1btkz33Xdftrdz/PhxnT17ViVLlvRI3a7I6dxulJKSot27dzvq9oV1u5V5LViwQMnJyerSpUu2t+ONNXNXds8zTzwGvGnOnDl69tlnNWfOHKevd8tMUlKSDh065NNrlpkdO3Y46s7t67Z+/XodPHjQpT9u5eY1y42s6OfeZkWvy618fa085cafl77AGKM+ffpo0aJFWrNmjcqWLZvtdXLDWuVkXjfLDc+t1NRUJScnZ3hZblinzGQ1r5vlhnVy4uUPcrPU3Llzjd1uN9OmTTM///yzeeGFF0yRIkXMqVOnjDHGPPPMM2bw4MGO8Zs2bTJ+fn5mzJgx5pdffjGxsbGmQIECZvfu3Y4xo0aNMkWKFDFLliwxu3btMm3btjVly5Y1ly5d8um5jRo1yvj7+5uFCxeakydPOk7nz583xhhz/vx5M3DgQLN582Zz5MgRs2rVKlOnTh1TsWJFc/nyZZ+e2/Dhw83y5cvNoUOHzLZt20zHjh1NQECA2bt3r9P8vb1u7s4rzUMPPWSeeuqpdNt9Zc3Onz9vtm/fbrZv324kmbFjx5rt27eb+Ph4Y4wxgwcPNs8884xj/OHDh02hQoXMK6+8Yn755RczceJEkz9/frNs2TLHmOzuK1+d2+zZs42fn5+ZOHGi0/Ps3LlzjjH//Oc/zbp168yRI0fMpk2bTExMjAkLCzOnT5/26bm9//77ZvHixebAgQNm9+7dpm/fviZfvnxm1apVjjG+sG7uzitNly5dTN26dTPcp6+s2Z3Min7ubVb0Ol9gRU/wNit+Xnpbr169TEhIiFm3bp1Tv7p48aJjTG58XuVkXr7+3Bo8eLBZv369OXLkiNm1a5cZPHiwsdlsZsWKFcaY3LlOxrg/L19fp+zk6dBtjDEffPCBKV26tPH39zcPPPCA+eGHHxyXNWrUyHTr1s1p/Pz5802lSpWMv7+/qVq1qvnmm2+cLk9NTTVDhw41xYsXN3a73TzyyCNm//79t2Mq6bgzt6ioKCMp3Sk2NtYYY8zFixdN8+bNTXh4uClQoICJiooyf//73297yEnjztz69evnGFu8eHHz6KOPmp9++slpf76ybu4+Hvft22ckOX4A3chX1iztq1FuPqXNpVu3bqZRo0bprlOrVi3j7+9vypUrZ6ZOnZpuv1ndV7eLu3Nr1KhRluONuf5VOCVLljT+/v6mVKlS5qmnnjIHDx68vRMz7s9t9OjRpnz58iYgIMAULVrUNG7c2KxZsybdfr29bjl5PJ47d84ULFjQfPzxxxnu01fW7E7n6X7uCzzd63yBVT3Bm6z6eelNGc1HktN9nxufVzmZl68/t5577jkTFRVl/P39TXh4uHnkkUecfi/MjetkjPvz8vV1yo7NGGM89KI5AAAAAAC4QZ49phsAAAAAAG8jdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMA4IINGzaoTZs2ioiIkM1m0+LFi926/rBhw2Sz2dKdChcubE3BAADc4W61d0uSMUZjxoxRpUqVZLfbVapUKb399ttu7YPQDQCACy5cuKCaNWtq4sSJObr+wIEDdfLkSadTlSpV1L59ew9XCgAApFvv3ZLUt29fffrppxozZoz27dunL7/8Ug888IBb+7AZY0yOKwAA4A5ks9m0aNEitWvXzrEtOTlZr7/+uubMmaNz586pWrVqGj16tBo3bpzhPnbu3KlatWppw4YNatiw4e0pHACAO1ROevcvv/yiGjVqaM+ePapcuXKOb5tXugEA8IA+ffpo8+bNmjt3rnbt2qX27durZcuWOnDgQIbjP/30U1WqVInADQCAl2TXu7/66iuVK1dOX3/9tcqWLasyZcqoR48e+vPPP926HUI3AAC36OjRo5o6daoWLFighg0bqnz58ho4cKAeeughTZ06Nd34y5cva/bs2Xr++ee9UC0AAHCldx8+fFjx8fFasGCBZsyYoWnTpmnbtm168skn3botPysmAADAnWT37t1KSUlRpUqVnLYnJyfrrrvuSjd+0aJFOn/+vLp163a7SgQAADdwpXenpqYqOTlZM2bMcIybMmWKoqOjtX//fpffck7oBgDgFiUlJSl//vzatm2b8ufP73RZYGBguvGffvqpHnvsMRUvXvx2lQgAAG7gSu8uWbKk/Pz8nIL5vffeK+n6K+WEbgAAbpPatWsrJSVFp0+fzvYY7SNHjmjt2rX68ssvb1N1AADgZq707gYNGujatWs6dOiQypcvL0n69ddfJUlRUVEu3xahGwAAFyQlJengwYOO80eOHNGOHTtUtGhRVapUSZ07d1bXrl313nvvqXbt2jpz5oxWr16tGjVqqHXr1o7rffbZZypZsqRatWrljWkAAHDHuNXeHRMTozp16ui5557TuHHjlJqaqt69e6tZs2bp3paeFb4yDAAAF6xbt05NmjRJt71bt26aNm2arl69qrfeekszZszQ//73P4WFhalevXoaPny4qlevLun6sWFRUVHq2rWr3n777ds9BQAA7iie6N0nTpzQSy+9pBUrVqhw4cJq1aqV3nvvPRUtWtTlOgjdAAAAAABYhK8MAwAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALPJ/7hsSODovCYwAAAAASUVORK5CYII=","text/plain":["<Figure size 1000x400 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":4},{"id":"85edbe6f","cell_type":"code","source":"col = 'isAccess3D'\nplt.figure(figsize=(10,4))\n\n# Create subplots in a 1x2 grid\nax1 = plt.subplot(1, 2, 1)\ntrain_df[col].value_counts().plot(kind='barh', color='skyblue', ax=ax1)\nax1.set_title(f'Distribution of {col} (Train)')\n\nax2 = plt.subplot(1, 2, 2)\ntest_df[col].value_counts().plot(kind='barh', color='lightgreen', ax=ax2)\nax2.set_title(f'Distribution of {col} (Test)')\n\nplt.tight_layout()\nplt.show()","metadata":{},"outputs":[{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA90AAAGGCAYAAABmGOKbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8ekN5oAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA/E0lEQVR4nO3dd3RUdf7G8WeSkElICL0YSggh9BARBJEWBERgVVYBYZWmLIqwNBVQVxEUsrgiCLqAukukWAgIYqUrgroC0qWX0EFpIYENkHx/f3CYnyEhTCZzczPwfp0z5zB3bu79fKfwmWducxhjjAAAAAAAgNf52V0AAAAAAAA3K0I3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjfy3SuvvCKHw5Ev64qLi1NcXJzr/rfffiuHw6G5c+fmy/p79eqlypUr58u6PJWSkqI+ffqoXLlycjgcGjx48HXnrVy5snr16pVvteHG2rdvr7/+9a/5us68fIanTp2qSpUqKS0tzctVAbAa/btgoX/7Njv6943Qo61D6EaeJCQkyOFwuG5BQUEKDw9X27ZtNWnSJJ07d84r6zly5IheeeUVbdiwwSvL86aCXJs7xo4dq4SEBPXr108zZ85U9+7dLVvXsGHD5HA49Mgjj1i2Djts3bpVnTt3VpUqVVS4cGGVKlVKzZs31+eff55l3ri4ONfnxc/PT2FhYapevbq6d++uJUuW5Gq9q1ev1uLFizV8+HBJV75U/fHzeL1bQkKCN4btkV69eunixYuaNm2abTUAoH9LBbs2d9C/8+5W7d9jx47VggULskynR1vHYYwxdhcB35WQkKDevXtr9OjRioyM1KVLl3Ts2DF9++23WrJkiSpVqqSFCxeqbt26rr+5fPmyLl++rKCgILfXs3btWt15552aPn16rn6pvXjxoiQpMDBQ0pVfylu2bKnExER16tTJ7eV4WtulS5eUkZEhp9PplXVZ4a677lJAQIBWrVp1w3nT0tLk5+enQoUK5Xo9xhhVqlRJAQEBOn78uI4fP64iRYp4UnKB89VXX2nSpElq3LixwsPDdf78ec2bN0/ff/+9pk2bpr59+7rmjYuL0549exQfHy9JSk1N1e7du/Xpp59q79696tKli2bNmuXWc9yxY0dduHBBixYtkiQtWLBAKSkpmer66KOPNGHCBJUqVco1/e6771aVKlU8Hq8nn+E/Gj58uD755BPt27cv37aaAciM/k3/dhf9+4qboX9fFRoaqk6dOmUb4unRFjFAHkyfPt1IMmvWrMny2LJly0xwcLCJiIgw58+fz9N61qxZYySZ6dOnuzV/ampqttNXrFhhJJnExMQ81ZOX2gqayMhI06FDB8vXs3z5ciPJLF++3BQqVMgkJCRYvk47Xb582cTGxprq1atnmt6iRQtTu3btbOd/+umnjSQzbNiwGy7/+PHjJiAgwLz//vvXneef//ynkWT27duX47JSUlJuuD5vWrt2rZFkli1blq/rBfD/6N/0b3fRv68oiP3bUyEhIaZnz57ZPkaPtga7l8My99xzj1566SUlJSVp1qxZrunZHRO2ZMkSNW3aVMWKFVNoaKiqV6+uF154QdKVX7fvvPNOSVLv3r2z7GITFxenOnXqaN26dWrevLkKFy7s+ttrjwm7Kj09XS+88ILKlSunkJAQPfDAAzp48GCmea53/NMfl3mj2rI7Jiw1NVXPPPOMKlasKKfTqerVq+uNN96QuWanE4fDoQEDBmjBggWqU6eOnE6nateurW+++Sb7J/waJ06c0BNPPKGyZcsqKChIsbGx+uCDD1yPXz0+bt++ffryyy9dte/fv/+6y7z2Obl06ZJGjRql6OhoBQUFqWTJkmratGm2u1nNnj1btWrVUsuWLdW6dWvNnj0723UcPnxYTzzxhMLDw+V0OhUZGal+/fq5tnpI0pkzZzRkyBBVrlxZTqdTFSpUUI8ePfT777+75klLS9PIkSNVtWpVOZ1OVaxYUcOGDctynFJO772rJk+erNq1a6tw4cIqXry4GjRooA8//PC6z5Mk+fv7q2LFijpz5kyO8/1x/kmTJqlWrVp6++23dfbs2Rzn//LLL3X58mW1bt3areVf1atXL4WGhmrPnj1q3769ihQpokcffVSS9P3336tz586qVKmS6zkbMmSILly4kGkZ2X2Gc/N+rV+/vkqUKKHPPvssV7UDyB/0b/r3H9G/c5Zf/VuSZs2apfr16ys4OFglSpRQ165ds7z/d+3apYcffljlypVTUFCQKlSooK5du7rqcjgcSk1N1QcffOB67/zxvUGPtkaA3QXg5ta9e3e98MILWrx48XVPFrF161b96U9/Ut26dTV69Gg5nU7t3r1bq1evliTVrFlTo0eP1ssvv6y+ffuqWbNmkq7sYnPVyZMn1a5dO3Xt2lWPPfaYypYtm2NdY8aMkcPh0PDhw3XixAlNnDhRrVu31oYNGxQcHOz2+Nyp7Y+MMXrggQe0YsUKPfHEE7r99tu1aNEiPffcczp8+LAmTJiQaf5Vq1bp008/1dNPP60iRYpo0qRJevjhh3XgwAGVLFnyunVduHBBcXFx2r17twYMGKDIyEglJiaqV69eOnPmjAYNGqSaNWtq5syZGjJkiCpUqKBnnnlGklS6dGm3x//KK68oPj5effr0UcOGDZWcnKy1a9fql19+UZs2bVzzpaWlad68ea51dOvWTb1799axY8dUrlw513xHjhxRw4YNdebMGfXt21c1atTQ4cOHNXfuXJ0/f16BgYFKSUlRs2bNtG3bNj3++OO644479Pvvv2vhwoU6dOiQSpUqpYyMDD3wwANatWqV+vbtq5o1a2rz5s2aMGGCdu7c6TqO6UbvPUl67733NHDgQHXq1EmDBg3S//73P23atEn//e9/9Ze//CXT85GamqoLFy7o7NmzWrhwob7++utcHf/m7++vbt266aWXXtKqVavUoUOH6877ww8/qGTJkoqIiHB7+VddvnxZbdu2VdOmTfXGG2+ocOHCkqTExESdP39e/fr1U8mSJfXzzz9r8uTJOnTokBITE2+43Ny8X++4445MzzOAgoX+nRn9m/6dk/zo32PGjNFLL72kLl26qE+fPvrtt980efJkNW/eXOvXr1exYsV08eJFtW3bVmlpafrb3/6mcuXK6fDhw/riiy905swZFS1aVDNnznS97ld3n4+Kisq0Lnq0Bezd0A5fl9PuaVcVLVrU1KtXz3V/5MiR5o9vvQkTJhhJ5rfffrvuMnLaBaxFixZGkpk6dWq2j7Vo0cJ1/+ruaeXLlzfJycmu6XPmzDGSzFtvveWaFhERke2uN9cuM6faevbsaSIiIlz3FyxYYCSZ1157LdN8nTp1Mg6Hw+zevds1TZIJDAzMNG3jxo1Gkpk8eXKWdf3RxIkTjSQza9Ys17SLFy+axo0bm9DQ0Exjj4iIcHv3tGufk9jYWLf+du7cuUaS2bVrlzHGmOTkZBMUFGQmTJiQab4ePXoYPz+/bN9PGRkZxhhjXn75ZSPJfPrpp9edZ+bMmcbPz898//33mR6fOnWqkWRWr15tjHHvvffggw9muztZdp588kkjyUgyfn5+plOnTubUqVOZ5rne7mlXzZ8/P8t7MTtNmzY19evXz3Ge7HZP69mzp5FkRowYkWX+7HYjjY+PNw6HwyQlJbmmXfsZNib379e+ffua4ODgHOsHYB36N/2b/v3/Cnr/3r9/v/H39zdjxozJNN/mzZtNQECAa/r69evdOgwjp93LjaFHW4Hdy2G50NDQHM+CWqxYMUnSZ599poyMDI/W4XQ61bt3b7fn79GjR6aTgHTq1Em33XabvvrqK4/W766vvvpK/v7+GjhwYKbpzzzzjIwx+vrrrzNNb926daZfH+vWrauwsDDt3bv3huspV66cunXr5ppWqFAhDRw4UCkpKfruu++8MJorr93WrVu1a9euHOebPXu2GjRooKpVq0qSihQpog4dOmTaRS0jI0MLFizQ/fffrwYNGmRZxtVdGufNm6fY2Fj9+c9/vu48iYmJqlmzpmrUqKHff//ddbvnnnskSStWrHDVL+X83itWrJgOHTqkNWvW5DhGSRo8eLCWLFmiDz74QO3atVN6enqm3ercERoaKkk3PHPwyZMnVbx48Vwt+4/69euXZdoftxKlpqbq999/19133y1jjNavX3/DZebm/Vq8eHFduHBB58+f93AEAKxG//5/9G/6941Y2b8//fRTZWRkqEuXLpmel3Llyik6Otr1vBQtWlSStGjRojz1V3q09xG6YbmUlJQcz3L5yCOPqEmTJurTp4/Kli2rrl27as6cOblq4OXLl3ed4dQd0dHRme47HA5VrVo1x+OhvCEpKUnh4eFZno+aNWu6Hv+jSpUqZVlG8eLFdfr06RuuJzo6Wn5+mT/i11uPp0aPHq0zZ86oWrVqiomJ0XPPPadNmzZlmufMmTP66quv1KJFC+3evdt1a9KkidauXaudO3dKkn777TclJyerTp06Oa5zz549N5xn165d2rp1q0qXLp3pVq1aNUlXjpeT3HvvDR8+XKGhoWrYsKGio6PVv3//6+5yVaNGDbVu3Vo9evTQF198oZSUFN1///1ZjvfLydWzl7pzZtjcLPePAgICVKFChSzTDxw4oF69eqlEiRIKDQ1V6dKl1aJFC0m64TFqUu7er1dr58yoQMFF//5/9G/6941Y2b937dolY4yio6OzPDfbtm1zPS+RkZEaOnSo3n//fZUqVUpt27bVO++841YPz64+erT3ELphqUOHDuns2bOuX0izExwcrJUrV2rp0qXq3r27Nm3apEceeURt2rRRenq6W+vJzXFc7rrefzTu1uQN/v7+2U73NGx5W/PmzbVnzx795z//UZ06dfT+++/rjjvu0Pvvv++aJzExUWlpaRo/fryio6Ndt6FDh0rSdU/IkhcZGRmKiYnRkiVLsr09/fTTktx779WsWVM7duzQxx9/rKZNm2revHlq2rSpRo4cecM6OnXqpDVr1ri+mLhjy5YtkpTjZ0aSSpYsecMvb9fjdDqzfKFLT09XmzZt9OWXX2r48OFasGCBlixZ4jqpkDtfonPzfj19+rQKFy5syWcXQN7Rv/OG/u0Z+nf2MjIy5HA49M0332T7vPzxutrjx4/Xpk2b9MILL+jChQsaOHCgateurUOHDrm9Pnq093EiNVhq5syZkqS2bdvmOJ+fn59atWqlVq1a6c0339TYsWP14osvasWKFWrdurXXf2m7dncqY4x2796d6XqkxYsXz/bMlUlJSZmukZib2iIiIrR06VKdO3cu0y+h27dvdz3uDREREdq0aZMyMjIyhStvr0eSSpQood69e6t3795KSUlR8+bN9corr6hPnz6SrjTlOnXqZNvkpk2bpg8//FCjRo1S6dKlFRYW5mpa1xMVFeXWPBs3blSrVq1u+Prc6L0nSSEhIXrkkUf0yCOP6OLFi3rooYc0ZswYPf/88zler/bqWb/d/YU5PT1dH374oQoXLqymTZvmOG+NGjU0b948t5brjs2bN2vnzp364IMP1KNHD9f07M5k6w379u1zbbkBUPDQvzOjf2dG/87M6v4dFRUlY4wiIyNdW/1zEhMTo5iYGP3973/XDz/8oCZNmmjq1Kl67bXXJN34vU+P9j62dMMyy5cv16uvvqrIyEjXJYmyc+rUqSzTbr/9dklyXR4iJCREkty+fMONzJgxI9MxN3PnztXRo0fVrl0717SoqCj99NNPmY7p+eKLL7JcmiE3tbVv317p6el6++23M02fMGGCHA5HpvXnRfv27XXs2DF98sknrmmXL1/W5MmTFRoa6tplOK9OnjyZ6X5oaKiqVq3qet0OHjyolStXqkuXLurUqVOWW+/evbV7927997//lZ+fnzp27KjPP/9ca9euzbKuq1sHHn74YW3cuFHz58+/7jxdunTR4cOH9d5772WZ58KFC0pNTZXk3nvv2jEGBgaqVq1aMsbo0qVLkv5/d7c/unTpkmbMmKHg4GDVqlUry+PXSk9P18CBA7Vt2zYNHDhQYWFhOc7fuHFjnT59+obHB7rr6laZP26FMcborbfe8sryr/XLL79c9yzBAOxF/86K/k3/vp786N8PPfSQ/P39NWrUqCx7SxhjXGNNTk7W5cuXMz0eExMjPz+/TJdcCwkJyfF9T4/2PrZ0wyu+/vprbd++XZcvX9bx48e1fPlyLVmyRBEREVq4cGGOvyaOHj1aK1euVIcOHRQREaETJ07oX//6lypUqOD6tTAqKkrFihXT1KlTVaRIEYWEhKhRo0aKjIz0qN4SJUqoadOm6t27t44fP66JEyeqatWqmS6L0qdPH82dO1f33XefunTpoj179mjWrFlZLquQm9ruv/9+tWzZUi+++KL279+v2NhYLV68WJ999pkGDx6cZdme6tu3r6ZNm6ZevXpp3bp1qly5subOnavVq1dr4sSJbh1v5I5atWopLi7OdU3HtWvXau7cuRowYIAk6cMPP3RdZiU77du3V0BAgGbPnq1GjRpp7NixWrx4sVq0aOG6VMjRo0eVmJioVatWqVixYnruuec0d+5cde7cWY8//rjq16+vU6dOaeHChZo6dapiY2PVvXt3zZkzR0899ZRWrFihJk2aKD09Xdu3b9ecOXO0aNEiNWjQwK333r333qty5cqpSZMmKlu2rLZt26a3335bHTp0cD2PTz75pJKTk9W8eXOVL19ex44d0+zZs7V9+3aNHz/edXKVq86ePeu69u358+e1e/duffrpp9qzZ4+6du2qV1999YbPfYcOHRQQEKClS5e6LvmRFzVq1FBUVJSeffZZHT58WGFhYZo3b57Hu7DnZN26dTp16pQefPBBry8bQO7Qv+nf9O+C37+joqL02muv6fnnn9f+/fvVsWNHFSlSRPv27dP8+fPVt29fPfvss1q+fLkGDBigzp07q1q1arp8+bJmzpwpf39/Pfzww67l1a9fX0uXLtWbb76p8PBwRUZGqlGjRpLo0ZbJn5Ok42Z19ZIjV2+BgYGmXLlypk2bNuatt97KdGmLq6695MiyZcvMgw8+aMLDw01gYKAJDw833bp1Mzt37sz0d5999pmpVauWCQgIyHSJj5wu4XC9S4589NFH5vnnnzdlypQxwcHBpkOHDpkuiXTV+PHjTfny5Y3T6TRNmjQxa9euzbLMnGq79pIjxhhz7tw5M2TIEBMeHm4KFSpkoqOjzT//+U/X5TKukmT69++fpabrXQrlWsePHze9e/c2pUqVMoGBgSYmJibby6Lk5ZIjr732mmnYsKEpVqyYCQ4ONjVq1DBjxowxFy9eNMYYExMTYypVqpTjMuPi4kyZMmXMpUuXjDHGJCUlmR49epjSpUsbp9NpqlSpYvr372/S0tJcf3Py5EkzYMAAU758eRMYGGgqVKhgevbsaX7//XfXPBcvXjTjxo0ztWvXNk6n0xQvXtzUr1/fjBo1ypw9e9YY4957b9q0aaZ58+amZMmSxul0mqioKPPcc8+5lmGMMR999JFp3bq1KVu2rAkICDDFixc3rVu3Np999lmW8V69RM7VW2hoqImOjjaPPfaYWbx4sVuvw1UPPPCAadWq1XUfv94lw0JCQrKd/9dffzWtW7c2oaGhplSpUuavf/2r6zI3f3zvXO+SYe6+X4cPH24qVaqU5T0PIP/Qv3Oujf5N/76W3f3bGGPmzZtnmjZtakJCQkxISIipUaOG6d+/v9mxY4cxxpi9e/eaxx9/3ERFRZmgoCBTokQJ07JlS7N06dJMy9m+fbtp3ry5CQ4ONpIyvTfo0dZwGFNAzugAAMiV77//XnFxcdq+fXuWM/oWVGlpaapcubJGjBihQYMG2V0OAAD5rqD2b3q0dTimGwB8VLNmzXTvvffq9ddft7sUt02fPl2FChXSU089ZXcpAADYoqD2b3q0ddjSDQAAAACARdjSDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFgkwO4CfEFGRoaOHDmiIkWKyOFw2F0OAOAmZ4zRuXPnFB4eLj8/fh/PDXo2ACC/uNuvCd1uOHLkiCpWrGh3GQCAW8zBgwdVoUIFu8vwKfRsAEB+u1G/JnS7oUiRIpKuPJlhYWE2VwMAuNklJyerYsWKrv4D99GzAQD5xd1+Teh2w9Xd08LCwmjgAIB8w+7RuUfPBgDktxv1aw4UAwAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALELoBgAAAADAIoRuAAAAAAAsQugGAAAAAMAihG4AAAAAACxC6AYAAAAAwCKEbgAAAAAALBJgdwG+5M2NJxUUetHuMgAAFhpRr5TdJcALppyeoqD0ILvLAAB4waDig+wuIU/Y0g0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWKRAhW6Hw5Hj7ZVXXrG7RAAAbnn0awAA3BdgdwF/dPToUde/P/nkE7388svasWOHa1poaKjr38YYpaenKyCgQA0BAICbHv0aAAD3Fagt3eXKlXPdihYtKofD4bq/fft2FSlSRF9//bXq168vp9OpVatWqVevXurYsWOm5QwePFhxcXGu+xkZGYqPj1dkZKSCg4MVGxuruXPn5u/gAAC4SdCvAQBwn8/97DxixAi98cYbqlKliooXL+7W38THx2vWrFmaOnWqoqOjtXLlSj322GMqXbq0WrRoYXHFAADceujXAABc4XOhe/To0WrTpo3b86elpWns2LFaunSpGjduLEmqUqWKVq1apWnTpmXbxNPS0pSWlua6n5ycnPfCAQC4heRHv776d/RsAEBB5nOhu0GDBrmaf/fu3Tp//nyWxn/x4kXVq1cv27+Jj4/XqFGjPK4RAIBbXX70a4meDQAo+HwudIeEhGS67+fnJ2NMpmmXLl1y/TslJUWS9OWXX6p8+fKZ5nM6ndmu4/nnn9fQoUNd95OTk1WxYsU81Q0AwK0kP/q1RM8GABR8Phe6r1W6dGlt2bIl07QNGzaoUKFCkqRatWrJ6XTqwIEDbh8P5nQ6c2zwAAAgd6zo1xI9GwBQ8Pl86L7nnnv0z3/+UzNmzFDjxo01a9YsbdmyxbUrWpEiRfTss89qyJAhysjIUNOmTXX27FmtXr1aYWFh6tmzp80jAADg5ke/BgDcqnw+dLdt21YvvfSShg0bpv/97396/PHH1aNHD23evNk1z6uvvqrSpUsrPj5ee/fuVbFixXTHHXfohRdesLFyAABuHfRrAMCtymGuPcAKWSQnJ6to0aIauXKvgkKL2F0OAMBCI+qVsrsEV985e/aswsLC7C7Hp1x97v6x/x8KCguyuxwAgBcMKj7I7hKy5W6/9svHmgAAAAAAuKUQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsEiA3QX4kqGxJRUWFmZ3GQAA4Ab6Fe9HzwYAFAhs6QYAAAAAwCKEbgAAAAAALJLr3cszMjKUkJCgTz/9VPv375fD4VBkZKQ6deqk7t27y+FwWFEnAADIJXo2AAD2y9WWbmOMHnjgAfXp00eHDx9WTEyMateuraSkJPXq1Ut//vOfraoTAADkAj0bAICCIVdbuhMSErRy5UotW7ZMLVu2zPTY8uXL1bFjR82YMUM9evTwapEAACB36NkAABQMudrS/dFHH+mFF17I0rwl6Z577tGIESM0e/ZsrxUHAAA8Q88GAKBgyFXo3rRpk+67777rPt6uXTtt3Lgxz0UBAIC8oWcDAFAw5Cp0nzp1SmXLlr3u42XLltXp06fzXBQAAMgbejYAAAVDrkJ3enq6AgKufxi4v7+/Ll++nOeiAABA3tCzAQAoGHJ1IjVjjHr16iWn05nt42lpaV4pCgAA5A09GwCAgiFXobtnz543nIezoAIAYD96NgAABUOuQvf06dOtqgMAAHgRPRsAgIIhV8d0AwAAAAAA9+U6dL///vvq2bOn6xf0Tz75RDVr1lSVKlU0cuRIrxcIAAA8Q88GAMB+udq9fOLEifr73/+utm3b6sUXX9SRI0c0YcIEDRkyROnp6Ro/frzKly+vvn37WlUvAABwAz0bAICCIVehe9q0aXr33Xf1l7/8RevXr1fDhg01depUPfHEE5Kk8uXLa8qUKTRwAABsRs8GAKBgyNXu5UlJSWratKkkqV69evL399ddd93lerxFixbas2ePdysEAAC5Rs8GAKBgyFXoLly4sFJTU133S5curdDQ0EzzXL582TuVAQAAj9GzAQAoGHIVumvUqKFNmza57h88eFARERGu+9u3b1flypW9VhwAAPAMPRsAgIIhV8d0jxs3TiEhIdd9/MCBA3ryySfzXBQAAMgbejYAAAWDwxhj7C6ioEtOTlbRokV19uxZhYWF2V0OAOAmR9/xHM8dACC/uNtzcn2dbunKLmqHDh1y3f/55581ePBgvfvuu54sDgAAWISeDQCAvTwK3X/5y1+0YsUKSdKxY8fUpk0b/fzzz3rxxRc1evRorxYIAAA8R88GAMBeHoXuLVu2qGHDhpKkOXPmqE6dOvrhhx80e/ZsJSQkeLM+AACQB/RsAADs5VHovnTpkpxOpyRp6dKleuCBByRdOVPq0aNHvVcdAADIE3o2AAD28ih0165dW1OnTtX333+vJUuW6L777pMkHTlyRCVLlvRqgQAAwHP0bAAA7OVR6B43bpymTZumuLg4devWTbGxsZKkhQsXunZhAwAA9qNnAwBgL48vGZaenq7k5GQVL17cNW3//v0qXLiwypQp47UCCwIuPwIAyE/e7jv0bAAAvM/SS4ZduHBBaWlpruadlJSkiRMnaseOHTdd8wYAwJfRswEAsJdHofvBBx/UjBkzJElnzpxRo0aNNH78eHXs2FFTpkzxaoEAAMBz9GwAAOzlUej+5Zdf1KxZM0nS3LlzVbZsWSUlJWnGjBmaNGmSVwsEAACeo2cDAGAvj0L3+fPnVaRIEUnS4sWL9dBDD8nPz0933XWXkpKSvFogAADwHD0bAAB7eRS6q1atqgULFujgwYNatGiR7r33XknSiRMnOGkJAAAFCD0bAAB7eRS6X375ZT377LOqXLmyGjZsqMaNG0u68gt6vXr1vFogAADwHD0bAAB7eXzJsGPHjuno0aOKjY2Vn9+V7P7zzz8rLCxMNWrU8GqRduPyIwCA/OTtvkPPBgDA+yy9ZJgklStXTkWKFNGSJUt04cIFSdKdd9550zVvAAB8HT0bAAD7eBS6T548qVatWqlatWpq3769jh49Kkl64okn9Mwzz3i1QAAA4Dl6NgAA9vIodA8ZMkSFChXSgQMHVLhwYdf0Rx55RN98843XigMAAHlDzwYAwF4BnvzR4sWLtWjRIlWoUCHT9OjoaC4/AgBAAULPBgDAXh5t6U5NTc30a/lVp06dktPpzHNRAADAO+jZAADYy6PQ3axZM82YMcN13+FwKCMjQ6+//rpatmzpteIAAEDe0LMBALCXR7uXv/7662rVqpXWrl2rixcvatiwYdq6datOnTql1atXe7tGAADgIXo2AAD28mhLd506dbRz5041bdpUDz74oFJTU/XQQw9p/fr1ioqK8naNAADAQ/RsAADs5TDGGLuLKOjcveg5AADeQN/xHM8dACC/uNtzPNrSPX36dCUmJmaZnpiYqA8++MCTRQIAAAvQswEAsJdHoTs+Pl6lSpXKMr1MmTIaO3ZsnosCAADeQc8GAMBeHoXuAwcOKDIyMsv0iIgIHThwIM9FAQAA76BnAwBgL49Cd5kyZbRp06Ys0zdu3KiSJUvmuSgAAOAd9GwAAOzlUeju1q2bBg4cqBUrVig9PV3p6elavny5Bg0apK5du3q7RgAA4CF6NgAA9vLoOt2vvvqq9u/fr1atWikg4MoiMjIy1KNHD44PAwCgAKFnAwBgrzxdMmzXrl3asGGDgoODFRMTo4iICG/WVmBw+REAQH6you/QswEA8C53e45HW7qvio6OVnR0dF4WAQAA8gE9GwAAe3h0TPfDDz+scePGZZn++uuvq3PnznkuCgAAeAc9GwAAe3kUuleuXKn27dtnmd6uXTutXLkyz0UBAADvoGcDAGAvj0J3SkqKAgMDs0wvVKiQkpOT81wUAADwDno2AAD28ih0x8TE6JNPPsky/eOPP1atWrXyXBQAAPAOejYAAPby6ERqL730kh566CHt2bNH99xzjyRp2bJl+uijj5SYmOjVAgEAgOfo2QAA2Muj0H3//fdrwYIFGjt2rObOnavg4GDVrVtXS5cuVYsWLbxdIwAA8BA9GwAAe+XpOt3Z2bJli+rUqePNRdqOa34CAPJTfvUdejYAAJ5zt+d4dEz3tc6dO6d3331XDRs2VGxsrDcWCQAALEDPBgAgf+UpdK9cuVI9evTQbbfdpjfeeEP33HOPfvrpJ2/VBgAAvISeDQCAPXJ9TPexY8eUkJCgf//730pOTlaXLl2UlpamBQsWcBZUAAAKEHo2AAD2y9WW7vvvv1/Vq1fXpk2bNHHiRB05ckSTJ0+2qjYAAOAhejYAAAVDrrZ0f/311xo4cKD69eun6Ohoq2oCAAB5RM8GAKBgyNWW7lWrVuncuXOqX7++GjVqpLffflu///67VbUBAAAP0bMBACgYchW677rrLr333ns6evSonnzySX388ccKDw9XRkaGlixZonPnzllVJwAAyAV6NgAABUOer9O9Y8cO/fvf/9bMmTN15swZtWnTRgsXLvRWfQUC1/wEAOQnq/oOPRsAAO/Jt+t0V69eXa+//roOHTqkjz76KK+LAwAAFqFnAwCQ/3J9ybDsJCcna/ny5apevfpN94s5AAA3E3o2AAD5y6Mt3V26dNHbb78tSbpw4YIaNGigLl26qG7dupo3b55XCwQAAJ6jZwMAYC+PQvfKlSvVrFkzSdL8+fNljNGZM2c0adIkvfbaa14tEAAAeI6eDQCAvTwK3WfPnlWJEiUkSd98840efvhhFS5cWB06dNCuXbu8WiAAAPAcPRsAAHt5FLorVqyoH3/8Uampqfrmm2907733SpJOnz6toKAgrxYIAAA8R88GAMBeHp1IbfDgwXr00UcVGhqqSpUqKS4uTtKVXdhiYmK8WR8AAMgDejYAAPbyKHQ//fTTatSokQ4cOKB7771Xfn5XNphXqVJFY8aM8WqBAADAc/RsAADs5XboHjp0qF599VWFhIRo6NChrunff/99lnnvvvtu71RXwLy58aSCQi/aXQYAoAAaUa+U3SW40LOlKaenKCid3ecBAJkNKj4o39fpduhev369Ll265Pr39TgcjrxXBQAAPEbPBgCg4HA7dK9YsSLbfwMAgIKFng0AQMHh0dnLAQAAAADAjRG6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsAihGwAAAAAAixC6AQAAAACwCKEbAAAAAACLELoBAAAAALAIoRsAAAAAAIsQugEAAAAAsIhPhu6EhAQVK1bM7jIAAEAO6NcAANgcunv16iWHw5Hltnv3bjvLAgAAf0C/BgDAcwF2F3Dfffdp+vTpmaaVLl3apmoAAEB26NcAAHjG9t3LnU6nypUrl+n21ltvKSYmRiEhIapYsaKefvpppaSkXHcZGzduVMuWLVWkSBGFhYWpfv36Wrt2revxVatWqVmzZgoODlbFihU1cOBApaam5sfwAAC4KdCvAQDwjO2hOzt+fn6aNGmStm7dqg8++EDLly/XsGHDrjv/o48+qgoVKmjNmjVat26dRowYoUKFCkmS9uzZo/vuu08PP/ywNm3apE8++USrVq3SgAED8ms4AADclOjXAADcmO27l3/xxRcKDQ113W/Xrp0SExNd9ytXrqzXXntNTz31lP71r39lu4wDBw7oueeeU40aNSRJ0dHRrsfi4+P16KOPavDgwa7HJk2apBYtWmjKlCkKCgrKsry0tDSlpaW57icnJ+dpjAAA+LqC2K8lejYAoOCzPXS3bNlSU6ZMcd0PCQnR0qVLFR8fr+3btys5OVmXL1/W//73P50/f16FCxfOsoyhQ4eqT58+mjlzplq3bq3OnTsrKipK0pVd2TZt2qTZs2e75jfGKCMjQ/v27VPNmjWzLC8+Pl6jRo2yYLQAAPimgtivJXo2AKDgs3338pCQEFWtWtV1S0tL05/+9CfVrVtX8+bN07p16/TOO+9Iki5evJjtMl555RVt3bpVHTp00PLly1WrVi3Nnz9fkpSSkqInn3xSGzZscN02btyoXbt2uRr9tZ5//nmdPXvWdTt48KA1gwcAwEcUxH4t0bMBAAWf7Vu6r7Vu3TplZGRo/Pjx8vO78pvAnDlzbvh31apVU7Vq1TRkyBB169ZN06dP15///Gfdcccd+vXXX1W1alW3a3A6nXI6nR6PAQCAm11B6NcSPRsAUPDZvqX7WlWrVtWlS5c0efJk7d27VzNnztTUqVOvO/+FCxc0YMAAffvtt0pKStLq1au1Zs0a125ow4cP1w8//KABAwZow4YN2rVrlz777DNOzAIAQB7QrwEAcE+BC92xsbF68803NW7cONWpU0ezZ89WfHz8def39/fXyZMn1aNHD1WrVk1dunRRu3btXMd31a1bV99995127typZs2aqV69enr55ZcVHh6eX0MCAOCmQ78GAMA9DmOMsbuIgi45OVlFixbVyJV7FRRaxO5yAAAF0Ih6pby2rKt95+zZswoLC/Pacm8FV5+7f+z/h4LCsj/jOQDg1jWo+CCvLcvdfl3gtnQDAAAAAHCzIHQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGCRALsL8CVDY0sqLCzM7jIAAMAN9Cvej54NACgQ2NINAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYJMDuAnyBMUaSlJycbHMlAIBbwdV+c7X/wH30bABAfnG3XxO63XDy5ElJUsWKFW2uBABwKzl37pyKFi1qdxk+hZ4NAMhvN+rXhG43lChRQpJ04MABvvx4SXJysipWrKiDBw8qLCzM7nJuGjyv3sdz6n08pzdmjNG5c+cUHh5udyk+52bu2Tf7Z4fx+a6beWwS4/NlVo/N3X5N6HaDn9+VQ9+LFi16070R7RYWFsZzagGeV+/jOfU+ntOc3WyBMb/cCj37Zv/sMD7fdTOPTWJ8vszKsbnTrzmRGgAAAAAAFiF0AwAAAABgEUK3G5xOp0aOHCmn02l3KTcNnlNr8Lx6H8+p9/Gcwko38/vrZh6bxPh82c08Nonx+bKCMjaH4XokAAAAAABYgi3dAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3W545513VLlyZQUFBalRo0b6+eef7S7JZ8XHx+vOO+9UkSJFVKZMGXXs2FE7duywu6ybyj/+8Q85HA4NHjzY7lJ83uHDh/XYY4+pZMmSCg4OVkxMjNauXWt3WT4rPT1dL730kiIjIxUcHKyoqCi9+uqr4nyeyK3c9uXExETVqFFDQUFBiomJ0VdffZVPleZebsaWkJAgh8OR6RYUFJSP1ebOypUrdf/99ys8PFwOh0MLFiy44d98++23uuOOO+R0OlW1alUlJCRYXqcncju2b7/9Nstr53A4dOzYsfwpOBc8/e7mK587T8bnS5+9KVOmqG7dugoLC1NYWJgaN26sr7/+Ose/8ZXXTsr9+Ox67QjdN/DJJ59o6NChGjlypH755RfFxsaqbdu2OnHihN2l+aTvvvtO/fv3108//aQlS5bo0qVLuvfee5Wammp3aTeFNWvWaNq0aapbt67dpfi806dPq0mTJipUqJC+/vpr/frrrxo/fryKFy9ud2k+a9y4cZoyZYrefvttbdu2TePGjdPrr7+uyZMn210afEhu+/IPP/ygbt266YknntD69evVsWNHdezYUVu2bMnnym/Mk+8cYWFhOnr0qOuWlJSUjxXnTmpqqmJjY/XOO++4Nf++ffvUoUMHtWzZUhs2bNDgwYPVp08fLVq0yOJKcy+3Y7tqx44dmV6/MmXKWFSh5zz57uZLnztPv5v6ymevQoUK+sc//qF169Zp7dq1uueee/Tggw9q69at2c7vS6+dlPvxSTa9dgY5atiwoenfv7/rfnp6ugkPDzfx8fE2VnXzOHHihJFkvvvuO7tL8Xnnzp0z0dHRZsmSJaZFixZm0KBBdpfk04YPH26aNm1qdxk3lQ4dOpjHH38807SHHnrIPProozZVBF+U277cpUsX06FDh0zTGjVqZJ588klL6/REbsc2ffp0U7Ro0Xyqzrskmfnz5+c4z7Bhw0zt2rUzTXvkkUdM27ZtLaws79wZ24oVK4wkc/r06XypyZvc+e7mS5+7a7kzPl/+7BljTPHixc3777+f7WO+/NpdldP47Hrt2NKdg4sXL2rdunVq3bq1a5qfn59at26tH3/80cbKbh5nz56VJJUoUcLmSnxf//791aFDh0zvV3hu4cKFatCggTp37qwyZcqoXr16eu+99+wuy6fdfffdWrZsmXbu3ClJ2rhxo1atWqV27drZXBl8hSd9+ccff8zy/2Lbtm0LXB/39DtHSkqKIiIiVLFixRtu3fE1vvLa5cXtt9+u2267TW3atNHq1avtLsct7nx38+XXzt3vpr742UtPT9fHH3+s1NRUNW7cONt5fPm1c2d8kj2vHaE7B7///rvS09NVtmzZTNPLli1bII+58TUZGRkaPHiwmjRpojp16thdjk/7+OOP9csvvyg+Pt7uUm4ae/fu1ZQpUxQdHa1FixapX79+GjhwoD744AO7S/NZI0aMUNeuXVWjRg0VKlRI9erV0+DBg/Xoo4/aXRp8hCd9+dixYz7Rxz0ZW/Xq1fWf//xHn332mWbNmqWMjAzdfffdOnToUH6UbLnrvXbJycm6cOGCTVV5x2233aapU6dq3rx5mjdvnipWrKi4uDj98ssvdpeWI3e/u/nK5+5a7o7P1z57mzdvVmhoqJxOp5566inNnz9ftWrVynZeX3ztcjM+u167AEuXDuSgf//+2rJli1atWmV3KT7t4MGDGjRokJYsWVJgT+LhizIyMtSgQQONHTtWklSvXj1t2bJFU6dOVc+ePW2uzjfNmTNHs2fP1ocffqjatWu7jtEMDw/nOQU80Lhx40xbc+6++27VrFlT06ZN06uvvmpjZbiR6tWrq3r16q77d999t/bs2aMJEyZo5syZNlaWs5v9u5u74/O1z1716tW1YcMGnT17VnPnzlXPnj313XffXTeY+prcjM+u147QnYNSpUrJ399fx48fzzT9+PHjKleunE1V3RwGDBigL774QitXrlSFChXsLsenrVu3TidOnNAdd9zhmpaenq6VK1fq7bffVlpamvz9/W2s0DfddtttWf6zrlmzpubNm2dTRb7vueeec23tlqSYmBglJSUpPj6e0A23eNKXy5Ur5xN93BvfOa7uQbJ7924rSsx313vtwsLCFBwcbFNV1mnYsGGBDrO5+e7mK5+7P8rLd9OC/tkLDAxU1apVJUn169fXmjVr9NZbb2natGlZ5vXF1y4347tWfr127F6eg8DAQNWvX1/Lli1zTcvIyNCyZctyPE4A12eM0YABAzR//nwtX75ckZGRdpfk81q1aqXNmzdrw4YNrluDBg306KOPasOGDQRuDzVp0iTLJUN27typiIgImyryfefPn5efX+a24+/vr4yMDJsqgq/xpC83btw40/yStGTJkgLXx73xnSM9PV2bN2/WbbfdZlWZ+cpXXjtv2bBhQ4F87Tz57uZLr503vpv62mcvIyNDaWlp2T7mS6/d9eQ0vmvl22uX76du8zEff/yxcTqdJiEhwfz666+mb9++plixYubYsWN2l+aT+vXrZ4oWLWq+/fZbc/ToUdft/Pnzdpd2U+Hs5Xn3888/m4CAADNmzBiza9cuM3v2bFO4cGEza9Ysu0vzWT179jTly5c3X3zxhdm3b5/59NNPTalSpcywYcPsLg0+5EZ9uXv37mbEiBGu+VevXm0CAgLMG2+8YbZt22ZGjhxpChUqZDZv3mzXEK4rt2MbNWqUWbRokdmzZ49Zt26d6dq1qwkKCjJbt261awg5OnfunFm/fr1Zv369kWTefPNNs379epOUlGSMMWbEiBGme/furvn37t1rChcubJ577jmzbds288477xh/f3/zzTff2DWE68rt2CZMmGAWLFhgdu3aZTZv3mwGDRpk/Pz8zNKlS+0awnW5893Nlz93nozPlz57I0aMMN99953Zt2+f2bRpkxkxYoRxOBxm8eLFxhjffu2Myf347HrtCN1umDx5sqlUqZIJDAw0DRs2ND/99JPdJfksSdnepk+fbndpNxVCt3d8/vnnpk6dOsbpdJoaNWqYd9991+6SfFpycrIZNGiQqVSpkgkKCjJVqlQxL774oklLS7O7NPiYnPpyixYtTM+ePTPNP2fOHFOtWjUTGBhoateubb788st8rth9uRnb4MGDXfOWLVvWtG/f3vzyyy82VO2eq5fJuvZ2dUw9e/Y0LVq0yPI3t99+uwkMDDRVqlQpsN8Xcju2cePGmaioKBMUFGRKlChh4uLizPLly+0p/gbc+e7my587T8bnS5+9xx9/3ERERJjAwEBTunRp06pVK1cgNca3Xztjcj8+u147hzHGWLstHQAAAACAWxPHdAMAAAAAYBFCNwAAAAAAFiF0AwAAAABgEUI3AAAAAAAWIXQDAAAAAGARQjcAAAAAABYhdAMAAAAAYBFCNwAAubRy5Urdf//9Cg8Pl8Ph0IIFC3K9DGOM3njjDVWrVk1Op1Ply5fXmDFjvF8sAAC3qILSrwNyvVYAAG5xqampio2N1eOPP66HHnrIo2UMGjRIixcv1htvvKGYmBidOnVKp06d8nKlAADcugpKv3YYY4xHawcAAHI4HJo/f746duzompaWlqYXX3xRH330kc6cOaM6depo3LhxiouLkyRt27ZNdevW1ZYtW1S9enV7CgcA4BZiZ79m93IAALxswIAB+vHHH/Xxxx9r06ZN6ty5s+677z7t2rVLkvT555+rSpUq+uKLLxQZGanKlSurT58+bOkGACAf5Ve/JnQDAOBFBw4c0PTp05WYmKhmzZopKipKzz77rJo2barp06dLkvbu3aukpCQlJiZqxowZSkhI0Lp169SpUyebqwcA4NaQn/2aY7oBAPCizZs3Kz09XdWqVcs0PS0tTSVLlpQkZWRkKC0tTTNmzHDN9+9//1v169fXjh072OUcAACL5We/JnQDAOBFKSkp8vf317p16+Tv75/psdDQUEnSbbfdpoCAgEyNvmbNmpKu/PJO6AYAwFr52a8J3QAAeFG9evWUnp6uEydOqFmzZtnO06RJE12+fFl79uxRVFSUJGnnzp2SpIiIiHyrFQCAW1V+9mvOXg4AQC6lpKRo9+7dkq407TfffFMtW7ZUiRIlVKlSJT322GNavXq1xo8fr3r16um3337TsmXLVLduXXXo0EEZGRm68847FRoaqokTJyojI0P9+/dXWFiYFi9ebPPoAAC4ORSUfk3oBgAgl7799lu1bNkyy/SePXsqISFBly5d0muvvaYZM2bo8OHDKlWqlO666y6NGjVKMTExkqQjR47ob3/7mxYvXqyQkBC1a9dO48ePV4kSJfJ7OAAA3JQKSr8mdAMAAAAAYBEuGQYAAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFiE0A0AAAAAgEUI3QAAAAAAWITQDQAAAACARQjdAAAAAABYhNANAAAAAIBFCN0AAAAAAFjk/wDQ8hWlsdMhFgAAAABJRU5ErkJggg==","text/plain":["<Figure size 1000x400 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":6},{"id":"108e5f5c","cell_type":"markdown","source":"### Company Information\n- corporateTariffCode - Corporate tariff code for business travel policies","metadata":{}},{"id":"1a2ab0c1","cell_type":"code","source":"col = 'corporateTariffCode'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')\nprint(f'Unique {col} in train:', train_df[col].nunique())\nprint(f'Unique  {col} in test:', test_df[col].nunique())\nprint(f'Intersection of  {col}:', len(set(train_df[col]) & set(test_df[col])))","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of corporateTariffCode in train: 50.89%\n","Missing ratio of corporateTariffCode in test: 51.25%\n","Unique corporateTariffCode in train: 170\n","Unique  corporateTariffCode in test: 133\n","Intersection of  corporateTariffCode: 122\n"]}],"execution_count":62},{"id":"d8a85f3d","cell_type":"markdown","source":"### Search and Route Information\n- searchRoute - Flight route: single direction without \"/\" or round trip with \"/\"\n- requestDate - Date and time when search was performed","metadata":{}},{"id":"b94a343a","cell_type":"code","source":"col = 'searchRoute'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of searchRoute in train: 0.00%\n","Missing ratio of searchRoute in test: 0.00%\n"]}],"execution_count":63},{"id":"f145bd6e","cell_type":"code","source":"print(f\"Percentage of round trips in train_df: {(train_df['searchRoute'].str.contains('/').sum() / len(train_df)) * 100:.2f}%\")\nprint(f\"Percentage of round trips in test_df: {(test_df['searchRoute'].str.contains('/').sum() / len(test_df)) * 100:.2f}%\")","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Percentage of round trips in train_df: 75.82%\n","Percentage of round trips in test_df: 83.82%\n"]}],"execution_count":26},{"id":"eba8eae6","cell_type":"markdown","source":"### Pricing Information\n- totalPrice - Total ticket price\n- taxes - Taxes and fees component","metadata":{}},{"id":"d8d8ac88","cell_type":"code","source":"col = 'totalPrice'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')\ntrain_df[col].describe()","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of totalPrice in train: 0.00%\n","Missing ratio of totalPrice in test: 0.00%\n"]},{"data":{"text/plain":["count    1.814537e+07\n","mean     4.631444e+04\n","std      7.506808e+04\n","min      7.700000e+02\n","25%      1.289700e+04\n","50%      2.497600e+04\n","75%      5.510800e+04\n","max      9.944355e+06\n","Name: totalPrice, dtype: float64"]},"execution_count":64,"metadata":{},"output_type":"execute_result"}],"execution_count":64},{"id":"86154c7a","cell_type":"code","source":"col = 'totalPrice'\nnp.log1p(train_df[col]).plot(kind='hist', bins=50, color='skyblue')\nnp.log1p(test_df[col]).plot(kind='hist', bins=50, color='lightgreen')\nplt.title(f'Distribution of log({col})')\nplt.xlabel(col)\nplt.ylabel('Frequency')\nplt.legend(['Train', 'Test'])\nplt.show()","metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":44},{"id":"7211884a","cell_type":"code","source":"train_df.taxes.describe()","metadata":{},"outputs":[{"data":{"text/plain":["count    1.814537e+07\n","mean     4.284696e+03\n","std      1.183975e+04\n","min      0.000000e+00\n","25%      1.006000e+03\n","50%      1.246000e+03\n","75%      1.746000e+03\n","max      8.979210e+05\n","Name: taxes, dtype: float64"]},"execution_count":41,"metadata":{},"output_type":"execute_result"}],"execution_count":41},{"id":"e9b2cced","cell_type":"code","source":"col = 'taxes'\nprint(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\nprint(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')\nnp.log1p(train_df[col]).plot(kind='hist', bins=50, color='skyblue')\nnp.log1p(test_df[col]).plot(kind='hist', bins=50, color='lightgreen')\nplt.title(f'Distribution of log({col})')\nplt.xlabel(col)\nplt.ylabel('Frequency')\nplt.legend(['Train', 'Test'])\nplt.show()","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of taxes in train: 0.00%\n","Missing ratio of taxes in test: 0.00%\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"execution_count":65},{"id":"19f989e3","cell_type":"markdown","source":"### Flight Timing and Duration\n- legs0_departureAt - Departure time for outbound flight\n- legs0_arrivalAt - Arrival time for outbound flight\n- legs0_duration - Duration of outbound flight\n- legs1_departureAt - Departure time for return flight\n- legs1_arrivalAt - Arrival time for return flight\n- legs1_duration - Duration of return flight","metadata":{}},{"id":"2dd72eea","cell_type":"code","source":"for leg in range(2):\n    for col in [f'legs{leg}_departureAt', f'legs{leg}_arrivalAt', f'legs{leg}_duration']:\n        print(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\n        print(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of legs0_departureAt in train: 0.00%\n","Missing ratio of legs0_departureAt in test: 0.00%\n","Missing ratio of legs0_arrivalAt in train: 0.00%\n","Missing ratio of legs0_arrivalAt in test: 0.00%\n","Missing ratio of legs0_duration in train: 0.00%\n","Missing ratio of legs0_duration in test: 0.00%\n","Missing ratio of legs1_departureAt in train: 24.18%\n","Missing ratio of legs1_departureAt in test: 16.18%\n","Missing ratio of legs1_arrivalAt in train: 24.18%\n","Missing ratio of legs1_arrivalAt in test: 16.18%\n","Missing ratio of legs1_duration in train: 24.18%\n","Missing ratio of legs1_duration in test: 16.18%\n"]}],"execution_count":67},{"id":"1c9ab38d","cell_type":"markdown","source":"The missing ratios of legs1 match the ratio of single trips.","metadata":{}},{"id":"f8484ed5","cell_type":"code","source":"train_df.legs0_departureAt.head()","metadata":{},"outputs":[{"data":{"text/plain":["0    2024-06-15T15:40:00\n","1    2024-06-15T09:25:00\n","2    2024-06-15T09:25:00\n","3    2024-06-15T09:25:00\n","4    2024-06-15T09:25:00\n","Name: legs0_departureAt, dtype: object"]},"execution_count":68,"metadata":{},"output_type":"execute_result"}],"execution_count":68},{"id":"07e7df17","cell_type":"markdown","source":"### Flight Segments\nEach flight leg (legs0/legs1) can consist of multiple segments (segments0-3) when there are connections. Each segment contains:\n##### (1) Geography and Route\n- legs*_segments*_departureFrom_airport_iata - Departure airport code\n- legs*_segments*_arrivalTo_airport_iata - Arrival airport code\n- legs*_segments*_arrivalTo_airport_city_iata - Arrival city code\n##### (2) Flight Details\n- legs*_segments*_marketingCarrier_code - Marketing airline code\n- legs*_segments*_operatingCarrier_code - Operating airline code (actual carrier)\n- legs*_segments*_aircraft_code - Aircraft type code\n- legs*_segments*_flightNumber - Flight number\n- legs*_segments*_duration - Segment duration\n##### (3) Service Characteristics\n- legs*_segments*_baggageAllowance_quantity - Baggage allowance: small numbers indicate piece count, large numbers indicate weight in kg\n- legs*_segments*_baggageAllowance_weightMeasurementType - Type of baggage measurement\n- legs*_segments*_cabinClass - Service class: 1.0 = economy, 2.0 = business, 4.0 = premium\n- legs*_segments*_seatsAvailable - Number of available seats","metadata":{}},{"id":"63596fb6","cell_type":"code","source":"for col in train_df.columns[train_df.columns.str.contains('segments3') | train_df.columns.str.contains('segments2')]:\n    print(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\n    print(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')\n    print('-' * 50)","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of legs0_segments2_aircraft_code in train: 98.90%\n","Missing ratio of legs0_segments2_aircraft_code in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_arrivalTo_airport_city_iata in train: 98.90%\n","Missing ratio of legs0_segments2_arrivalTo_airport_city_iata in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_arrivalTo_airport_iata in train: 98.90%\n","Missing ratio of legs0_segments2_arrivalTo_airport_iata in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_baggageAllowance_quantity in train: 98.90%\n","Missing ratio of legs0_segments2_baggageAllowance_quantity in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_baggageAllowance_weightMeasurementType in train: 98.90%\n","Missing ratio of legs0_segments2_baggageAllowance_weightMeasurementType in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_cabinClass in train: 98.90%\n","Missing ratio of legs0_segments2_cabinClass in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_departureFrom_airport_iata in train: 98.90%\n","Missing ratio of legs0_segments2_departureFrom_airport_iata in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_duration in train: 98.90%\n","Missing ratio of legs0_segments2_duration in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_flightNumber in train: 98.90%\n","Missing ratio of legs0_segments2_flightNumber in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_marketingCarrier_code in train: 98.90%\n","Missing ratio of legs0_segments2_marketingCarrier_code in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_operatingCarrier_code in train: 98.90%\n","Missing ratio of legs0_segments2_operatingCarrier_code in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments2_seatsAvailable in train: 98.90%\n","Missing ratio of legs0_segments2_seatsAvailable in test: 99.23%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_aircraft_code in train: 100.00%\n","Missing ratio of legs0_segments3_aircraft_code in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_arrivalTo_airport_city_iata in train: 100.00%\n","Missing ratio of legs0_segments3_arrivalTo_airport_city_iata in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_arrivalTo_airport_iata in train: 100.00%\n","Missing ratio of legs0_segments3_arrivalTo_airport_iata in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_baggageAllowance_quantity in train: 100.00%\n","Missing ratio of legs0_segments3_baggageAllowance_quantity in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_baggageAllowance_weightMeasurementType in train: 100.00%\n","Missing ratio of legs0_segments3_baggageAllowance_weightMeasurementType in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_cabinClass in train: 100.00%\n","Missing ratio of legs0_segments3_cabinClass in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_departureFrom_airport_iata in train: 100.00%\n","Missing ratio of legs0_segments3_departureFrom_airport_iata in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_duration in train: 100.00%\n","Missing ratio of legs0_segments3_duration in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_flightNumber in train: 100.00%\n","Missing ratio of legs0_segments3_flightNumber in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_marketingCarrier_code in train: 100.00%\n","Missing ratio of legs0_segments3_marketingCarrier_code in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_operatingCarrier_code in train: 100.00%\n","Missing ratio of legs0_segments3_operatingCarrier_code in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs0_segments3_seatsAvailable in train: 100.00%\n","Missing ratio of legs0_segments3_seatsAvailable in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_aircraft_code in train: 99.27%\n","Missing ratio of legs1_segments2_aircraft_code in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_arrivalTo_airport_city_iata in train: 99.27%\n","Missing ratio of legs1_segments2_arrivalTo_airport_city_iata in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_arrivalTo_airport_iata in train: 99.27%\n","Missing ratio of legs1_segments2_arrivalTo_airport_iata in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_baggageAllowance_quantity in train: 99.28%\n","Missing ratio of legs1_segments2_baggageAllowance_quantity in test: 99.47%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_baggageAllowance_weightMeasurementType in train: 99.28%\n","Missing ratio of legs1_segments2_baggageAllowance_weightMeasurementType in test: 99.47%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_cabinClass in train: 99.27%\n","Missing ratio of legs1_segments2_cabinClass in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_departureFrom_airport_iata in train: 99.27%\n","Missing ratio of legs1_segments2_departureFrom_airport_iata in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_duration in train: 99.27%\n","Missing ratio of legs1_segments2_duration in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_flightNumber in train: 99.27%\n","Missing ratio of legs1_segments2_flightNumber in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_marketingCarrier_code in train: 99.27%\n","Missing ratio of legs1_segments2_marketingCarrier_code in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_operatingCarrier_code in train: 99.27%\n","Missing ratio of legs1_segments2_operatingCarrier_code in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments2_seatsAvailable in train: 99.27%\n","Missing ratio of legs1_segments2_seatsAvailable in test: 99.46%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_aircraft_code in train: 100.00%\n","Missing ratio of legs1_segments3_aircraft_code in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_arrivalTo_airport_city_iata in train: 100.00%\n","Missing ratio of legs1_segments3_arrivalTo_airport_city_iata in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_arrivalTo_airport_iata in train: 100.00%\n","Missing ratio of legs1_segments3_arrivalTo_airport_iata in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_baggageAllowance_quantity in train: 100.00%\n","Missing ratio of legs1_segments3_baggageAllowance_quantity in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_baggageAllowance_weightMeasurementType in train: 100.00%\n","Missing ratio of legs1_segments3_baggageAllowance_weightMeasurementType in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_cabinClass in train: 100.00%\n","Missing ratio of legs1_segments3_cabinClass in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_departureFrom_airport_iata in train: 100.00%\n","Missing ratio of legs1_segments3_departureFrom_airport_iata in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_duration in train: 100.00%\n","Missing ratio of legs1_segments3_duration in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_flightNumber in train: 100.00%\n","Missing ratio of legs1_segments3_flightNumber in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_marketingCarrier_code in train: 100.00%\n","Missing ratio of legs1_segments3_marketingCarrier_code in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_operatingCarrier_code in train: 100.00%\n","Missing ratio of legs1_segments3_operatingCarrier_code in test: 100.00%\n","--------------------------------------------------\n","Missing ratio of legs1_segments3_seatsAvailable in train: 100.00%\n","Missing ratio of legs1_segments3_seatsAvailable in test: 100.00%\n","--------------------------------------------------\n"]}],"execution_count":74},{"id":"1e48cb3a","cell_type":"code","source":"# Geography and Route\n\"\"\"\n- legs*_segments*_departureFrom_airport_iata - Departure airport code\n- legs*_segments*_arrivalTo_airport_iata - Arrival airport code\n- legs*_segments*_arrivalTo_airport_city_iata - Arrival city code\n\"\"\"\nfor leg in range(2):\n    for segment in range(2):\n        for col in [f'legs{leg}_segments{segment}_departureFrom_airport_iata',\n                    f'legs{leg}_segments{segment}_arrivalTo_airport_iata',\n                    f'legs{leg}_segments{segment}_arrivalTo_airport_city_iata']:\n            print(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\n            print(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[],"execution_count":null},{"id":"91071f26","cell_type":"code","source":"# Flight Details\n\"\"\"\n- legs*_segments*_marketingCarrier_code - Marketing airline code\n- legs*_segments*_operatingCarrier_code - Operating airline code (actual carrier)\n- legs*_segments*_aircraft_code - Aircraft type code\n- legs*_segments*_flightNumber - Flight number\n- legs*_segments*_duration - Segment duration\n\"\"\"\nfor leg in range(2):\n    for segment in range(2):\n        for col in [f'legs{leg}_segments{segment}_marketingCarrier_code',\n                    f'legs{leg}_segments{segment}_operatingCarrier_code',\n                    f'legs{leg}_segments{segment}_aircraft_code',\n                    f'legs{leg}_segments{segment}_flightNumber',\n                    f'legs{leg}_segments{segment}_duration']:\n            print(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\n            print(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of legs0_segments0_marketingCarrier_code in train: 0.00%\n","Missing ratio of legs0_segments0_marketingCarrier_code in test: 0.00%\n","Missing ratio of legs0_segments0_operatingCarrier_code in train: 0.00%\n","Missing ratio of legs0_segments0_operatingCarrier_code in test: 0.00%\n","Missing ratio of legs0_segments0_aircraft_code in train: 0.00%\n","Missing ratio of legs0_segments0_aircraft_code in test: 0.00%\n","Missing ratio of legs0_segments0_flightNumber in train: 0.00%\n","Missing ratio of legs0_segments0_flightNumber in test: 0.00%\n","Missing ratio of legs0_segments0_duration in train: 0.00%\n","Missing ratio of legs0_segments0_duration in test: 0.00%\n","Missing ratio of legs0_segments1_marketingCarrier_code in train: 78.87%\n","Missing ratio of legs0_segments1_marketingCarrier_code in test: 79.46%\n","Missing ratio of legs0_segments1_operatingCarrier_code in train: 78.87%\n","Missing ratio of legs0_segments1_operatingCarrier_code in test: 79.46%\n","Missing ratio of legs0_segments1_aircraft_code in train: 78.87%\n","Missing ratio of legs0_segments1_aircraft_code in test: 79.46%\n","Missing ratio of legs0_segments1_flightNumber in train: 78.87%\n","Missing ratio of legs0_segments1_flightNumber in test: 79.46%\n","Missing ratio of legs0_segments1_duration in train: 78.87%\n","Missing ratio of legs0_segments1_duration in test: 79.46%\n","Missing ratio of legs1_segments0_marketingCarrier_code in train: 24.18%\n","Missing ratio of legs1_segments0_marketingCarrier_code in test: 16.18%\n","Missing ratio of legs1_segments0_operatingCarrier_code in train: 24.18%\n","Missing ratio of legs1_segments0_operatingCarrier_code in test: 16.18%\n","Missing ratio of legs1_segments0_aircraft_code in train: 24.18%\n","Missing ratio of legs1_segments0_aircraft_code in test: 16.18%\n","Missing ratio of legs1_segments0_flightNumber in train: 24.18%\n","Missing ratio of legs1_segments0_flightNumber in test: 16.18%\n","Missing ratio of legs1_segments0_duration in train: 24.18%\n","Missing ratio of legs1_segments0_duration in test: 16.18%\n","Missing ratio of legs1_segments1_marketingCarrier_code in train: 84.14%\n","Missing ratio of legs1_segments1_marketingCarrier_code in test: 84.50%\n","Missing ratio of legs1_segments1_operatingCarrier_code in train: 84.14%\n","Missing ratio of legs1_segments1_operatingCarrier_code in test: 84.50%\n","Missing ratio of legs1_segments1_aircraft_code in train: 84.14%\n","Missing ratio of legs1_segments1_aircraft_code in test: 84.50%\n","Missing ratio of legs1_segments1_flightNumber in train: 84.14%\n","Missing ratio of legs1_segments1_flightNumber in test: 84.50%\n","Missing ratio of legs1_segments1_duration in train: 84.14%\n","Missing ratio of legs1_segments1_duration in test: 84.50%\n"]}],"execution_count":76},{"id":"4b8fc46f","cell_type":"code","source":"# Service Characteristics\n\"\"\"\n- legs*_segments*_baggageAllowance_quantity - Baggage allowance: small numbers indicate piece count, large numbers indicate weight in kg\n- legs*_segments*_baggageAllowance_weightMeasurementType - Type of baggage measurement\n- legs*_segments*_cabinClass - Service class: 1.0 = economy, 2.0 = business, 4.0 = premium\n- legs*_segments*_seatsAvailable - Number of available seats\n\"\"\"\nfor leg in range(2):\n    for segment in range(2):\n        for col in [f'legs{leg}_segments{segment}_baggageAllowance_quantity',\n                    f'legs{leg}_segments{segment}_baggageAllowance_weightMeasurementType',\n                    f'legs{leg}_segments{segment}_cabinClass',\n                    f'legs{leg}_segments{segment}_seatsAvailable']:\n            print(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\n            print(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of legs0_segments0_baggageAllowance_quantity in train: 0.01%\n","Missing ratio of legs0_segments0_baggageAllowance_quantity in test: 0.00%\n","Missing ratio of legs0_segments0_baggageAllowance_weightMeasurementType in train: 0.01%\n","Missing ratio of legs0_segments0_baggageAllowance_weightMeasurementType in test: 0.00%\n","Missing ratio of legs0_segments0_cabinClass in train: 0.00%\n","Missing ratio of legs0_segments0_cabinClass in test: 0.00%\n","Missing ratio of legs0_segments0_seatsAvailable in train: 0.44%\n","Missing ratio of legs0_segments0_seatsAvailable in test: 0.00%\n","Missing ratio of legs0_segments1_baggageAllowance_quantity in train: 79.06%\n","Missing ratio of legs0_segments1_baggageAllowance_quantity in test: 79.50%\n","Missing ratio of legs0_segments1_baggageAllowance_weightMeasurementType in train: 79.06%\n","Missing ratio of legs0_segments1_baggageAllowance_weightMeasurementType in test: 79.50%\n","Missing ratio of legs0_segments1_cabinClass in train: 79.06%\n","Missing ratio of legs0_segments1_cabinClass in test: 79.50%\n","Missing ratio of legs0_segments1_seatsAvailable in train: 79.09%\n","Missing ratio of legs0_segments1_seatsAvailable in test: 79.50%\n","Missing ratio of legs1_segments0_baggageAllowance_quantity in train: 24.95%\n","Missing ratio of legs1_segments0_baggageAllowance_quantity in test: 16.31%\n","Missing ratio of legs1_segments0_baggageAllowance_weightMeasurementType in train: 24.95%\n","Missing ratio of legs1_segments0_baggageAllowance_weightMeasurementType in test: 16.31%\n","Missing ratio of legs1_segments0_cabinClass in train: 24.94%\n","Missing ratio of legs1_segments0_cabinClass in test: 16.31%\n","Missing ratio of legs1_segments0_seatsAvailable in train: 25.25%\n","Missing ratio of legs1_segments0_seatsAvailable in test: 16.31%\n","Missing ratio of legs1_segments1_baggageAllowance_quantity in train: 84.55%\n","Missing ratio of legs1_segments1_baggageAllowance_quantity in test: 84.61%\n","Missing ratio of legs1_segments1_baggageAllowance_weightMeasurementType in train: 84.55%\n","Missing ratio of legs1_segments1_baggageAllowance_weightMeasurementType in test: 84.61%\n","Missing ratio of legs1_segments1_cabinClass in train: 84.54%\n","Missing ratio of legs1_segments1_cabinClass in test: 84.61%\n","Missing ratio of legs1_segments1_seatsAvailable in train: 84.56%\n","Missing ratio of legs1_segments1_seatsAvailable in test: 84.61%\n"]}],"execution_count":77},{"id":"ffabd1b2","cell_type":"code","source":"train_df['legs0_segments0_baggageAllowance_weightMeasurementType'].value_counts()","metadata":{},"outputs":[{"data":{"text/plain":["legs0_segments0_baggageAllowance_weightMeasurementType\n","0.0    17074181\n","1.0     1070127\n","Name: count, dtype: int64"]},"execution_count":84,"metadata":{},"output_type":"execute_result"}],"execution_count":84},{"id":"f1a3db3e","cell_type":"code","source":"train_df['legs0_segments0_cabinClass'].value_counts()","metadata":{},"outputs":[{"data":{"text/plain":["legs0_segments0_cabinClass\n","1.0    14721259\n","2.0     3205841\n","4.0      216667\n","3.0        1605\n","Name: count, dtype: int64"]},"execution_count":85,"metadata":{},"output_type":"execute_result"}],"execution_count":85},{"id":"5bd872df","cell_type":"markdown","source":"### Cancellation and Exchange Rules\n#### Rule 0 (Cancellation)\n- miniRules0_monetaryAmount - Monetary penalty for cancellation\n- miniRules0_percentage - Percentage penalty for cancellation\n- miniRules0_statusInfos - Cancellation rule status (0 = no cancellation allowed)\n#### Rule 1 (Exchange)\n- miniRules1_monetaryAmount - Monetary penalty for exchange\n- miniRules1_percentage - Percentage penalty for exchange\n- miniRules1_statusInfos - Exchange rule status","metadata":{}},{"id":"6271463c","cell_type":"code","source":"for col in train_df.columns[train_df.columns.str.contains('miniRules')]:\n    print(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\n    print(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of miniRules0_monetaryAmount in train: 7.69%\n","Missing ratio of miniRules0_monetaryAmount in test: 7.31%\n","Missing ratio of miniRules0_percentage in train: 98.35%\n","Missing ratio of miniRules0_percentage in test: 97.37%\n","Missing ratio of miniRules0_statusInfos in train: 8.10%\n","Missing ratio of miniRules0_statusInfos in test: 7.98%\n","Missing ratio of miniRules1_monetaryAmount in train: 7.69%\n","Missing ratio of miniRules1_monetaryAmount in test: 7.31%\n","Missing ratio of miniRules1_percentage in train: 98.49%\n","Missing ratio of miniRules1_percentage in test: 97.95%\n","Missing ratio of miniRules1_statusInfos in train: 8.37%\n","Missing ratio of miniRules1_statusInfos in test: 8.33%\n"]}],"execution_count":null},{"id":"b35b8afc","cell_type":"markdown","source":"### Pricing Policy Information\n- pricingInfo_isAccessTP - Compliance with corporate Travel Policy\n- pricingInfo_passengerCount - Number of passengers","metadata":{}},{"id":"fbca871f","cell_type":"code","source":"for col in train_df.columns[train_df.columns.str.contains('pricingInfo')]:\n    print(f'Missing ratio of {col} in train: {train_df[col].isnull().mean():.2%}')\n    print(f'Missing ratio of {col} in test: {test_df[col].isnull().mean():.2%}')","metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Missing ratio of pricingInfo_isAccessTP in train: 4.99%\n","Missing ratio of pricingInfo_isAccessTP in test: 3.55%\n","Missing ratio of pricingInfo_passengerCount in train: 0.00%\n","Missing ratio of pricingInfo_passengerCount in test: 0.00%\n"]}],"execution_count":88},{"id":"74860b14","cell_type":"code","source":"train_df['pricingInfo_isAccessTP'].value_counts()","metadata":{},"outputs":[{"data":{"text/plain":["pricingInfo_isAccessTP\n","0.0    8640071\n","1.0    8600256\n","Name: count, dtype: int64"]},"execution_count":89,"metadata":{},"output_type":"execute_result"}],"execution_count":89},{"id":"02f3bbc5","cell_type":"code","source":"train_df['pricingInfo_passengerCount'].value_counts()","metadata":{},"outputs":[{"data":{"text/plain":["pricingInfo_passengerCount\n","1    18145372\n","Name: count, dtype: int64"]},"execution_count":91,"metadata":{},"output_type":"execute_result"}],"execution_count":null},{"id":"758b903c","cell_type":"code","source":"test_df['pricingInfo_passengerCount'].value_counts()","metadata":{},"outputs":[{"data":{"text/plain":["pricingInfo_passengerCount\n","1    6897776\n","Name: count, dtype: int64"]},"execution_count":92,"metadata":{},"output_type":"execute_result"}],"execution_count":92},{"id":"e90726c1","cell_type":"markdown","source":"### Target Variable\n- selected - In training data: binary variable (0 = not selected, 1 = selected). In submission: ranks within ranker_id groups","metadata":{}},{"id":"64797626","cell_type":"code","source":"train_df.selected.value_counts()","metadata":{},"outputs":[{"data":{"text/plain":["selected\n","0    18039833\n","1      105539\n","Name: count, dtype: int64"]},"execution_count":93,"metadata":{},"output_type":"execute_result"}],"execution_count":93}]}