big-mart-sales-using-xgbregressor.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/yahyasoker/big-mart-sales-using-xgbregressor?scriptVersionId=127915607\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown"},{"cell_type":"markdown","id":"252cea0e","metadata":{"papermill":{"duration":0.009213,"end_time":"2023-05-01T14:24:08.675347","exception":false,"start_time":"2023-05-01T14:24:08.666134","status":"completed"},"tags":[]},"source":["### [1-Preparing Data](#1)\n","    cleaning data\n","    Numerical Features\n","    Categorical Features\n","    Data Pre-Processing\n","### [2-Training Data](#2)\n","### [3-Evaluation](#3)"]},{"cell_type":"markdown","id":"c6bc61f6","metadata":{"papermill":{"duration":0.008411,"end_time":"2023-05-01T14:24:08.691768","exception":false,"start_time":"2023-05-01T14:24:08.683357","status":"completed"},"tags":[]},"source":["<a id='1'></a>\n","### Preparing Data"]},{"cell_type":"code","execution_count":1,"id":"713b0db6","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2023-05-01T14:24:08.709295Z","iopub.status.busy":"2023-05-01T14:24:08.708921Z","iopub.status.idle":"2023-05-01T14:24:10.168203Z","shell.execute_reply":"2023-05-01T14:24:10.16697Z"},"papermill":{"duration":1.471275,"end_time":"2023-05-01T14:24:10.170916","exception":false,"start_time":"2023-05-01T14:24:08.699641","status":"completed"},"tags":[]},"outputs":[],"source":["import numpy as np\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.preprocessing import LabelEncoder\n","from sklearn.model_selection import train_test_split\n","from xgboost import XGBRegressor\n","from sklearn import metrics"]},{"cell_type":"code","execution_count":2,"id":"9367066a","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:10.188503Z","iopub.status.busy":"2023-05-01T14:24:10.188088Z","iopub.status.idle":"2023-05-01T14:24:10.279286Z","shell.execute_reply":"2023-05-01T14:24:10.277988Z"},"papermill":{"duration":0.102627,"end_time":"2023-05-01T14:24:10.281573","exception":false,"start_time":"2023-05-01T14:24:10.178946","status":"completed"},"tags":[]},"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>Item_Identifier</th>\n","      <th>Item_Weight</th>\n","      <th>Item_Fat_Content</th>\n","      <th>Item_Visibility</th>\n","      <th>Item_Type</th>\n","      <th>Item_MRP</th>\n","      <th>Outlet_Identifier</th>\n","      <th>Outlet_Establishment_Year</th>\n","      <th>Outlet_Size</th>\n","      <th>Outlet_Location_Type</th>\n","      <th>Outlet_Type</th>\n","      <th>Item_Outlet_Sales</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>FDA15</td>\n","      <td>9.30</td>\n","      <td>Low Fat</td>\n","      <td>0.016047</td>\n","      <td>Dairy</td>\n","      <td>249.8092</td>\n","      <td>OUT049</td>\n","      <td>1999</td>\n","      <td>Medium</td>\n","      <td>Tier 1</td>\n","      <td>Supermarket Type1</td>\n","      <td>3735.1380</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>DRC01</td>\n","      <td>5.92</td>\n","      <td>Regular</td>\n","      <td>0.019278</td>\n","      <td>Soft Drinks</td>\n","      <td>48.2692</td>\n","      <td>OUT018</td>\n","      <td>2009</td>\n","      <td>Medium</td>\n","      <td>Tier 3</td>\n","      <td>Supermarket Type2</td>\n","      <td>443.4228</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>FDN15</td>\n","      <td>17.50</td>\n","      <td>Low Fat</td>\n","      <td>0.016760</td>\n","      <td>Meat</td>\n","      <td>141.6180</td>\n","      <td>OUT049</td>\n","      <td>1999</td>\n","      <td>Medium</td>\n","      <td>Tier 1</td>\n","      <td>Supermarket Type1</td>\n","      <td>2097.2700</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>FDX07</td>\n","      <td>19.20</td>\n","      <td>Regular</td>\n","      <td>0.000000</td>\n","      <td>Fruits and Vegetables</td>\n","      <td>182.0950</td>\n","      <td>OUT010</td>\n","      <td>1998</td>\n","      <td>NaN</td>\n","      <td>Tier 3</td>\n","      <td>Grocery Store</td>\n","      <td>732.3800</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>NCD19</td>\n","      <td>8.93</td>\n","      <td>Low Fat</td>\n","      <td>0.000000</td>\n","      <td>Household</td>\n","      <td>53.8614</td>\n","      <td>OUT013</td>\n","      <td>1987</td>\n","      <td>High</td>\n","      <td>Tier 3</td>\n","      <td>Supermarket Type1</td>\n","      <td>994.7052</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  Item_Identifier  Item_Weight Item_Fat_Content  Item_Visibility  \\\n","0           FDA15         9.30          Low Fat         0.016047   \n","1           DRC01         5.92          Regular         0.019278   \n","2           FDN15        17.50          Low Fat         0.016760   \n","3           FDX07        19.20          Regular         0.000000   \n","4           NCD19         8.93          Low Fat         0.000000   \n","\n","               Item_Type  Item_MRP Outlet_Identifier  \\\n","0                  Dairy  249.8092            OUT049   \n","1            Soft Drinks   48.2692            OUT018   \n","2                   Meat  141.6180            OUT049   \n","3  Fruits and Vegetables  182.0950            OUT010   \n","4              Household   53.8614            OUT013   \n","\n","   Outlet_Establishment_Year Outlet_Size Outlet_Location_Type  \\\n","0                       1999      Medium               Tier 1   \n","1                       2009      Medium               Tier 3   \n","2                       1999      Medium               Tier 1   \n","3                       1998         NaN               Tier 3   \n","4                       1987        High               Tier 3   \n","\n","         Outlet_Type  Item_Outlet_Sales  \n","0  Supermarket Type1          3735.1380  \n","1  Supermarket Type2           443.4228  \n","2  Supermarket Type1          2097.2700  \n","3      Grocery Store           732.3800  \n","4  Supermarket Type1           994.7052  "]},"execution_count":2,"metadata":{},"output_type":"execute_result"}],"source":["df = pd.read_csv(\"/kaggle/input/bigmart-sales-data/Train.csv\")\n","df.head()"]},{"cell_type":"code","execution_count":3,"id":"25c9bab2","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:10.300421Z","iopub.status.busy":"2023-05-01T14:24:10.300015Z","iopub.status.idle":"2023-05-01T14:24:10.313354Z","shell.execute_reply":"2023-05-01T14:24:10.312117Z"},"papermill":{"duration":0.025921,"end_time":"2023-05-01T14:24:10.315762","exception":false,"start_time":"2023-05-01T14:24:10.289841","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Item_Identifier                 0\n","Item_Weight                  1463\n","Item_Fat_Content                0\n","Item_Visibility                 0\n","Item_Type                       0\n","Item_MRP                        0\n","Outlet_Identifier               0\n","Outlet_Establishment_Year       0\n","Outlet_Size                  2410\n","Outlet_Location_Type            0\n","Outlet_Type                     0\n","Item_Outlet_Sales               0\n","dtype: int64"]},"execution_count":3,"metadata":{},"output_type":"execute_result"}],"source":["df.isnull().sum()"]},{"cell_type":"markdown","id":"69c151d2","metadata":{"papermill":{"duration":0.008131,"end_time":"2023-05-01T14:24:10.33226","exception":false,"start_time":"2023-05-01T14:24:10.324129","status":"completed"},"tags":[]},"source":["### Data Cleaning"]},{"cell_type":"code","execution_count":4,"id":"c1101d0b","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:10.350421Z","iopub.status.busy":"2023-05-01T14:24:10.349998Z","iopub.status.idle":"2023-05-01T14:24:10.358035Z","shell.execute_reply":"2023-05-01T14:24:10.357103Z"},"papermill":{"duration":0.020026,"end_time":"2023-05-01T14:24:10.360404","exception":false,"start_time":"2023-05-01T14:24:10.340378","status":"completed"},"tags":[]},"outputs":[],"source":["# filling the missing data in \"Item_weight column\" with \"Mean\" value\n","df['Item_Weight'].fillna(df['Item_Weight'].mean(), inplace=True)"]},{"cell_type":"code","execution_count":5,"id":"a3672ff3","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:10.380588Z","iopub.status.busy":"2023-05-01T14:24:10.380179Z","iopub.status.idle":"2023-05-01T14:24:10.406329Z","shell.execute_reply":"2023-05-01T14:24:10.405411Z"},"papermill":{"duration":0.038651,"end_time":"2023-05-01T14:24:10.408814","exception":false,"start_time":"2023-05-01T14:24:10.370163","status":"completed"},"tags":[]},"outputs":[],"source":["# filling the missing data in \"Outlet_Size\" column with Mode\n","mode_of_Outlet_size = df.pivot_table(values='Outlet_Size', \n","                                                columns='Outlet_Type', \n","                                                aggfunc=(lambda x: x.mode()[0]))"]},{"cell_type":"code","execution_count":6,"id":"5f18ddc0","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:10.427912Z","iopub.status.busy":"2023-05-01T14:24:10.427005Z","iopub.status.idle":"2023-05-01T14:24:10.43249Z","shell.execute_reply":"2023-05-01T14:24:10.431397Z"},"papermill":{"duration":0.017726,"end_time":"2023-05-01T14:24:10.435031","exception":false,"start_time":"2023-05-01T14:24:10.417305","status":"completed"},"tags":[]},"outputs":[],"source":["miss_values = df['Outlet_Size'].isnull()  "]},{"cell_type":"code","execution_count":7,"id":"32237bb1","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:10.45341Z","iopub.status.busy":"2023-05-01T14:24:10.453002Z","iopub.status.idle":"2023-05-01T14:24:10.530706Z","shell.execute_reply":"2023-05-01T14:24:10.529397Z"},"papermill":{"duration":0.090284,"end_time":"2023-05-01T14:24:10.533592","exception":false,"start_time":"2023-05-01T14:24:10.443308","status":"completed"},"tags":[]},"outputs":[],"source":["df.loc[miss_values, 'Outlet_Size'] = df.loc[miss_values,'Outlet_Type'].apply(lambda x: mode_of_Outlet_size[x])"]},{"cell_type":"markdown","id":"2af8e985","metadata":{"papermill":{"duration":0.007986,"end_time":"2023-05-01T14:24:10.550059","exception":false,"start_time":"2023-05-01T14:24:10.542073","status":"completed"},"tags":[]},"source":["### Numerical Features"]},{"cell_type":"code","execution_count":8,"id":"f35d60b8","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:10.568737Z","iopub.status.busy":"2023-05-01T14:24:10.568298Z","iopub.status.idle":"2023-05-01T14:24:11.01319Z","shell.execute_reply":"2023-05-01T14:24:11.011939Z"},"papermill":{"duration":0.457559,"end_time":"2023-05-01T14:24:11.015878","exception":false,"start_time":"2023-05-01T14:24:10.558319","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:4: UserWarning: \n","\n","`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n","\n","Please adapt your code to use either `displot` (a figure-level function with\n","similar flexibility) or `histplot` (an axes-level function for histograms).\n","\n","For a guide to updating your code to use the new functions, please see\n","https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n","\n","  after removing the cwd from sys.path.\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAhoAAAITCAYAAABBtrXuAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAA9hAAAPYQGoP6dpAABkb0lEQVR4nO3dd3xb9b0//tc5R9uybMs7y3FC4kwSssNIIJQLNGGGXGgLpZRyL2WVS4ELpe19wIWm/Aq9/ZZRZgcQVmgIlCYUKJAUCCuskEES24md5W1LsrbO+f0hS7HibUs650iv5+OhB0Tj6P2J4uiVzxQURVFARERElAKi2gUQERFR5mLQICIiopRh0CAiIqKUYdAgIiKilGHQICIiopRh0CAiIqKUYdAgIiKilGHQICIiopQxqF2AmhRFgSzrf78yURQyoh29yeS2AWyf3mVy+zK5bQDbl4zrC4IwqOdmddCQZQWtrZ1qlzEiBoOIgoIcuFxehMOy2uUkVSa3DWD79C6T25fJbQPYvmRwOnMgSYMLGhw6ISIiopRh0CAiIqKUYdAgIiKilGHQICIiopRh0CAiIqKUYdAgIiKilGHQICIiopRh0CAiIqKUYdAgIiKilGHQICIiopRh0CAiIqKUYdAgIiKilGHQICIiopRh0CAiIqKUYdAgIiKilGHQICIiopRh0CAiIqKUYdAgIiKilGHQICIiopQxqF0A6ZcgCL3eryhKmishIiKtYtCgYYkA8PtDvT5mMRsgpbccIiLSKAYNGjJBEOD3h7BjXytCYTnhMaNBxLTxTtgtRvZsEBERgwYNXygsIxiKqF0GERFpGCeDEhERUcowaBAREVHKMGgQERFRynCOBiWdIERvAJe/EhFlOwYNSipJEiCKIty+MIDeAwWXvxIRZQ8GDUoqSRTgC4ZRXd+BYLjnihQufyUiyi4MGpQSXPpKREQAJ4MSERFRCjFoEBERUcowaBAREVHKcI4G9au3E1r7OLSViIioBwYN6lNfJ7SKogC559OJiIh6YNCgXvV3QqvNYkBFuQNCHxtyERERxTBoUL96W6ZqMnJqDxERDQ6DRoaIbvvds4eBm2IREZGaGDQygMcbRIc3BEXuGSq43TcREamJQUPnBAHw+sPYta8V/mDiEAe3+yYiIrUxaGQIbvlNRERaxFl9RERElDLs0aARCYVlfLyjAS0uP6xmA0YX52B8uUPtsoiISCMYNGjYwhEZ735+EIdbvACAdk8Qh1u8MBokTB/vVLk6IiLSAg6d0LDIioK3tx7A4RYvDJKAk2aWYW5VMQBgy9dHsK2mReUKiYhIC1QPGvv378cvf/lLnHfeeZg2bRpWrFjR6/M2bdqE888/HzNnzsQZZ5yBNWvWpLlS6m57TQv2N7ghiQKWzRmDiaPzML3SiZNmlgEAPtrRgOZ2n8pVEhGR2lQPGnv27MGmTZtQUVGBiRMn9vqczz//HNdccw2mTZuGxx9/HBdccAHuvvturF27Ns3VUsy7nx0CAEwbX4CyQlv8/uOPK8TsyUUAgK9rW1WpjYiItEP1ORrLli3Dt771LQDAbbfdhq+//rrHcx566CFMmzYNv/rVrwAAixYtwuHDh/H//t//w8qVKyGKquelrNLQ6sW+wy6IgoCqcQUJjwmCgDPmj8MXu5tR1+CBqzMIR45JpUqJiEhtqn9DDxQSgsEgPvzwQyxfvjzh/nPOOQdNTU3YsWNHKsujXny5Nzr/YuLoPNgsPbNqWaEN40pzAQDb2atBRJTVVO/RGEhdXR1CoRAmTJiQcP9xxx0HAKiursaMGTOGfX2DQfWsNSKSJAKyAlEUIImJZ51IogBBFGAwCFCUoZ20KgiA0HXN7tf1+EKoPtgBAJg1qbDHe4qCAEEQMHtSIeoa3Kg55MLcqmJYzYYh1yRJYsJ/Mw3bp2+Z3L5MbhvA9qWb5oNGR0f0S83hSNybIfbr2OPDIYoCCgpyhl+cRvhavTCbjRClxFNNjAYRVosJ+fm2Pl7Zv6DshdVqgsF49Jj4PQddUBRg4pg8jCl19DhC3moxwGCQUDk6H6VOGxpavdjf0Ik5U0qGXZPDYR1W/XrB9ulbJrcvk9sGsH3povmgEdPbyaT93T8YsqzA5fIO+/VaEOuRCQRC8AfCCY+ZjBJ8/iDa2xUM9agTQQB8/hB8vmDC1uY1B9oBADMqC+HzBxE85nwVQZERDkfgD4QwoTwXDa1e7Klvw5RxeUOuSZJEOBxWuFw+RCJy/0/WIbZP3zK5fZncNoDtSwaHwzroHhPNB428vOgX1LE9Fy6XC0DPno6hCof1/YcsmrMEyLKCyDGnt0ZkBYqsIBxWhnyomiAIULquGbtuKCzjSGs0mE0Zn4/W9kCP95SV6HvJEWBMiR3Y3oDmDj86OoOwW43DqikSkXX/OfWH7dO3TG5fJrcNYPvSRRsDOP0YN24cjEYjampqEu7fu3cvAPS5JJaS73BLJ2QFcOSYUJw/cJec1WxASUH0eXUN7lSXR0REGqT5oGEymbBo0SJs3Lgx4f7XXnsNxcXFmDZtmkqVZZ+DTZ0AgIoy+6CHrCq6Vp/UNXhSVhcREWmX6kMnPp8PmzZtAgAcPHgQHo8Hr7/+OgBgwYIFcDqduPbaa3HppZfi5z//Oc455xx89tlnWLt2Le666y7uoZEmiqIcDRpd4WEwxpXa8cmuRjS2+eALhGEySgO/iIiIMobqQaOlpQU/+clPEu6L/fqpp57CwoULccIJJ+Dhhx/Gb3/7W6xfvx5lZWX4+c9/jlWrVqlRclZq9wTgDYQhiQJGFQ9+pU6O1YiiPAuaO/yoa3Bjpt2cwiqJiEhrVA8aY8aMwTfffDPg85YuXYqlS5emoSLqzaHm6CTQskIbDENcmz22xI7mDj8ONXsxk1NqiIiyCscdaFBiB6TFJncORXnXWSgNrV7IQ11nS0REusagQYPS1OEHABTnDT1oOB0WGA0igmEZrV3XISKi7MCgQQPy+sPw+sMQABTmWYb8elEUUNrVE3KouTPJ1RERkZYxaNCAmjuiwyZ5dhOMwzwbJnaUPIMGEVF2YdCgATW1R4c7igaxSVdfYvM0jrR6Ec7ALX+JiKh3DBo0oFiPRvEwhk1i8u1mmI0SwhEFdUe4SygRUbZg0KB+yYqClo6R92gIghAfPtld356M0oiISAcYNKhf7e4AwhEFBklAnt00omuVOaNBZc+BjgGeSUREmYJBg/rV2BYdNinKs0Ic5PkmfYkdxFbX4IYscz8NIqJswKBB/WruGjYZzrLWY+XbzTBIAvzBCA61cPUJEVE2YNCgfrW5okGjIHfkZ5SIohDv1ag+yOETIqJswKBBfVIUBW3uAACgIHdk8zNiYluYM2gQEWUHBg3qU7sngGBYhiAAjpzknLpaUhBdecKgQUSUHRg0qE+xE1sdOSZI4sgmgsbEejQOtXjh9YeSck0iItIuBg3q0+Gu7cIL7MnpzQAAq9mAoq6JpTWHXEm7LhERaRODBvUptjIkPwkTQbsbX+4AAFQzaBARZTwGDepTrEcjf4QbdR2rMhY0OE+DiCjjMWhQryKyjCOt0TkayVja2l1FWS4AYN8RNxSFG3cREWUyBg3qVWObL771uN1qTOq1RxXlQBIFeHwhtHTt00FERJmJQYN6daDJAyDamyGMcOvxYxkNIkYX5wAA9vMkVyKijMagkeUEQej1drCpa8VJ7si3Hu/5nsD4sug8jf0NnoT3JSKizGJQuwBSTwSAv4+9LPY3RHsakj0/Q5IEiKKIssJoj0b1wQ54utVgMRsgJfUdiYhITQwaWUoQBPj9IezY14pQWO7xeH1jdOgkP4l7aACAJArwBcOIRKLvWXvYhS/2NEEQBBgNIqaNd8JuMXKSKBFRhmDQyHKhsIxgKJJwn6IoaO864yQvyUtbYxw5JggC4A9G0OYOJH3CKRERaQPnaFAPnf4wIrICURSQa01N0DBIYry3pJUrT4iIMhaDBvXg6gwCAArzLBCTdMZJbwod0YmmLR0MGkREmYpBg3pweaNBozjfmtL3ceZFezRaXIGUvg8REamHQYN6cHdGV4GkOmjEejRaXX5O/iQiylAMGtRDbOikuCC1QaMg1wwB0QmhvkBkwOcTEZH+MGhQD0eHTpK/WVd3BkmEo2tVS6ub8zSIiDIRgwYliMgKPN70DJ0AgLNrQ7A2ztMgIspIDBqUwOMNQkFXb0NOapa2dlcQm6fhZtAgIspEDBqUwNXVm5FvN6Xl7JFYjwb30iAiykwMGpQgNhE0P8lnnPTF6Yi+j9sbQjDMCaFERJmGQYMSxINGirYeP5bFZIDNHN0Jv5XzNIiIMg6DBiWIBY28JB+m1p+Crl6NVu4QSkSUcRg0KIHbF52jkZeGiaAxsXkaLZynQUSUcRg0KC4SkeH1hwEgLStOYpw884SIKGMxaFCcxxcNGQZJgNUspe19YxNC29wBRCJy2t6XiIhSj0GD4jy+6PwMu9WYlqWtMXarEUZJRERW0NDmS9v7EhFR6jFoUJy7aw+NXFv6hk0AQBCE+ITQg02etL43ERGlFoMGxXm6JoLarca0v3dB14TQ+kYGDSKiTMKgQXFHezTSHzRiE0IPNnWm/b2JiCh1GDQoLt6joUbQ6OrRONDkgaIoaX9/IiJKDQYNAgAoytFTW3NVGDqJnq0CeP1hHrBGRJRBGDQIABAIRRDqWlqqxhwNSRKR37UbaX2DO+3vT0REqcGgQQAQ782wmQ2QJHX+WBTlRedp7GfQICLKGAwaBODo1uNqzM+IiU0IrWvgyhMiokzBoEEAoOr8jJjCrh6N+kb2aBARZQoGDQKgrR6NpnY/vP6QanUQEVHyMGgQgG49GioGDYtJ4sZdREQZhkGDAABub+yck/RuP36sMSV2AJynQUSUKRg0CLKsxI+HV2Npa3djinMAAHWcp0FElBEYNAhefxgKAFFI7/HwvRldHO3RqGePBhFRRmDQIHi6Jl7mWA1pPR6+N2O6gsbB5k6EuzYQIyIi/WLQIHT6YkFD3WETAHA6zLBZDIjICg9YIyLKAAwaFA8adov6QUMQBIyLTwjlPA0iIr1j0CB4uiaC5lgNKlcSNa40FwC3IiciygQMGnS0R0MDQycAMLYkGjTqjjBoEBHpHYMGwRObo6GBoRMAGFd6dC8NRVFUroaIiEaCQSPLKYqCTp829tCIGVWUA4MkwBsIo6HVq3Y5REQ0AgwaWc4XCENWFAgAbBZtzNEwSCJGFUU37qo91KFyNURENBIMGlkuNmxitRggiuruodHduK55GjUHXSpXQkREI8GgkeXcXm1NBI0Z2zVPgz0aRET6xqCR5Y5OBNXGsElMRdcS1+qDDBpERHrGoJHlPBpb2hoT24q8ud0XP1mWiIj0h0Ejy3m82tl+vDubxYCSfCsAHrBGRKRnDBpZTmt7aHQ3rizaq8EdQomI9ItBI4spitJt6ERbczSAo/M0eOYJEZF+6SZovPXWW1i1ahXmzJmDE088Eddddx1qamrULkvXvIEwQuHoUexaGzoBgHFlXWeecCtyIiLd0kXQ+OCDD3DdddehsrISDzzwAH7xi1+gtrYWV1xxBTwejt8PV6srAACwmCQYJO39UYj1aBxq9iIUjqhcDRERDYf2+st78fe//x2jRo3CvffeC0GIbio1evRorFq1Clu3bsXSpUtVrlCfWl1+ANrszQCAglwzcm0muL1BHGzuxPgyh9olERHREGnvn7G9CIfDyMnJiYcMAMjNzVWxoszQ1tWjYdfYHhoxgiBgwuhouODwCRGRPmnzG+YYF110EX7wgx/g6aefxnnnnQeXy4V7770XEydOxOLFi0d0bYNBF1mrT5IkArICURQgHbOFuCQKEEQBBoMARUl8TBCAVk+0R8NuM/V4rSgIEAQBogRIkeQ8NtDjx9YrSSKOG5OPL/c0o67Bo/vP6lhS13CVpMFhq2Rg+/Qrk9sGsH3ppougMX/+fDz44IP46U9/irvvvhsAcNxxx+GPf/wjTCbTsK8rigIKCnKSVaZqfK1emM1GiJKUcL/RIMJqMSE/39br6zo80RUnzjwLbDZzwmNWiwEGgwSrxQSDQU7KYwM93lu9k8YVAAD2N3gy4rPqjcNhVbuElGL79CuT2wawfemii6Dx2Wef4ZZbbsHKlSuxbNkyeDwePPLII7jqqqvw3HPPwW63D+u6sqzA5dL3MeSxf+UHAiH4A+GEx0xGCT5/EO3tChQl8XWCADS1R9tukgR4vYHExxUZ4XAEPn8QwWAkKY8N9Pix9UqSiMljo0Fj32EXGhpdMBmlHtfUK0kS4XBY4XL5EIn0DGV6x/bpVya3DWD7ksHhsA66x0QXQePuu+/GokWLcMcdd8Tvmzt3LpYsWYK1a9fiiiuuGPa1w2F9/yGLTlsRIMsKInJimojIChRZQTisQDkmaQiCEJ+jYTUberxWVqKvkSNI2mMDPd5bvUX5NuTlmNDRGUTNIReOG5036N8bvYhEZN3/OewP26dfmdw2gO1LF20M4AyguroaU6ZMSbjP6XSipKQEdXV1KlWlb4FgRLPnnHQnCAImjIpOCK09xCPjiYj0RhdBY9SoUdi+fXvCfU1NTWhsbMTo0aNVqkrfWrqWtpoMouaHIypjQeMIgwYRkd7oImh873vfw9tvv4277roL77//PjZu3IirrroKNpsN5557rtrl6VJzhw8AYLdptzcjhj0aRET6pYs5Gt/73vdgNBrx7LPP4uWXX4bNZsPMmTNx7733oqSkRO3ydKmlo2tpq4aHTWIqy6NBo6HNh05/SJMHwBERUe90ETQEQcDFF1+Miy++WO1SMkazSz9BI9dmQnG+BU3tfuw77Mb0SqfaJRER0SDpYuiEki/eo6GDoRPgaK9G7WEXhK5Nv469ERGR9jBoZKmjQyfD3/AsnSaMii5r/aa+HR5/qNcbj10jItIeXQydUPK16GjoBAAmjckHAOw90IEv9jT16MEwGkRMG++E3WLssWcIERGph0EjC4UjMtrdXQeq6WToZFypHUaDiEAogqZ2H/Lt5oFfREREquPQSRZqdQegADBKIqwmbe+hEWOQRFSURU/sbWr3qVwNERENFoNGForNzyhwmHU1iTI2IbSxjUGDiEgvGDSyUGyzLqfDonIlQxPbuKup3a9yJURENFgMGlko1qPhzNXXPIfYVuSuziD8wfAAzyYiIi1g0MhCsRUnWuzREITYTUBsVCd2X47FiHx7dDkuezWIiPSBq06yULxHw6GtHg1JEiCKIty+MAAFgiggKHvh84cgAJABlDhtaPcE0djmw9gSu8oVExHRQBg0slCsR6Mg14JOf0jlao6SRAG+YBjV9R0IhiOQRAFWqwk+XxBmk4SKcgfKnTbsrmtHY5tX7XKJiGgQOHSSZWRFQasruoeG1no0YkJhGcFQBMFQJP7/4YgMACgvzAEANHf4EQrLapZJRESDwKCRZTo8QURkBaIgIE+Hm17l2kywW41QFLBXg4hIBxg0skz3+RmSqJ89NLorc9oAAEdaGTSIiLSOQSPLNLuie2gU5mlvxclglRVaAQBHWrhxFxGR1jFoZJlYj0ahBpe2DlasR6PV5UcwxDNbiYi0jEEjy8SCRpGOezRsFiMcNiMUAA3cjpyISNMYNLJMc9fS1sI8q8qVjExZYdc8jRbO0yAi0jIGjSyTCUMnwNHhk8MtnSpXQkRE/WHQyCKKosQ369LzZFAgup+GAKDdE4THp51Nx4iIKBGDRhbx+EIIhqKbXBVqdLOuwTKbJBTlR4d/DjaxV4OISKsYNLJIrDcjL8cEo0FSuZqRG1Mc3SX0YJNH5UqIiKgvDBpZJBNWnHQ3uitoHGn1xrcoJyIibeGhalkkPhE0Q4JGQa4ZVrMBvkB4xKtPBKHvXVIVRRnRtYmIshmDRhZpzpAVJzGCIGB0cQ72HuhAfePwh08iAPz9nGJrMRug/4EmIiJ1MGhkkUxZcdLdmK6gUdfgHlbPgyAI8PtD2LGvtdfTYI0GEdPGO2G3GNmzQUQ0DJyjkUUyZQ+N7soLcyCJAtzeEA6MYPVJ96Ppu994FD0R0cgwaGSRTOzRMBrE+OqTz3c3qVwNEREdi0EjS/gCYXT6wwAyq0cDACrKHQCiQYPDG0RE2sKgkSVivRk5FgOs5syamjO6KAcGSUBzhx/7j7jVLoeIiLph0MgSmTg/I8ZoEDG2JBcA8PGuRpWrISKi7hg0skQmzs/obsKo6PDJJzsbOHxCRKQhDBpZItM26zrW2BI7LCYJzR1+7K5vV7scIiLqwqCRJWI9GkUZOHQCAAaDiLlVxQCATV8eUrkaIiKKYdDIEs0Z3qMBAItnlAMAPt3VhM5+dvokIqL0YdDIEpk+dAIA40rtGFtiRzgiY8vXR9Quh4iIwKCRFULhCDo6gwAyc9VJjCAIWDp7FABg85eHOCmUiEgDGDSyQIsrAAAwGUXYrUaVq0mtRdPKYDSIONDUyUmhREQawKCRBbrvodHfceiZIMdqxEkzygAAGz+qU7kaIiJi0MgCmb6HxrHOXDgOAoCvqltwoGn4x8cTEdHIMWhkgZYOHwCgKM+qciXpUVpgiy91fZ29GkREqmLQyALxpa0Os8qVpM/ZiyoAAB/taEBzV9AiIqL0Y9DIAtk2dAIAleUOTBtfgIis4JV/1apdDhFR1mLQyAKxHo0iR3YMncSsXDoRAPDB10dwoJFzNYiI1MCgkeEisoK2ruWt2dSjAUR7NeZNKYEC4KVN1WqXQ0SUlRg0MlyHJwBZUSCJAvLsJrXLSbuVSyZAEgV8Vd2Cnfta1S6HiCjrMGhkuNau3gynwwwxw/fQ6E2p0xbfLXTNW3sQjsgqV0RElF0YNDJcm/voZl3Z6vxTJsBuNeJQcyfe3npA7XKIiLIKg0aGa83S+Rnd2a1GXHRqdGLo+vdq0e4JqFwREVH2YNDIcK1dS1uzZbOuvpx8fDkqyx3wByNY+85etcshIsoaDBoZrtXd1aORxUMnACAKAi79t8kQAGzZ3sAD14iI0oRBI8O1ZuFmXX2pLHdgSdfE0Gfe+AYRmRNDiYhSjUEjgylK9u6h0ZeVSycix2LAgaZOvP3ZQbXLISLKeAwaGcwXjCAUkSEAcOZmzzkn/bFbjfEdQ9f/qwYdnZwYSkSUSgwaGczjDQEA8nPNMEj8qGOWzBqFirJc+AIRrH2HO4YSEaUSv30ymMcXDRrZPhH0WKIYnRgKAO9vO4yaQx0qV0RElLkYNDKYxxcEABTlWSAIwjE3lYtT2cRReTjl+HIAwLpNNVAUReWKiIgyE4NGBvP6wwCA3BwTPP5Qwq0zEEa2r7lYuXQiTAYR+4+4cbCpU+1yiIgykkHtAih1OruGTgKhCL7c25zwmM1iQEW5AwIyp2tDENDVU9OzTb31WDhyTDj1hNF445N6fLa7CWcuGAsh27t6iIiSjD0aGczdNRnUajIgGIok3DLtcDFJEiCKIty+cI/eG48/hEgfrzt7UQUMkoDGNh+OtHrTWjMRUTZgj0YGc3f1aNitRpUrST1JFOALhlFd34FgODFWGA0ipo13wm4x9ujZyLebceLMcmz+4hC+qm5BeWFOOssmIsp4w+7RCAaDyayDkiwUlhEIRr9wsyFoxITCco/em1C4/96bb80bA0EAGlp9aHdzXw0iomQadtBYsmQJ7r//fhw6dCiZ9VCSdPqjvRkWkwSTUVK5Gm0ryLVgXGkuAPAMFCKiJBt20DjttNPw9NNP44wzzsC1116LLVu2JLMuGqFOX3TFSQF3BB2UqRUFAIDqQ64Be0CIiGjwhh00Vq9ejU2bNuHGG2/Erl278MMf/hBnn302nnnmGXg8nmTWSMMQ69HIZ9AYlNHFObBbjQiFZew74la7HCKijDGiVSd5eXm46qqr8NZbb+HBBx9EeXk57rnnHixZsgR33XUXqqu5vbNaOv2xHg3uCgocXfra18ZlgiBg8tg8AMDuunb1CiUiyjBJWd4qCAJOP/103HzzzZg/fz68Xi+effZZrFixAtdffz1aWlqS8TY0BLE9NDh00v/S1+4blx03Jg+iALS4/Gj3cFIoEVEyjHh5azgcxuuvv441a9bgiy++QHl5OW6++WZ8+9vfxj//+U88/PDDuPXWW/Hkk08mo14aJA6dHNXf0tfuG5dZTAaUF+XgYFMn9h12Y/Yk/t4REY3UsINGQ0MDnn/+eaxduxbNzc2YN28efve73+GMM86AKEY7Si677DKUlpbilltuSVrBNDjdJ4MGAn1tV5VdYktfuzMZEzv1Kstzo0HjiBuzjitMZ3lERBlp2EFj2bJlkCQJy5cvx/e//31MnTq11+eNHTsWhYXJ+Qt77dq1ePrpp1FbWwu73Y5Zs2bhkUceScq1M4miKPB269FoCHDHy8EaU2KHKApwdQbR5g6grJB72hERjcSw/xa99tprcckll8DpdPb7vKlTp+Ltt98e7tvEPfDAA/jzn/+Mq6++GrNmzUJHRwf+9a9/jfi6mcgXiEBWopMfHTkmNDQzaAyWySBhTHEO6ho82HfYjTLuFEpENCLDDhqjRo3q8wCq9vZ2vPvuuzj//POHe/kE1dXV+MMf/oDHHnsMJ598cvz+M844IynXzzSx+Rk5FiMkkYeEDdX4stxo0DjixsLppWqXQ0Ska8NedXL77bejvr6+18cOHDiA22+/fdhFHWvdunUYO3ZsQsigvsVWnOTasmfr8WQaU2KHQRLg8YXQ0uFXuxwiIl0bdo9Gb8duxwQCAUhS8ra9/vLLLzF58mQ89NBDeOaZZ+B2uzF79mzccccdfc4NGSyDQd8H2EqSCMgKRFGI9154A9GJoLk2IwRBgCgBUiSxZ0Ps2keit8cGeny4jw31tbFJxaIoprVeSZQwqig6fHKgyQNBFGAwCFCU5PYOSZKY8N9Mw/bpVya3DWD70m1IQePQoUM4ePBg/Nc7duxAIJC434Df78eLL76I8vLy5FQIoKmpCdu3b8eePXtw5513wmg04sEHH8QVV1yBN954Aw6HY1jXFUUBBQX6H4P3tXphNhshdoW7QDgaAgscVhgMEqwWEwyGxG21rRZDn48N9PhwHxvuay0WY9rrnTgmH3UNHtQ3dsJqMSE/39bjPZPF4bCm7NpawPbpVya3DWD70mVIQWPdunV48MEH47sq3nnnnT2eE+vpuOOOO5JTYdc1vV4vHnjgAUyaNAkAMH36dJx++ul44YUXcNVVVw3rurKswOXS90TJWI9MIBCCv6sno8Md7e63GEWEwxH4/EEEg4nLOgVF7vOxgR4f7mNDfa0oirBYjPD7Q2mvtyQ/uqNqQ6sXDS0emEQF/XTiDYskiXA4rHC5fIhEMu98FbZPvzK5bQDblwwOh3XQPSZDChpnn302Jk2aBEVRcOONN+Kmm25CRUVFwnNMJhMmTZqEMWPGDOXS/crLy0NRUVE8ZABASUkJJkyYgL17947o2mGdH6AVnY8rQJYVROToN6Gna46G3WaEoiiQI4g/FiMrSp+PDfT4cB8b+mujn40sy5AVMa31mo0SCvMsaOnw4+vqFpQX2PodLhyJSETW/Z/D/rB9+pXJbQPYvnQZUtCYOHEiJk6cCCB6qNqpp56KgoKClBR27Pv2dhy9oijxcXw6KrZZl93KyaAjMaY4Jxo0altwxryxapdDRKRLw/6WvuCCC9ISMgDg1FNPRXNzM3bv3h2/r6GhATU1NaiqqkpLDXoRCssIdO1+yVUnIzOm2A4A2LW/jUfHExEN05B6NB588EGsWrUKpaWlePDBB/t9riAIuPbaa0dUXMwZZ5yB6dOn4/rrr8dPfvITmEwmPPTQQ3A6nfj3f//3pLxHpojtoWE0iDAZk7fyJxs5HWbYLAZ4/WHsrm/DtPH9b05HREQ9DTloLFmyJO1BQ5IkPP744/jVr36FX/7ylwiHw5g/fz7uv/9+2GypWw2gR7FhkxwLt84eKUEQMLo4B3vqO7B9H4MGEdFwDOnbaNeuXb3+fzoUFhbi/vvvT+t76lF8V1DOz0iK0UV27KnvwI59rQAmql0OEZHucCZlhun0x3o0GDSSYVRRdJ+VuiNuuL1BlashItKfYQeNQCAAj8eTcN+GDRtw33334YMPPhhxYTQ8se3Hc6wcOkkGm8WA8kIbFAC76trVLoeISHeGHTRuueUW3H333fFfP/XUU7jpppvwxBNP4Morr8SmTZuSUiANTfcD1Sg5qsZFV1dFh0+IiGgohh00tm3bhlNOOSX+66effhrnnnsuPv30U5xxxhl48sknk1IgDU18Mih7NJKmalw+AAYNIqLhGHbQaG1tRWlp9Ajt+vp61NfX49JLL4XdbsdFF12EPXv2JK1IGhxFUeBlj0bSHTcmD5IooKndj8Z2n9rlEBHpyrCDhsVigdvtBgBs3boVNpsNM2fOBACYzWZ4vfo+Q0SPfIEIZCW6LbnNzB6NZLGYDJgwKnpw3072ahARDcmwg8bkyZOxZs0afPPNN3j22WexcOFCCNGDN3D48GEUFRUlrUganNj8DJvZAFFM7pHm2S62h8aOfW0qV0JEpC/DDhrXXHMNPvnkE5x//vnYtWsXfvSjH8Ufe/fddzF9+vSkFEiDd3TFCYdNkm16ZTRo7NzfBjlFh6sREWWiYfevL168GBs2bMD27dsxdepUjB179NCpRYsWYerUqUkpkAbv6B4aHDZJtspyB8wmCR5fCPUNHlSU5apdEhGRLozoG2n06NEYPXp0j/svueSSkVyWhineo8GJoElnkERUjc3HV9Ut2LG/lUGDiGiQRvxP35aWFhw8eBCBQKDHY/Pnzx/p5WkI4j0aXNqaEtPGO6NBY18bzl5YoXY5RES6MOxvpMbGRtx666346KOPejymKAoEQcDOnTtHVBwNDTfrSq1p46Mbd+2pb0coHIHRwNNxiYgGMuyg8b//+7/YuXMnbr75ZlRVVcFkMiWzLhoGb1ePho1zNFJidFEOHDkmuDqD2HvQhakVBWqXRESkecP+Rvr4449x6623YuXKlcmsh4YpIsvwByMAGDRSRRAETBtfgA+3N2DHvlYGDSKiQRj28lZBEFBeXp7MWmgEYr0ZoiDAbGSXfqpMq+B+GkREQzHsoHHWWWfhnXfeSWYtNAKxM05sFkN84zRKDkGI3YT4fhr7jrji4Y6IiPo27D72s88+G7/4xS+gKApOO+005Ofn93gON+1Kn/iuoBw2SSpJEiCKIty+MAAFJpOEUqcVDa0+fL63GYtmlIH9R0REfRv2t9Lll18OAHjmmWewZs2ahMe46iT9um8/TskjiQJ8wTCq6zsQDEfnwBQ6LGho9eHD7Ucwe1IR7BYjFO4WSkTUq2F/K61evTqZddAIdR86oeQLhWUEQ9GgUVJgxY59bahv9KhcFRGR9g37W+mCCy5IZh00Qhw6SZ8ypw2CALg6g2h1+WHnviVERH0a9mTQ7mpqarB161YeDa+ieI8Gh05SzmSUUJRnAQB8U8fVJ0RE/RlR0Fi/fj2WLFmC5cuX49JLL0VtbS0A4Cc/+QlefPHFpBRIg8MejfQqL8wBAOyqa1e3ECIijRt20Ni4cSNuu+02TJs2Lb76JGb69OnYuHFjUgqkgSmKEj/nxGZmN346lBfaAAC769p5bDwRUT+GHTQee+wxXHjhhXjkkUdw8cUXJzw2YcIE7N27d8TF0eB4vCHIcvTLzsoejbQoyrfCIAnw+EI4wEmhRER9GnbQqK6uxvLly3t9LD8/H+3t7cO9NA1Rmzt6cq7FJEESuVlXOkiiEB8+2b6vVeVqiIi0a9hBw2q1wu129/pYQ0MD8vLyhl0UDU2b2w+A8zPSbXRxNGjsqGXQICLqy7CDxgknnIA1a9b0ulHRunXrsGDBghEVRoMX69HgipP0GlUUDRq7u46NJyKinoYdNK699lp88cUXuOiii/D0009DEAS88cYbuPrqq/Hpp5/i6quvTmad1I929miooiDXDIfNhGBYxt6DLrXLISLSpGEHjZkzZ+Lxxx+H1+vFr3/9ayiKgkcffRS1tbV47LHHMHny5GTWSf2I92hw46i0EgQBVePyAQA7OE+DiKhXI/on8KJFi7Bx40bU1dWhubkZBQUFqKysTFZtNEjtHDpRTdW4fHyyqxFf17Zi5dKJapdDRKQ5w/pmam1txfPPP49PP/0UjY2NAICSkhIsXLgQ//7v/46CgoKkFkn9a+XQiWqmjo8eG7//iBvtngDy7WaVKyIi0pYhfzNt2bIF119/PTweDyRJQkFBARRFQW1tLT744AP88Y9/xIMPPoj58+enol7qBXs01OPIMaGy3IHawy5sq27BKbNGqV0SEZGmDGmORmtrK2688Ubk5ubid7/7HT799FO89957eP/99/Hpp5/it7/9LaxWK2644Qa0tfEMiHQIhiLwdu0KamXQUMWs4woBAF9Wt6hcCRGR9gwpaLz00kuQZRnPPfcczjrrLFit1vhjVqsV3/72t/Hss88iHA7jpZdeSnqx1FO7JwgguoGUyZiUM/JoiGZNLAIQ3bgrFJZVroaISFuG9M303nvvYeXKlSgrK+vzOaNGjcKFF16If/3rXyMujgbW0RkdNrGaDRAE7gqqhnFlucizmxAIRrC7vl3tcoiINGVIQaOmpgZz584d8Hnz5s1DTU3NsIuiwWt3R3s0OBFUPaIg4PgJseGTZpWrISLSliEFDZfLBafTOeDznE4nXC5uYJQO7Z7YHhoMGmqadVx0+OTLvc297pZLRJSthhQ0gsEgjMaBN4UyGAwIhULDLooGLx40OBFUVdPHO2E0iGhq96Oep7kSEcUN+duppqYGkiQN+BxKj9hk0BzuCqoqs0nCjEonPt/TjK3fNGFcaa7aJRERacKQg8btt98+4HMUReHExDTh0Il2zKsqiQaN3U24YMkEtcshItKEIX07rV69OlV10DB1uBk0tGLWcYWQRAGHmjtxuKUT5YU5apdERKS6IX07XXDBBamqg4YpNnTCORrqs1mMmDbeiW01Lfj0myaccyKDBhERd3jSsYgsw9XJ5a1aMreqGACw9ZtGlSshItIGBg0dc3WGoAAQBMDCHg1NOGFSEURBQF2DBw2tXrXLISJSHYOGjsV2BXXkmCBy8q0m5NpMmFYZPb14y/YjKldDRKQ+Bg0di83P4NHk2rJ4WnSL/o92NHDzLiLKegwaOtbRtbQ1j0FDU06YXASTQURDmw/7jrjVLoeISFUMGjrW0dWjwaChLRaTAbMnRbck5/AJEWU7Bg0da++MDZ2YVK6EjrVoenT45OOdjZC7NrA79kZElA24VEHHOHSiXTMqnbBbjXB1BvHJrkbM6DrdtbscK7eNJ6LMx6ChY+3dhk7CobDK1VB3RoOE+VNL8M5nB/H6h3WIyMoxj4uY3kv4ICLKNBw60bHY8lauOtGmxTOiwyd1jW60uwMIhiLxWygsq1wdEVF6MGjolKIo3SaDco6GFpUX5qCkwApFAaoPdqhdDhGRKhg0dKrTH453x3OOhnZNqYhu3rXnQAf31CCirMSgoVOxM05yLAYYJH6MahGE2O3YVSXRxyvLHTAaRHh8IRzhluRElIX4DaVTsaDhyOGwiVokSYAoinD7wvD4Qwm3zkAYMqKTPivLHQCAPfUcPiGi7MNVJzrl8jJoqE0SBfiCYVTXdyAYjiQ8ZrMYUFHugAABk8bkYXd9O+oaPPAHw7CY+GNHRNmDPRo6xR4N7QiF5YQVJcFQBOHI0VUlhXkWOB1myIqCmkMuFSslIko/Bg2divVo5DFo6MKkMfkAosMnnBRKRNmEQUOnXJ0hAAwaelFZnguDJKCjM4imdp/a5RARpQ2Dhk5x6ERfTEYJFWW5AIBv6trVLYaIKI0YNHSKk0H1Z8q46J4a+4+44Q1wy3giyg4MGjrFHg39KcyzoDjfAlkBvtnfpnY5RERpwaChU5wMqk9VXb0aO/e3IRLheSdElPkYNHQoEIwgGIp+SfGcE32pKMuFxSTB6w/jq+oWtcshIko5Bg0d6ujqzTAZRJiNksrV0FBIooDJY/MBAJs+P6huMUREacCgoUPd52cIsUM1SDcmj82DIAB7D3Rg32Fu4EVEmY1BQ4fcXUEj18ZhEz2yWYwYXxY9/+Tv79eqXA0RUWoxaOhQByeC6t60yuik0He21qPTH1K5GiKi1NFl0Ojs7MSSJUtQVVWFbdu2qV1O2rnjQydGlSuh4Spz2lBelINAMIJ/fXlI7XKIiFJGl0Hj4YcfRiQSGfiJGSq2/TiHTvRLEAQsPWEUAOCNj+sRkbnUlYgyk+6CRnV1NZ599llcf/31apeimg7uCpoRFkwtRa7NhOYOPz7f3ax2OUREKaG7oHHPPffgkksuQWVlpdqlqCY+dMIeDV0zmyR8+6TxAIB/fFwHQRDiNyKiTGFQu4CheP3117Fr1y78/ve/x/bt25NyTYNBd1krvitogcMMSRIBWYEoCpDExC8osetLS5QAKTL4x0by2mReVxSjn40oirqodyjXNRlEiKKEhdPK8Ne396L6kAvbalswYXQeAMBmNsAg6jtwSJKY8N9Mk8nty+S2AWxfuukmaPh8Pvz617/GTTfdBLvdnpRriqKAgoKcpFwrnTy+6ByNseV5yM21wtfqhdlshCglbt5ltRhgMEiwWkwwGORBPzaS16biuhaLUVf1Dua6NosBoYiMwy2dqKoowPaaFrz6Xi1WnDwBRoOIKRVOFBTYerxOjxwOq9olpFQmty+T2wawfemim6Dxhz/8AYWFhbjwwguTdk1ZVuByeZN2vXQIR2S4vV3LISMRuN0+AEAgEIL/mBNBBUVGOByBzx9EMBgZ9GMjeW0yryuKIiwWI/z+kC7qHep1I2EZobCMqrH52F7Tgr0HOlB/uANF+Vb4/EG0tytQlB4v1Q1JEuFwWOFy+TLyXJdMbl8mtw1g+5LB4bAOusdEF0Hj4MGD+OMf/4iHHnoIHo8HAOD1euP/7ezsRE7O8HomwmF9/SFrcwcARLvmzUap6w+RAFlWEJETv5VkRYGiKJAjGNJjI3ltcq8b/WxkWYasiDqod4jXRfT+vBwjRhfl4GBzJ76ubcUps0ZBkRWEw9Fr6F0kIuvu52woMrl9mdw2gO1LF10EjQMHDiAUCuE//uM/ejz2/e9/H7NmzcKLL76oQmXp54rvCmqEyEmDGWNaZQEONnei+mAH5k8tVbscIqKk0UXQmDp1Kp566qmE+3bu3InVq1fjzjvvxMyZM1WqLP1cXNqakcqcNhTkmtHmDmDX/jYsnMawQUSZQRdBw+FwYOHChb0+Nn36dEyfPj3NFaknfqCajbuCZhJBEDBtfAHe33YE22tbEAxHAPAzJiL908baFxo09mhkrvHlDuRYDPAFIvjgqyNql0NElBS6DRoLFy7EN998k1XDJgDg7tp+nEEj80iigJkTCwEAb35aj1A4e7fZJ6LModugka06uCtoRps4Og92qxGuziA2fcHD1ohI/xg0dIZDJ5lNEgXMOi7aq/H3LfsQCLFXg4j0jUFDZ9zx5a0MGplq8th8OB1mtHuCeOPjOrXLISIaEQYNnYmd3JrHHo2MJUkizj05emjghg/r0OEJqFwREdHwMWjoiKwo8Hg5GTQbzJlcjAnlDgRCEbzyXq3a5RARDRuDho54/eH4dta53EcjowmCgItPnwQA2PTlIew74lK5IiKi4WHQ0JHYipMciwEGjRz/S6kzeWw+Fk4rhaIAf9qwC+EMPPyJiDIfv610hBNBs893Tp8Eu9WI+kYPXv+IE0OJSH8YNHSES1uzjyPHhO90DaG8+v4+1Dd6VK6IiGhoGDR0JH7OCYNGVlk0vRSzJhYiHJHx0Mvb4PWH+n2+IAh93oiI0o1BQ0fiPRqcCJpVBEHAlSumodBhRmObD0/+fWf8/mNvEQAef6jPG7f/IqJ008XprRTFHo3sZbcacc0FM7H6ma34fE8z1ry5G+edUpnQSyGKAsKygl37WhEK95w4ajSImDbeCbvFCEVR0lk+EWUxBg0dccUOVONk0KxUWe7A5WdNwZN/34l/bj2Ajs4gZk8qij9usxhQUe5AOKwgyK3LiUgjOHSiI5wMSicfPwoXLJkAAPh0VyO27mpEIBhGMBTh8lci0iQGDR3h0AkBwLK5Y3DC5GhPxud7mvHRjgbIModCiEibGDR0hJNBKWZuVQnmTykBAOyu78A7nx9EKMzhEiLSHgYNnfAHwwiGol3j7NEgAJg6vgCnnjAKkijgYFMn1m+ujfd6ERFpBYOGTri6DlMzGUSYjZLK1ZBWjCvNxb8tGAuzUUJTux+/f/FLtLr9apdFRBTHoKET3edncOMl6q4434pvLx6HPLsJbe4A/vZeLY60eNUui4gIAIOGbvCcE+pPrs2ElUsnYHy5A8GwjLe2HsDBpk61yyIiYtDQi46uiaB5nJ9BfbCYDbj6ghmoKM2FLCt45/ODONjEs1GISF0MGjrhjg+dcMUJ9c1oEHH6vDEYV2qHLCt49/NDaGr3qV0WEWUxBg2diO0KyqETGogkilgyaxRGF+cgIit457OD8Hj7P4iNiChVGDR04ugeGgwaNDBRFLBk1igU5JrhD0bw9mcHej3/hIgo1Rg0dMLN7cdpiIwGEcvmjobVLKHdE8SW7UcgCOi68Qh5IkoPBg2d6OjkrqA0dDkWI045fhQAYHddO77Y0wy3L8wj5IkobXh6q064u8bY2aORHWI9D4DQ4/6hKiu0YeYEJ7bVtOKZf3yDYEiGyZj4bwweIU9EqcKgoQPhiAyPr2syKINGxpMkAaIowu0LA0j80hdFAcOZaTHruCI0tPnQ2ObDps8PYukJo5JSKxHRQBg0dCAWMgQBsFs4dJLpJFGALxhGdX0HgscclGazGFBR7oCAoXVtiKKA0+aMxtp3qrG/wY26BjfGleYms2wiol5xjoYOuLrtCiqKnLSXLUJhGcFQJOEWjgx/5UhhngXL5o4BAHy0oxHBEGdlEFHqMWjoAI+Hp2T51vyxcOSY4AuEsa2mVe1yiCgLMGjogLuTE0EpOYwGEYunlwEAdu5r40ZeRJRyDBo6cHRpK4MGjdzYEjvKCm2QFQWf7WlSuxwiynAMGjrAzboomQRBwLyqYgDAvsNuNPMsFCJKIQYNHTg6GZRzNCg5nA4LJo52AAA+/aaJe2cQUcowaOiAK7ZZF4dOKIlOmFQESRTQ2ObDviNutcshogzFoKEDrk4OnVDy2SxGTK90AgA+2dk4oqWzRER9YdDQARfnaFCKTK90wmKS4OoM4r0vD6tdDhFlIAYNjVMU5ehkUA6dUJIZDSJmTyoCAPzj4zr4AmGVKyKiTMOgoXG+QBjhSHSiniOHk0Ep+Y4bnYe8HBM8vhBe/6hO7XKIKMMwaGhcbCKo1SzBaJBUroYykSgKmDelBEC0VyO2bwsRUTIwaGhc93NOiFJlfHkuKspyEQhF8Nr7+9Quh4gyCIOGxrm4KyilgSAIOPfkSgDAu18cRCM38SKiJGHQ0DiuOKF0mTw2HzMqnYjICtZvrlG7HCLKEAwaGne0R4MTQSn1Ljr1OADAhzsaUNeQuImXIAh93oiI+sKgoXFuL09upfSpKMvFwmmlAICXNlXH748A8PhDfd4iKtVLRNpnULsA6h8ng1K6XXBKJT7d1Yiva1qxa38bpo53wu8PYce+VoTCPXcPNRpETBvvhN1i5JkpRNQDezQ0LjZHI489GpQmJQU2LJ09CgCw9t3qeHgIhWUEQ5Eet97CBxFRDIOGxvHkVlLDOSdVwmyUUHvYha27m9Quh4h0jEFD41yco0EqyMsx4Yz5YwEA6zZVIyJzSISIhodBQ8NC4Uj87AkGDUq3sxeOg91qxOEWLz7ecUTtcohIpxg0NCy24kQSBdjMnLdL6WU1G7BicQUAYMOW/TxGnoiGhUFDw7pv1sW9CkgNp80ZjUKHBe2eIHbUtqpdDhHpEIOGhnEiKKnNaJBw/ikTAABf7m1GIMgdM4hoaBg0NMzVyYmgpL4TZ5RhVFEOAiEZX1W3qF0OEekMg4aGxYdOuFkXqUgUBZy/JHrg2jd1bfGeNiKiwWDQ0DCe3EpaMbXCiTHFOZAV4DPuq0FEQ8CgoWE8uZXSSRBit2MPTYs+vnB6KQQAdQ0eNLR6Va2ViPSDQUPD3JwMSmkiSQJEUYTbF+5xYFpnIAwZQEGuBZPG5gEAPt3VxHNNiGhQuDmDhsV2BeU5J5RqkijAFwyjur4DwXDiyhKbxYCKcgcECJh1XBFqD7nR4vKj9rALE0blqVQxEekFezQ0jCe3Urr1dnBa9426rGYDZkxwAgA+293MTbyIaEAMGholK0p8Z1DO0SAtmTq+ADkWA7z+ML6u4SZeRNQ/Bg2N6vSFIHeNgXOOBmmJQRIxt6oYALC9thVuL5e7ElHfGDQ0KjY/I8digEHix0TaUlGWizKnDRFZwZaveeAaEfWN32AaFd9Dg8MmpEGCIGDBtBIIQnS563aeg0JEfWDQ0KhYdzQngpJW5dvNmFpRAAB46Z29CIV5DgoR9cSgoVHs0SA9mHVcEWwWA5o7/Nj4UZ3a5RCRBjFoaJTLy826SPuMBhELp5UCAP7+wT40d/hUroiItIZBQ6PaPdGgkc8eDdK4CaMcOG5MHoJhGc+8sXvIO4b23PL86I2I9E8XQWPjxo245pprsHTpUsyePRvnnHMOnn32Wchy5m4W1NEVNPLsZpUrIeqfIAi4eNkkGCQBX1W34IMhrEKJAD22PO9+46wPIv3TxRbkf/rTnzBq1CjceuutKCwsxEcffYR77rkH9fX1+O///m+1y0uJDk8AQHTCHZHWlRXacP4pE/DSu9V47q09mDbeieICa7+vEQQBfn8IO/a1IhTu+Y8Go0HEtPFO2C1GnqtCpGO6CBqPPPIInE5n/NeLFi2C1+vFmjVr8F//9V8wmTJveKE9HjQyr22Umc5aOA6f7mrEviNu/GnjTtz8nRMG9brYtudElJl0MXTSPWTETJ06FYFAAO3t7ekvKMUishzffpxDJ6QXkijiyuVTYTSI+LqmFRu37Fe7JCLSAF30aPRm69atyM/PR2Fh4YiuYzBoL2u5XEEoAERBQIHDDLGfSXGSJAKyAlEUIImJzxO7JtSJEiBFBv/YSF6bzOuKYvSzEUVRF/UO+boQ4u0D5EG9VottkUQBgijAYBBQUe7Apf9WhT9t2Im171Rj7rRyjC7sfQhFEACh68/tsX92j72uomhvYqjUtWOvlIE792Zy2wC2L910GTS2bduGdevW4dprr4UkScO+jigKKCjISWJlydHkjk4ELXCYUei0D/h8X6sXZrMR4jG/F1aLAQaDBKvFBINBHvRjI3ltKq5rsRh1Ve9gryt1hVyLxTjo12qxLUaDCKvFhPx8GwDggmWTUH3Yhc2fH8Svn/oYv7lhCUr6+DkLyl5YrSYYjANfV6scjv7nouhZJrcNYPvSRXdBo6mpCTfccANmzpyJq666akTXkmUFLpc3SZUlT/3hDgCAw2ZCW1tnv8+N9cgEAiH4A+GExwRFRjgcgc8fRDAYGfRjI3ltMq8riiIsFiP8/pAu6h3qdSNdEyD9/lDCCiq9tcVklODzB9HeriA2Z/N735qEmgPtONDUif95bAt+/v15sFkS/7oRBMDnD8HnC/Y6R6O362qJJIlwOKxwuXyIRDJrBVwmtw1g+5LB4bAOusdEV0HD7XbjqquugsViwR/+8AcYjSPfzCrcy2x3tbV2+AEAeTmmAeuLjqoIkGUFETnxb2NZUaAoCuQIhvTYSF6b3OtG2y7LMmRF1EG9Q7wulHj7uj9Hb22JyAoUWUE4rMRXhxglETddcgLu/ssnONDowe9e/AI/uWgWzKajvW6CIEDp+nM72OtqUSQia/LvkWTI5LYBbF+6aGMAZxACgQB+/OMfo7m5GU888QQKCgrULilluOKEMkFRngW/vHIRLCYJu+ra8X8vfgHfMb1uRJT5dBE0wuEwfvKTn2DXrl144oknMHr0aLVLSql2btZFGWLimHzc8p0TYDVL2H2gA7957nO0uQNql0VEaaSLoHHXXXfhnXfewdVXXw2/348vvvgifvN4PGqXl3Ts0aBMMmlsPm79zhzYrUbsO+LGnX/+BLvr29Uui4jSRBdzNN577z0AwG9+85sejz311FNYuHBhuktKKW4/TpmmoiwXP//+XDy4bhsONHXi/3v2cyxfXIHT5o5RuzQiSjFdBI23335b7RLSqr2TPRqUeUoKbLjjsnn48+u78NGOBvztg3349JtGLJhWijweHkiUsXQxdJJNZFmBq7Pr5Fb2aFCGMZsk/Oe503HN+TOQazPicIsXr/6rFlu/acrIZYZExKChOS5vEIoSXbbqsPFfeZSZ5k0pwT1XLcKcqmIoALbXtuK1LfvR3LW0e7B4vDyR9uli6CSbxOZnOGwmiL1sy0yUKXJtJlzx7alw5prx3leH0eEJYuOH+zFjQiGOnzjw0QIRRDc7643FbMDw9wwmomRi0NCYNh4PTxmot16G2F3jyx1wOiz4eEcD9h1xY1t1Cw40enDanL6Xsfd3xDyPlyfSFgYNjenoChp5nAhKGSIsK+jspedBFIX4UXIWk4Qls0dh3BE3PtregDZ3AK++VwtHjglLZ/UdOHjEPJH2MWhoTGzohCtOSE8E4eh2+N3vAwBvINxrz4PNYkBFuSN+ii0AjC/LRWmBFe99dRiHW7z484ZdaGzzYeWSCZx7QaRTDBoa086hE9IZSRIgiiLcvjCAo0MVgiggpHihKL33PJiMvc9Ft5oNOH3eGHxV3YKv9rZgw5b9cHmCuPzsKkgi568T6Q2DhsbEtmfmZl2kF5IowBcMo7q+A8FwJOF+Z74NxfmWhF6LwRAFAQumlmLmhEI89+YevLftMLyBMK4+bzoMgzwxkoi0gT+xGtPaFTQKHQwapC+xXovut/AI98ZYNL0M162cCYMk4rPdTXjitR2QeznplYi0i0FDY1pd0X0EnA6LypUQacMJk4px3YUzIYkCPt7ZiKf+sYurSYh0hEFDQ/zBMDr90WO0nbkMGkQxx08sxH+eOx2CAGz+8jA2fLhf7ZKIaJAYNDSk1RUdNrGaJdgsnD5D1N28KSW49IzJAIC/vluNr6qbVa6IiAaDQUNDWt0cNiHqz2lzxuC0OaOhAPjLxl3xydNEpF0MGhoS69HgsAlR375z+iRMrShAMCTj7a0HRjzhlIhSi0FDQ2ITQbnihKhvBknEf547Hbk2I9rcAXy6q1HtkoioHwwaGtLSFTQKOHRC1K88uxnfP2sKAGB3fQfqGtwqV0REfWHQ0JDY0Al7NIgGNqWiAMcfFz3l9cPtDfAHeeYJkRYxaGjI0aET9mgQDcacycXIyzHBH4xwCIVIoxg0NEJRlPiuoBw6IRocgyTixJllEADUHHLhQKNH7ZKI6BgMGhrh9oUQCssQABTwnBOiQSvOt2JaZQEA4OOdjQiHuQqFSEsYNDQiNmzisJtgNPBjIQKOHj8vCMIxt8TnHT+xCDkWAzy+EL7Yy428iLSE32ga0dLBPTSIuut+/LzHH0q4dQbC6N5vYTSImD+1BADwVXULGlq96hRNRD1wn2uNiO0KyhUnRFF9HT8PADaLARXljoTj58eW2DG6KAcHmzuxbnMNbrnkhHSXTES9YI+GRvDUVqLeDfb4eUEQMH9qCQQB2FHbih37WlWoloiOxaChEfHtxxk0iIbNkWPCtPFOAMDz/9wDWeZx8kRqY9DQiNiuoM5cDp0QjcQJk4pgNUuob/Rgy/YjapdDlPUYNDSisc0HACgpsKpcCZG+WcwG/NuCcQCAdZtrEAhxx1AiNTFoaIDXH4LHFwLAoEGUDEtnj0ZhngVt7gDe+KRe7XKIshqDhgY0dPVm5OWYYDFxIRDRSBkNIi5aOhEAsOHD/ejwBFSuiCh7MWhoQENbdM1/KXsziJJmwbRSVJbnIhCM4JX3atUuhyhrMWhoQGNrbH6GTeVKiDKHKAi4eNkkAMDmLw/jcEunyhURZScGDQ2IDZ2UOtmjQZRMk8fmY9bEQsiKgnWba9QuhygrMWhoQGN86IQ9GkTJtnLpRAgAtn7ThJpDLrXLIco6DBoa0MClrUQpM6bEjsUzygAAL727F4rCTbyI0olBQ2Vc2kqUeuefUgmDJGBXXTu213JrcqJ0YtBQGZe2EqVeUZ4Vy+aMAQC89G41ZPZqEKUNg4bKuLSVKD2WL66A1SyhrtGDj3c2qF0OUdZg0FAZl7YSpUeuzYSzurYmf3lzTa8nwBJR8jFoqIxLW4nS59/mj4Mjx4Smdj82fXFI7XKIsgKDhsq4tJUo+QQhdhMSbhazAeedVAkA+Nv7tfAHwypXSpT5GDRUpCgKjrRGgwZXnBAlhyQJEEURbl8YHn+ox23ulGIU51vh8oZ44BpRGnCZg4ra3AF0+sOQRAHlhezRIEoGSRTgC4ZRXd+BYLjnEfFGg4jlJ1bgzxt24fWP6nDaCWPgyDHFH+c+G0TJxR4NFdU1egAA5YU2GA2SytUQZZZQWEYwFOlxkxUF86aWYmyJHf5gBGvf3ZvQ49EzmhDRSLBHQ0X1DW4AwNiSXJUrIcoekiggEIpgblUJ6hs9eP+rwygpsMLpsMBoEDFtvBN2i5E9G0RJwh4NFcV6NMaV2lWuhCj7FOdbMa7UDgXAlq+PIBAMIxTmkleiZGPQUFF9Q1fQKGHQIFLD3KpiiIKAwy1e1HcFfyJKLgYNlfgCYTS2R/fQGFvKoRMiNeTaTJhWWQAA+GRnI3s0iFKAQUMlsX89OR1m2K1Glashyl4zJxQix2JApz+ML/Y0qV0OUcZh0FBJLGiM40RQIlUZDSIWTCsFAHxV3YLDLZ0qV0SUWRg0VFIXX3HC+RlEahtbYseY4hwoCrDmjd2IyBxCIUoWBg2VcMUJkbYsnF4Kk0HE/iNuvP5RndrlEGUMBg0VhCMyDjZFu2c5EZRIG3IsRiyaUQYAWP+vGhxo4ioUomRg0FBBzSEXwhEZdqsRRXkWtcshoi6TxuRhRqUT4YiCR1/ZjkCQ+4QSjRSDhgp27W8DAEytKIAoCCpXQ0QxgiDgO2dMRl6OCQebO/HUP77hDqFEI8SgoYKdsaAxvkDlSojoWI4cE358/gyIgoAt24/g3S8OqV0Ska4xaKRZIBRB9aEOANEeDSLSnqpxBVi5dAIA4Jk3vsEXe5pVrohIvxg00mzvgQ6EIwoKHWaU5FvVLoeI+nDWwnE4eWY5FAX4wytfY8+BdrVLItIlBo0027G/FQAwpaIAAudnEGmWIAi4/OwqHD+xEKGwjN++8CW217aqXRaR7jBopFn3iaBEpG2SKOLH58/A1IoCBEIR/G7tl/jg68Nql0WkKwwaadTpD2HfkeiOoFMrnCpXQ0SDYTZKuHHVLCyYWoKIrOCJ13biidd2wOsPq10akS4Y1C4gm3yysxGKAowpzkFBrlntcoioF4IQvQFHhzZNRgn/ed4MlBbU4LUt+/DB10ewc38bvnPmFMybVDiEa/c+XMoltJTJGDTS6L1t0S7XE2eUq1wJEfVGkgSIogi3Lwyg55f/uUsmYMYEJ554bQea2v14+KUv4XSYceKMMiycWopRRTl9hokIAL8/1OtjFrMBUhLbQaQlDBppcrC5EzWHXJBEAYu7tjkmIm2RRAG+YBjV9R0IhhN3BTUaREwb78TksQW4+0cL8a+vDuO1LfvR6grgtQ/247UP9sORY8LkMXkoL8xBqdOGkgIrSp02OGxG+P1h7NjXilBY7vW6douRPRuUkRg00uT9r6K9GcdPLERejknlaoioP6GwjGCo7+3HjQYJ/7ZgHM5fNhlvf7QP7391GNv3tcLVGcSn3zQBaEp4vtkowekww2AQkWM2wG41IsdqRK7NiKI8LnOnzMagkQbhiByfqX7yTA6bEGUKs1HCoullmFdVgnBExvZ9bfh4ZwPa3AG4OgNwdYbg8YUQCEVwuMXb53Veea8W5YU5KHNaUea0oazQhjKnDU6HJX5MAed3kF4xaKTBlu1H4PKG4LAZMXPi4CeOEZF+GA0SjhuTh05/KKE3JBKRoQCw20zYUdOKdk8AHl80gLi90RDS5g6gzR3Ajn2J1zQZRJQU2FBaaENRngWlBVbk2c3RHhGLATaLEbk5Js7vIE1j0Egxrz+Mv75bDQA4c8E4GCSuKCbSq+4rUmIdDNH7jv76WJIkwm4zYuKYfCgyEAglLouVFQXF+VZ0eII43NKJIy1eHGn1orHNh2BYxoEmT79H1puMInKtJuRYjbBZDLCZDUf/azbAeux9FiMcOSbk2owQBaHXnhK97iXIXh9tYtBIsVffr4XLG0Kp04Yz5o9VuxwiGqZjV6QIooCg7IXPH4IiKxBFAfKAV+nJYjJgwqi8HpNBI7KM5g4/Glp92N/gxs59rWjzBOAPRBAIRW+KAgRDMlpCfrS4/ENrjyggP9eMvBwT8nPNKLCbkZ9rRlGeBcUFVkwSROgpb3BVj3YxaKTQ/iNu/HPrAQDA9741ib0ZRDp27IoUSRRgtZrg8wURkRXYLAZUlDsgJOnrWRJFlBbYUObMwcQxeSjMsyQMySiKApNRQonTht372+HxBRHsmsQaDMnRmqwGeH1h+ALRmzcQhtcfRqcvhIisoKXDj5aOvgNKQa4ZxflWlORbUZxvRXFB9P+L8i3ItRpTcoxC7JqKosAfjKDTH4rW7A+h0xdCpz/aBm8gen8wLCMcURAIhtHmCSAcUSDLMhQl2ptklAQUOCzxSbi5NhPyc00YVeqAWRLgtJtgNEjsDUkh3QSN2tpa3H333di6dSusViuWL1+Om2++GRaLRe3SenWwuRP3v/AFIrKCEyYVYcYEzs0gygSxFSmSKMBgjP5/RFZgMg7/HxK9bRLW/bHeXyPAbJJQlG9Fc5sfOdbEv85jwzW9LdWVZQUKFOR0zRtxeQLo7Poyd3uj80dCYTk+d2R3fXuP97eYpGj46Aoi+XYTLGYDrGYDLCYJZqMU3YlEiQ4PybICfygCnz8MXzAafPyBCHzBruDgD8HTFYK8XcEoWd/xtYfd/T6en2tGkSPak1PqjE7ELXVa4XRYYLMY2RsyQroIGi6XC5dffjlGjRqF3//+92htbcXq1avR3t6O++67T+3yeqg97MLvX/oKHl8IFWW5uHL5VLVLIiKNGmiTsOEOycT0tVTXbjOistyBgD/SY95Irs2I0aUOfLarAS0dfrg6g3B7Q3B5g3B7g/D6wvAHI6hv9KC+se/5I8kgigLMRhFmowEFuWbk2oywWbomw5oNMJskGCQRYVnGkRYvFEWJrtQRooFKFAWUOnPgD4S7JuFG29LpD6OpzYdAKIJ2dwDt7gD2HuxIeG+DJKDMacPoYjvKC20YVZiD8kIbSp029lAPgS6CxvPPPw+Xy4X169fD6YyeESJJEm6++Wb8+Mc/xsSJE1WuMMoXCOPFd/Zi8xeHoAAYU2zHTy+eDZvFqHZpRKRR/W0SBiDpQzKDIQgC7DYTCvMssJkTvyZMRgnTxjvhD4TR2BadtNrY7oPbG4I/EA0gnYEwPN4gFET7aGLDEmaTBGeuBWaTBItJgtVsgNkowWY2IMdqgNlkwOHmTohC9H1MRjH+hW61GDDruGJEIgqODWSiKCAsK9i2t7lHqOqtZyc27OX1BqAAsFqM2LanGS0uPzo6g+jwRJcmhyMKDjR14kBTZ+L7CQKK8y0oL8xBYZ4F+XYT8u1m5HetCIpNwLWaJUgiA4kugsbmzZuxePHieMgAgDPPPBM/+9nPsGnTJs0Ejdc+2IdNXxwCACyeXopLTp8Eu5Uhg4gG1lfPw0iGZFLFZBThzM1BeWFOj8cEAXD7QvhykF/6MbFABaXnyhyg/0A2mDDW/fc3NuwVCsuwWgyoKMuFzxfG2G7vK8sKAmEZzlwz2lwBHGruxKGWThxu6YQvEEFDmw8Nbb4Bf6/MxmigspqlaHgyiDAbpXiQMhmi/zV3PWYyHvu82HO6/t8owSiJEMXoSidRECB2rXwSu1Y/KYguq5Y1Mr9EUHQw02Xx4sVYuXIlbr755oT7ly9fjtmzZ+Oee+4Z1nWVrnHDZAlHZHgDYVhNBhgN6fnLQRAARUF8Bnp3ogAYDCJCYXlIj43ktcm8brT3U4ACBQK0X+9wrhuOKFAUJeE5em3LsY/H/hKUJEEX9Q71se5/PhVF+/UO6bqiAIMkIhTu+feKIAAmgwRA6WWg5+jviZZ/Hwb7d0tfbZVlBRFZOfrfru8SWY7+WdDKF3x3BklM6mGe0aAzuF42XfRouFwuOByOHvc7HA50dHT08orBEbr+EkwWSRJhNqnzW2rrZ7zQaOh7KlN/j43ktbzuYK+rxnvyurzuYF87/H8wZdLvA42M9vrkhkBRlJQsryIiIqLk0EXQcDgccLlcPe53u9299nQQERGRNugiaEycOBHV1dUJ9wWDQdTV1WlmIigRERH1pIugsWTJEnz44Ydoa2uL3/fmm28iGAxi6dKlKlZGRERE/dHFqhOXy4UVK1Zg9OjRuOaaa9DS0oJf//rXOPnkkzW5YRcRERFF6SJoAIlbkFssFqxYsULTW5ATERGRjoIGERER6Y8u5mgQERGRPjFoEBERUcowaBAREVHKMGgQERFRyjBoEBERUcowaBAREVHKMGhoRG1tLa688krMnj0bixcvxt133w2/3z+o17788ss466yzMHPmTKxYsQIbN27s8ZxQKIT7778fJ598MmbNmoXLLrsMu3btSnYzepXqtlVVVfW4nXTSScluRp+G274NGzbg+uuvxymnnIKqqio8+eSTvT5Pzc8OSH379Pj5eTwePPDAA1i1ahXmzZuHRYsW4corr8T27dt7PFdvP3tDaZsePzsA+M1vfoPly5fjhBNOwJw5c7By5Ur8/e9/7/E8vf7sDbZ96fr8dHFMfKZzuVy4/PLLMWrUKPz+979Ha2srVq9ejfb29gF3Pn399ddx22234T/+4z9w0kkn4a233sJ//dd/ITc3FyeffHL8eatXr8b69etx2223YfTo0XjiiSfwgx/8AH/7299QXFys67YBwGWXXYYVK1bEf200GlPSnmONtH319fU47bTT8MILL/T5PLU+OyA97QP09/kdOnQIL7zwAlauXIkbbrgB4XAYTz31FC655BI8//zzmD59evy5evvZG0rbAP19dgDg8/lwySWXoLKyEoqi4B//+AduuukmyLKMc845J/48vf7sDbZ9QJo+P4VU9+ijjyqzZs1SWlpa4ve9+uqryuTJk5W9e/f2+9qzzjpLueGGGxLu++EPf6isWrUq/usjR44oU6dOVZ555pn4fW63W1mwYIHym9/8Jkmt6F2q26YoijJ58mTliSeeSF7RQzCS9kUikfj/99UGNT87RUl9+wZ6LNWG277Ozk7F6/Um3Of3+5WTTjpJue222+L36fFnb7BtUxR9fnZ9ufjii5Urrrgi/ms9/+z15tj2KUr6Pj8OnWjA5s2bsXjxYjidzvh9Z555JkwmEzZt2tTn6+rr61FTU5OQRgFgxYoV+Oqrr9Da2goAeO+99xCJRLB8+fL4c+x2O5YtW9bv9ZMh1W1T23DbBwCiOPCPn5qfHZD69qltuO2z2WywWq0J95nNZkycOBGNjY3x+/T4szfYtqltJH82e5Ofn49QKBT/tZ5/9npzbPvSSft/E2SB6urqHsfdm0wmjBs3DtXV1X2+rqamBgAwYcKEhPsnTpwIRVHij1dXV6OoqAj5+fk9nldbWwtZlpPQit6lum0xjz32GKZPn4558+bhxhtvxKFDh5LUgv4Nt31Dub5an13s/VPZvphM+Py8Xi927tyZ8GdWjz97vemtbTF6/ewURUE4HIbL5cL69evx/vvv43vf+17C9fX8szdQ+2LS8flxjoYGuFwuOByOHvc7HA50dHT0+brYY8e+Ni8vL+Fxl8uF3NzcHq/Py8tDKBSC1+uF3W4fdv39SXXbAOD888/HqaeeiqKiIuzevRt/+MMf8N3vfhevvPJK/PmpMtz2DeX6an12sfdPZfuAzPn8fve738Hn8+HSSy9NuL7efvZ601vbAH1/dlu2bMEVV1wBADAYDPjFL36Bs846K+H6ev7ZG6h9QPo+PwYNDVMUBYIgDPi8Y5+jdJ2T1/3+3q6jqHieXjLbdu+998b/f/78+Zg7dy4uvPBCvPjii7jqqquSVPHQDLZ9g6G1zy72/slqXyZ8fn/729/wl7/8Bb/85S9RUVGR8JjWPr9ktk3Pn93xxx+Pl156CR6PB5s3b8b//u//QpIkrFq1Kv4crX12sfdPVvvS9fkxaGiAw+GAy+Xqcb/b7e7RddZd93/dFxUVxe+PXSuWhvu6vsvlgtFohM1mG1H9/Ul123ozZcoUVFZW9rocL9mG276RXj8dn11/75+s9vVGb5/f+++/j9tvvx1XXnllj65pPf7sdddf23qjp8/Obrdj5syZAIDFixcjGAzi17/+NS688EJIkqT7n72B2tebVH1+nKOhARMnTuwx5hYMBlFXV9fvH6jYeOmx8xWqq6shCEL88YkTJ6KlpQXt7e09nldZWZnSSXupbltf0vWvjuG2byjXV+uzi71/KtvXF718fl999RWuu+46nHXWWbjlllt6vb7efvZiBmpbX/Ty2R1r+vTp8Hg88Ynmmfazd2z7+pKKz49BQwOWLFmCDz/8EG1tbfH73nzzTQSDQSxdurTP140dOxYTJkzAhg0bEu5/7bXXcPzxx8dnK5988skQRTFhs6vOzk68/fbb/V4/GVLdtt7s3LkT+/bti6f5VBpu+wZLzc8OSH37eqOXz6+6uhpXXXUV5syZg9WrV/fana3Hnz1gcG3rjV4+u95s3boVdrsdBQUFADLvZ+/Y9vUmZZ9fyhfQ0oA6OjqUU045RbnkkkuUzZs3Ky+//LKycOFC5ac//WnC826//XZl6tSpCfdt2LBBqaqqUn77298qH374oXLPPfcoVVVVyr/+9a+E5915553KnDlzlBdffFF57733lB/+8IfKggULlMbGRl237YknnlD+53/+R/n73/+ubNmyRXnqqaeUE088UTnttNOUjo6OlLZtpO3bs2ePsnHjRmXjxo3K5MmTlVtvvVXZuHGj8u677yY8T63PLh3t0+vn19zcrCxdulQ56aSTlA8++ED5/PPP47ft27cnvFZvP3uDbZteP7udO3cqV155pbJ27Vrlgw8+UN566y3ljjvuUCZPnqw8+uijCa/V48/eYNuXzs+PczQ0wOFw4C9/+QvuvvtuXH/99bBYLFixYgVuvvnmhOfJsoxIJJJw39lnnw2/349HHnkETz75JCoqKvB///d/PXbOvO2222Cz2fC73/0Obrcbs2bNwl/+8peU726X6rZVVlbijTfewIYNG9DZ2YmCggIsXboUN954Y7/zOLTQvo0bN+LBBx+M/3r9+vVYv349Ro8ejbfffjt+v1qfHZD69un189u7dy8OHz4MAPjBD36Q8FytfH6pbpteP7uioiI4HA48/PDDaGpqQm5uLiZMmICHHnoI3/rWtxJeq8efvcG2L52fn6AoKk+hJSIioozFORpERESUMgwaRERElDIMGkRERJQyDBpERESUMgwaRERElDIMGkRERJQyDBpERESUMgwaRERElDIMGkQ6tW7dOlRVVWHbtm0AgE2bNuGBBx5Quaq+vfXWW6iqqsJzzz3X53Pef/99VFVV4U9/+hMAoKqqashteuCBB1BVVZVw37Jly/Cf//mfA772wIEDqKqqwrp16+L3xX6fDxw4EL/vtttuw7JlyxJe+8gjj+Ctt94aUq1E2YBBgyhDbNq0KWHLb6059dRTUVxcjL/+9a99PmfdunUwGo0477zzAAAvvPACVq1aNaT3WbVqFV544YVh1VhSUoIXXngBp556ar/Pu+aaa3r8Xj/66KMMGkS94FknRJQWBoMB5513Hp544gns3r0bkydPTnjc5XLhzTffxLJly+Kn886ePXvI71NWVoaysrJh1WgymQb1nuPGjRvW9YmyEXs0iDLAbbfdhjVr1gCIDjfEbrHufkVRsGbNGpx33nk4/vjjMX/+fNxwww2or69PuM5ll12GFStW4PPPP8cll1yC448/HsuWLYv3Qrz77ru44IILMGvWLJxzzjnYvHnzkOq86KKLACBhaCLmtddeQyAQwMqVK+P3HTt04vP5cO+992LZsmWYOXMmFixYgAsvvBCvvfZa/Dm9DZ3EvPnmmzjnnHMwc+ZMnH766XjqqacSHu9t6KQ3xw6dVFVVwev14uWXX47/3l922WU4cOAApk2bhkcffbTHNT755BNUVVUlHENOlInYo0GUAa655hp4vV784x//SBg2KCkpAQD88pe/xMsvv4zLLrsMN998Mzo6OvDQQw/hkksuwSuvvIKioqL4a5qamnD77bfjRz/6EcrKyvDMM8/gZz/7GQ4fPox//OMfuPrqq2G32/Hwww/j2muvxVtvvYXS0tJB1VlZWYm5c+fi1VdfxU9/+lMYjcb4Y+vWrUNpaWmPk4e7W716NV599VXceOONmDp1Knw+H3bv3o329vYB33vnzp341a9+heuuuw5FRUX429/+hnvuuQehUAhXXnnloOrvywsvvIDLL78cCxcuxDXXXAMAsNvtGDNmDJYtW4bnn38eP/rRjyBJUvw1zzzzDEpKSnDGGWeM6L2JtI5BgygDjBs3Lh4Wju36/+KLL/Diiy/itttuwxVXXBG/f968eTjzzDPxpz/9Cbfcckv8/vb2djz55JOYMWMGAGDGjBk48cQT8fjjj+ONN96Ih4rS0lKcd955eOONN3DZZZcNutaLLroIt99+O9599934l+yePXuwbds2XH311Qlfxsf6/PPPcdJJJyUcXz7QfIqYxsZGrF+/HlOmTAEALF26FK2trXj44Yfx3e9+F1arddBtONbs2bMhiiKcTmeP3//LLrsM3//+9/HOO+/Ej+luaGjAW2+9hR//+McwGPjXMGU2Dp0QZbh33nkHgiDg3HPPRTgcjt+KioowZcoUfPzxxwnPLy4ujocMAMjPz4fT6cTUqVMTei4mTJgAADh06NCQ6jn77LORk5OTMCn0r3/9KwRBSBg26c3MmTOxefNm3Hffffjoo4/g9/sH/b6TJk2Kh4yYFStWwOPxYPv27UNqw1AsXLgQU6ZMiQ9tAcDzzz8PQRBw8cUXp+x9ibSCUZoow7W0tEBRFJx44om9Pj527NiEX+fn5/d4jslkQl5eXo/7ACAQCAypHqvViuXLl2PdunVoampCQUEBXn31VcyfP3/ASZY///nPUVZWhg0bNuDxxx+H2WzGySefjFtvvRXjx4/v97Xdh4eOvW8wQy8jcdlll+HnP/85ampqMHbsWKxduxZnnnkmiouLU/q+RFrAoEGU4QoKCiAIAtasWRMPB931dl+qXXTRRXjxxRexfv16VFZWoqWlBf/93/894OtsNhtuuOEG3HDDDWhubsbmzZtx//334+qrr8brr7/e72ubm5v7vK+3cJVM55xzDu677z48++yzmDVrFpqamvDd7343pe9JpBUMGkQZIhYY/H4/LBZL/P5TTz0Vjz32GBoaGvDtb39brfISzJo1C5MnT8a6deswfvx45Obm4swzzxzSNYqKinDhhRdi165d+Mtf/gKfz9fvPIs9e/Zg165dCcMnr732GnJycjB9+vRhtyXGZDL1OZRjNptx8cUX45lnnsFnn32GqVOnYu7cuSN+TyI9YNAgyhCxfSkef/xxLFmyBKIooqqqCnPnzsXFF1+Mn/3sZ/j6668xf/58WK1WNDU1YevWrZg8ebIq/7peuXIlVq9ejdraWlx88cUJ4agvq1atwqmnnoqqqirk5eWhuroar7zyCk444YQBJ3OWlJTgxz/+Ma677joUFxfj1Vdfxfvvv4+bb755RBNBYyZPnoyPP/4Yb7/9NoqLi5GTkxOfxwIA3/3ud/HEE09g+/btuPvuu0f8fkR6waBBlCFWrFiBzz77DM8++yweeughKIqCf/7znxgzZgzuuusuzJo1Cy+88AKee+45yLKMkpISzJkzB8cff7wq9Z577rm47777EAqFBpwEGrNo0SK8/fbb8R6M0tJSnH/++bj66qsHfO3UqVNx4YUX4oEHHsC+fftQUlKC22+/PWEFy0jccccduPPOO3HTTTfB5/NhwYIFePrpp+OPl5aWYs6cOdi9ezfOOeecpLwnkR4IiqIoahdBRJTpWlpacNppp+HSSy/FrbfeqnY5RGnDHg0iohQ6cuQI6uvr8eSTT0IURVx++eVql0SUVgwaRJQU4XC438dFUYQoZt/WPWvXrsVDDz2E0aNH47777hv0LqpEmYJDJ0Q0YgcOHMDpp5/e73Ouu+46XH/99WmqiIi0gkGDiEYsGAzim2++6fc5JSUl/Nc8URZi0CAiIqKUyb4BUyIiIkobBg0iIiJKGQYNIiIiShkGDSIiIkoZBg0iIiJKGQYNIiIiShkGDSIiIkqZ/x/qUov/WTwV8AAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 600x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["sns.set()\n","# Item Visibility distribution\n","plt.figure(figsize=(6,6))\n","sns.distplot(df['Item_Visibility'])\n","plt.show()"]},{"cell_type":"code","execution_count":9,"id":"17a9d963","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:11.0355Z","iopub.status.busy":"2023-05-01T14:24:11.035075Z","iopub.status.idle":"2023-05-01T14:24:11.374731Z","shell.execute_reply":"2023-05-01T14:24:11.373357Z"},"papermill":{"duration":0.352712,"end_time":"2023-05-01T14:24:11.377623","exception":false,"start_time":"2023-05-01T14:24:11.024911","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:3: UserWarning: \n","\n","`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n","\n","Please adapt your code to use either `displot` (a figure-level function with\n","similar flexibility) or `histplot` (an axes-level function for histograms).\n","\n","For a guide to updating your code to use the new functions, please see\n","https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n","\n","  This is separate from the ipykernel package so we can avoid doing imports until\n"]},{"data":{"image/png":"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\n","text/plain":["<Figure size 600x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Item Weight distribution\n","plt.figure(figsize=(6,6))\n","sns.distplot(df['Item_Weight'])\n","plt.show()"]},{"cell_type":"code","execution_count":10,"id":"b8de7be8","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:11.398904Z","iopub.status.busy":"2023-05-01T14:24:11.398496Z","iopub.status.idle":"2023-05-01T14:24:11.813781Z","shell.execute_reply":"2023-05-01T14:24:11.812504Z"},"papermill":{"duration":0.429146,"end_time":"2023-05-01T14:24:11.816605","exception":false,"start_time":"2023-05-01T14:24:11.387459","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:3: UserWarning: \n","\n","`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n","\n","Please adapt your code to use either `displot` (a figure-level function with\n","similar flexibility) or `histplot` (an axes-level function for histograms).\n","\n","For a guide to updating your code to use the new functions, please see\n","https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n","\n","  This is separate from the ipykernel package so we can avoid doing imports until\n"]},{"data":{"image/png":"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\n","text/plain":["<Figure size 600x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Item Outlet Sales distribution\n","plt.figure(figsize=(6,6))\n","sns.distplot(df['Item_Outlet_Sales'])\n","plt.show()"]},{"cell_type":"code","execution_count":11,"id":"65ed1877","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:11.840388Z","iopub.status.busy":"2023-05-01T14:24:11.839972Z","iopub.status.idle":"2023-05-01T14:24:12.112368Z","shell.execute_reply":"2023-05-01T14:24:12.110998Z"},"papermill":{"duration":0.287509,"end_time":"2023-05-01T14:24:12.11499","exception":false,"start_time":"2023-05-01T14:24:11.827481","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 600x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Outlet Establishment Year column\n","plt.figure(figsize=(6,6))\n","sns.countplot(x='Outlet_Establishment_Year', data=df)\n","plt.show()"]},{"cell_type":"markdown","id":"d92e7db4","metadata":{"papermill":{"duration":0.010278,"end_time":"2023-05-01T14:24:12.136061","exception":false,"start_time":"2023-05-01T14:24:12.125783","status":"completed"},"tags":[]},"source":["### Categorical Features"]},{"cell_type":"code","execution_count":12,"id":"7b9bf75a","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:12.159546Z","iopub.status.busy":"2023-05-01T14:24:12.159147Z","iopub.status.idle":"2023-05-01T14:24:12.389655Z","shell.execute_reply":"2023-05-01T14:24:12.388659Z"},"papermill":{"duration":0.245764,"end_time":"2023-05-01T14:24:12.392411","exception":false,"start_time":"2023-05-01T14:24:12.146647","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 600x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Item Fat Content column\n","plt.figure(figsize=(6,6))\n","sns.countplot(x='Item_Fat_Content', 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\n","text/plain":["<Figure size 3000x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Item Type column\n","plt.figure(figsize=(30,6))\n","sns.countplot(x='Item_Type', data=df)\n","plt.show()"]},{"cell_type":"code","execution_count":14,"id":"d8805d1a","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:12.869238Z","iopub.status.busy":"2023-05-01T14:24:12.868764Z","iopub.status.idle":"2023-05-01T14:24:13.083335Z","shell.execute_reply":"2023-05-01T14:24:13.082101Z"},"papermill":{"duration":0.230748,"end_time":"2023-05-01T14:24:13.086131","exception":false,"start_time":"2023-05-01T14:24:12.855383","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAi0AAAIWCAYAAACbVL0cAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA5cklEQVR4nO3dfVzV9eH//+c5R474QY/CQvmo0xSDREnBJlgJZrmmySaZm6VZSpZX1UrrZ6WWZpqrYCSoYbip2VZs6YpJbcvJdE3bJ9RVppvHNosQL/F4xYWH8/vDL2cewQuuPLzkcb/dvCHv9+u8z+sN54YP3xcHi8fj8QgAAKCJs/p7AgAAAJeDaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYwe/R8u677yoyMrLan1deecVnXH5+vkaMGKHo6GgNGTJEa9asqXF72dnZGjx4sKKjozVy5Eht3bq12pgTJ05ozpw5iouLU0xMjCZNmqTCwsJG2T8AANAwWvh7AlXeeOMNtWnTxvt5hw4dvH/ftm2bpkyZoh/96EeaOXOmCgoKNH/+fNntdo0aNco7Ljs7W2lpaXr88ccVFRWlnJwcTZw4UTk5OYqMjPSOmz59ur744gvNnj1brVu31muvvabx48frvffeU2Bg4JXZYQAAUCtNJlp69eqlkJCQGtdlZmYqKipKCxYskCTFx8erqKhI6enpGjlypKxWq8rLy7V06VKNGzdOKSkpkqT+/fsrKSlJy5YtU1pamiRpx44d2rhxo7KyspSYmChJioiI0JAhQ7R27Vrdc889dd4Hj8ejykp+lRMAALVhtVpksVguOa7JRMuFlJeXa8uWLZoxY4bP8qSkJL3zzjvauXOnevfurYKCAh0/flzDhw/3jrHZbBo2bJhWrFghj8cji8Wi/Px8ORwOJSQkeMd17NhRsbGxys/Pr1e0VFZ6dOTIyTo/HgCA5igkJEg226Wjxe/XtFQZPny4evbsqdtuu02vv/663G63JGnfvn2qqKhQ9+7dfcb36NFDkuR0On0+nj8uPDxcJ0+eVHFxsXdct27dqhVdjx49vNsAAABNj9+PtISGhuqRRx5Rnz59ZLFYtGHDBv385z9XcXGx5syZo2PHjkmSHA6Hz+OqPq9a73K5ZLfbq12T0rZtW0lSSUmJwsLC5HK5fK6dOXd7VduqjxYtmkwHAgBwVfF7tAwcOFADBw70fn7LLbeoZcuWWrlypSZNmuRdfqFzXecur2mMx+O5rHEXW365rFaLgoOD6rUNAABQM79HS02GDh2qFStW6Msvv1SnTp0kqdpREJfLJem/R1wcDofKyspUVlamli1bVhtXdcTF4XCoqKio2nO6XK5qR3Nqq7LSI5frVL22AQBAc+NwtJLNdukzFU0yWs7VpUsXBQQEaO/evT4Xz+7Zs0fS2WtWzv3odDoVFRXlHed0OhUUFOS9hTo8PFwff/yx98Lcc7dXtY36OHOmst7bAAAA1TXJCzDWr18vm82mqKgo2e12xcfHKy8vz2dMbm6uQkNDvYESGxurNm3aaP369d4xbrdbeXl5SkxM9AZKYmKiXC6XNm3a5B1XVFSkgoIC7y3QAACg6fH7kZaUlBTFx8crIiJCkvTRRx/pnXfe0bhx4xQaGipJmjp1qsaOHatZs2YpKSlJBQUFysnJ0bx582S1nu0uu92uyZMnKy0tTSEhId43l/v666+Vmprqfb4+ffpo0KBBevbZZzVz5ky1bt1a6enp6tSpk5KTk6/8FwAAAFwWi6fqSlU/mT9/vjZt2qT9+/ersrJS1157rUaNGqX77rvP5/RNfn6+UlNT5XQ6FRYWpvHjx2vMmDE+2/J4PMrOztaaNWt06NAhRURE6Mknn1R8fLzPuBMnTmjRokX68MMPVVFRobi4OM2ePdt7/Uxdud2VvE8LAAC1dPZ9Wi598sfv0XI1IVoAAKi9y42WJnlNCwAAwPmIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEv//CRABXltVqkdVqufRAXBUqKz2qrOS3teDqQLQAzYjValFwcCtZrTZ/TwVXSGWlW0ePniZccFUgWoBm5OxRFpu+yl2u04eL/D0dNLJW3/lfdRs+UVarhWjBVYFoAZqh04eLdLp4n7+nAQC1woW4AADACEQLAAAwAtECAACMQLQAAAAjEC0AAMAIRAsAADAC0QIAAIxAtAAAACMQLQAAwAhECwAAMALRAgAAjEC0AAAAIxAtAADACEQLAAAwAtECAACMQLQAAAAjEC0AAMAIRAsAADAC0QIAAIxAtAAAACMQLQAAwAhECwAAMALRAgAAjEC0AAAAIxAtAADACEQLAAAwAtECAACMQLQAAAAjEC0AAMAIRAsAADAC0QIAAIxAtAAAACMQLQAAwAhECwAAMALRAgAAjEC0AAAAIxAtAADACEQLAAAwAtECAACMQLQAAAAjEC0AAMAIRAsAADAC0QIAAIxAtAAAACMQLQAAwAhECwAAMALRAgAAjEC0AAAAIxAtAADACEQLAAAwAtECAACMQLQAAAAjEC0AAMAIRAsAADAC0QIAAIxAtAAAACMQLQAAwAhECwAAMALRAgAAjEC0AAAAIxAtAADACEQLAAAwAtECAACMQLQAAAAjEC0AAMAITSpaTp48qYSEBEVGRuqzzz7zWZefn68RI0YoOjpaQ4YM0Zo1a2rcRnZ2tgYPHqzo6GiNHDlSW7durTbmxIkTmjNnjuLi4hQTE6NJkyapsLCwUfYJAAA0jCYVLUuWLJHb7a62fNu2bZoyZYqioqK0fPlyJScna/78+crJyfEZl52drbS0NI0ZM0ZZWVnq2rWrJk6cqN27d/uMmz59ujZs2KDZs2crLS1NBw4c0Pjx41VaWtqo+wcAAOquyUSL0+nUW2+9pUceeaTauszMTEVFRWnBggWKj4/XlClTdPfddys9PV2VlZWSpPLyci1dulTjxo1TSkqKBgwYoJdfflmdO3fWsmXLvNvasWOHNm7cqBdffFHDhw/XoEGDlJGRocLCQq1du/aK7S8AAKidJhMtL774okaPHq1u3br5LC8vL9eWLVt05513+ixPSkrSwYMHtXPnTklSQUGBjh8/ruHDh3vH2Gw2DRs2TPn5+fJ4PJLOnmZyOBxKSEjwjuvYsaNiY2OVn5/fWLsHAADqqYW/JyBJH3zwgXbt2qXXXntNX3zxhc+6ffv2qaKiQt27d/dZ3qNHD0lnj9D07t1bTqdTkqqNCw8P18mTJ1VcXKywsDA5nU5169ZNFoul2vY2b95c731p0aLJdCBQjc3G67M54vuOq4Xfo+X06dN66aWX9MQTT6h169bV1h87dkyS5HA4fJZXfV613uVyyW63KzAw0Gdc27ZtJUklJSUKCwuTy+VSmzZtqj2Pw+HwbquurFaLgoOD6rUNAGhoDkcrf08BaBB+j5alS5fqO9/5ju66666Ljjv/yEhNy2saU3Va6FLjLrb8clVWeuRynarXNoDGZLNZ+QesGXK5TsvtrvT3NIALcjhaXdYRQb9GS2FhoVasWKHMzEydOHFCknTq1Cnvx5MnT3qPlJx/FMTlckn67xEXh8OhsrIylZWVqWXLltXGVW3H4XCoqKio2lxcLle1ozl1ceYMPxgANC1udyU/m3BV8Gu0fPPNN6qoqNBDDz1Ubd24cePUp08fvfnmmwoICNDevXt9Lp7ds2ePpLPXrJz70el0KioqyjvO6XQqKChIHTp08I77+OOP5fF4fI6s7Nmzx7sNAADQ9Pj16qyePXtq1apVPn+efvppSdLcuXP13HPPyW63Kz4+Xnl5eT6Pzc3NVWhoqDdQYmNj1aZNG61fv947xu12Ky8vT4mJid5ASUxMlMvl0qZNm7zjioqKVFBQoMTExMbeZQAAUEd+PdLicDgUFxdX47pevXqpV69ekqSpU6dq7NixmjVrlpKSklRQUKCcnBzNmzdPVuvZ7rLb7Zo8ebLS0tIUEhKiqKgo5eTk6Ouvv1Zqaqp3u3369NGgQYP07LPPaubMmWrdurXS09PVqVMnJScnN/5OAwCAOvH7hbiXIyYmRkuWLFFqaqrWrVunsLAwzZo1S6NGjfIZN2HCBHk8Hq1evVqHDh1SRESEsrKyFBkZ6TPu1Vdf1aJFizR37lxVVFQoLi5OixcvrnbnEQAAaDosnqrba1Bvbneljhw56e9pABfUooVVwcFB2rlynk4X7/P3dNDIWnXooqj75+jo0ZNciIsmLSQk6LLuHuIdhwAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBL9Hy6ZNmzR27FjFx8erd+/euu2227Rw4UIdP37cZ1x+fr5GjBih6OhoDRkyRGvWrKlxe9nZ2Ro8eLCio6M1cuRIbd26tdqYEydOaM6cOYqLi1NMTIwmTZqkwsLCRtk/AADQMPweLceOHVNMTIxeeOEFZWdna/z48Vq3bp0ee+wx75ht27ZpypQpioqK0vLly5WcnKz58+crJyfHZ1vZ2dlKS0vTmDFjlJWVpa5du2rixInavXu3z7jp06drw4YNmj17ttLS0nTgwAGNHz9epaWlV2SfAQBA7bXw9wSGDx+u4cOHez+Pi4uT3W7X7NmzVVxcrA4dOigzM1NRUVFasGCBJCk+Pl5FRUVKT0/XyJEjZbVaVV5erqVLl2rcuHFKSUmRJPXv319JSUlatmyZ0tLSJEk7duzQxo0blZWVpcTERElSRESEhgwZorVr1+qee+65wl8BAABwOfx+pKUm7dq1kySdOXNG5eXl2rJli+68806fMUlJSTp48KB27twpSSooKNDx48d9Ashms2nYsGHKz8+Xx+ORdPY0k8PhUEJCgndcx44dFRsbq/z8/EbeMwAAUFdNJlrcbrfKysr0xRdfKDMzU7feeqs6deqkffv2qaKiQt27d/cZ36NHD0mS0+n0+Xj+uPDwcJ08eVLFxcXecd26dZPFYqm2vaptAACApsfvp4eq3Hrrrd6wGDhwoFJTUyWdveZFkhwOh8/4qs+r1rtcLtntdgUGBvqMa9u2rSSppKREYWFhcrlcatOmTbXndzgc3m3VR4sWTaYDgWpsNl6fzRHfd1wtmky0ZGVl6dSpU9qzZ4+WLFmiSZMm6Re/+IV3/flHRmpaXtOYqtNClxp3seWXy2q1KDg4qF7bAICG5nC08vcUgAbRZKLl+uuvlyTFxsYqKipKI0eO1B//+EfvaaDzj4K4XC5J/z3i4nA4VFZWprKyMrVs2bLauKojLg6HQ0VFRdWe3+VyVTuaU1uVlR65XKfqtQ2gMdlsVv4Ba4ZcrtNyuyv9PQ3gghyOVpd1RLDJRMu5evbsKZvNpn379mnw4MEKCAjQ3r17fS6e3bNnj6Sz16yc+9HpdCoqKso7zul0KigoSB06dPCO+/jjj+XxeHyOrOzZs8e7jfo4c4YfDACaFre7kp9NuCo0yROd27Ztk9vtVufOnWW32xUfH6+8vDyfMbm5uQoNDfUGSmxsrNq0aaP169d7x7jdbuXl5SkxMdEbKImJiXK5XNq0aZN3XFFRkQoKCry3QAMAgKbH70dapk2bpt69eysyMlKBgYHatWuX3njjDUVGRur222+XJE2dOlVjx47VrFmzlJSUpIKCAuXk5GjevHmyWs92l91u1+TJk5WWlqaQkBBFRUUpJydHX3/9tfeiXknq06ePBg0apGeffVYzZ85U69atlZ6erk6dOik5OdkvXwMAAHBpfo+WG264QevXr1dWVpY8Ho86deqkH//4x0pJSZHdbpckxcTEaMmSJUpNTdW6desUFhamWbNmadSoUT7bmjBhgjwej1avXq1Dhw4pIiJCWVlZioyM9Bn36quvatGiRZo7d64qKioUFxenxYsXV7vzCAAANB0WT9XtNag3t7tSR46c9Pc0gAtq0cKq4OAg7Vw5T6eL9/l7OmhkrTp0UdT9c3T06EmuaUGTFhISdFkX4jbJa1oAAADOR7QAAAAjEC0AAMAIRAsAADAC0QIAAIxAtAAAACMQLQAAwAhECwAAMALRAgAAjEC0AAAAIxAtAADACH7/hYk4y2q1yGq1+HsauEIqKz2qrOTXfgFAbRAtTYDValG7dv9zWb8sClcHt7tSJSWnCBcAqAWipQmwWi2y2azK/NVfVXjgmL+ng0bWqX1bTb3nZlmtFqIFAGqBaGlCCg8c078Lj/p7GgAANEmcjwAAAEaoU7RkZGSouLi4xnUHDhxQRkZGvSYFAABwvjpFS2Zm5kWjJTMzs16TAgAAOF+dosXjufDFg6dOnVKLFlwqAwAAGtZl18WuXbu0a9cu7+f5+fnau3evz5jS0lK9//776tKlS8PNEAAAQLWIlj/96U/ea1UsFssFTwEFBgZqwYIFDTM7AACA/+eyo+XHP/6xBg0aJI/Ho1GjRmnhwoW67rrrfMbY7XZ16dJFgYGBDT5RAADQvF12tLRv317t27eXJK1atUq9evVSUFBQo00MAADgXHW6YrZ///4NPQ8AAICLqvNtPr/73e+Um5urb7/9VqWlpT7rLBaL/vSnP9V7cgAAAFXqFC1ZWVlKTU1Vjx49dP3118tutzf0vAAAAHzUKVreeecdjRkzRrNnz27o+QAAANSoTm8ud+jQId1+++0NPRcAAIALqlO09OrVS19//XVDzwUAAOCC6hQtM2fO1IoVK/T555839HwAAABqVKdrWp555hmVlJRo1KhRuuaaa9SuXTuf9RaLRe+9915DzA8AAEBSHaOlXbt21UIFAACgMdUpWlavXt3Q8wAAALioOl3TAgAAcKXV6UjL3//+90uO+d73vleXTQMAANSoTtFy3333yWKxXHTMl19+WacJAQAA1KRO0bJq1apqy44ePaqPPvpIBQUFmjNnTr0nBgAAcK4G/S3Pd9xxh+bMmaNNmzYpISGhXhMDAAA4V4NfiDtkyBCtX7++oTcLAACauQaPFpfLpfLy8obeLAAAaObqdHro22+/rbasvLxcu3fv1quvvqo+ffrUe2IAAADnqlO0DB48uMa7hzwej7p168aFuAAAoMHVKVoWLFhQLVpatmypTp06KTo6WlYr71kHAAAaVp2i5a677mroeQAAAFxUnaKlyokTJ7R9+3aVlJQoODhYffr0UevWrRtqbgAAAF51jpbs7GxlZGSotLRUHo9HktSqVSs9+uijGj9+fINNEAAAQKpjtKxbt04vv/yyEhISlJycrPbt2+vAgQNat26dfvaznyk4OFgjRoxo4KkCAIDmrE7R8stf/lLDhw/XK6+84rN86NChmjFjhlauXEm0AACABlWn23z27t2rH/7whzWu++EPfyin01mvSQEAAJyvTtESGBioY8eO1bju2LFjCgwMrNekAAAAzlenaOnXr58yMjJUXFzss/zgwYPKzMzUjTfe2CCTAwAAqFKna1qeeOIJ/eQnP9H3v/99DRgwQKGhoTp48KC2bNmiFi1aKCMjo6HnCQAAmrk6Rct1112n3/zmN8rIyNDWrVtVUlKidu3a6bbbbtO0adPUrVu3hp4nAABo5uoULRUVFQoLC1Nqamq1dadOnVJFRYUCAgLqPTkAAIAqdYqW2bNnq7y8vMZomT17tgIDA/Xiiy/We3IAAABV6nQh7tatWzV48OAa1w0ePFh/+9vf6jUpAACA89UpWg4dOqTQ0NAa111zzTU6dOhQvSYFAABwvjpFi8Ph0L59+2pct2/fPgUFBdVrUgAAAOerU7TExcXp9ddfV0lJic/ykpISZWVlKT4+viHmBgAA4FWnC3GnTZumu+++W3fccYeGDh2qDh06aP/+/frggw905swZPfLIIw09TwAA0MzVKVq6d++ut956SwsXLlROTo7cbrdsNpu+973vaebMmerevXtDzxMAADRzdYoWSbr++uu1cuVKlZaW6tixY2rXrp1atmzZkHMDAADwqnO0VAkMDOQXJAIAgEZXpwtxAQAArjSiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEfweLXl5eZoyZYoSExPVt29fJSUl6a233lJlZaXPuPz8fI0YMULR0dEaMmSI1qxZU+P2srOzNXjwYEVHR2vkyJHaunVrtTEnTpzQnDlzFBcXp5iYGE2aNEmFhYWNsn8AAKBh+D1afvGLX8hut+upp57SsmXLdPvtt+vFF1/Uyy+/7B2zbds2TZkyRVFRUVq+fLmSk5M1f/585eTk+GwrOztbaWlpGjNmjLKystS1a1dNnDhRu3fv9hk3ffp0bdiwQbNnz1ZaWpoOHDig8ePHq7S09IrsMwAAqL0W/p7AsmXLFBIS4v08Pj5ep06d0po1a/T444/LbrcrMzNTUVFRWrBggXdMUVGR0tPTNXLkSFmtVpWXl2vp0qUaN26cUlJSJEn9+/dXUlKSli1bprS0NEnSjh07tHHjRmVlZSkxMVGSFBERoSFDhmjt2rW65557rvBXAAAAXA6/H2k5N1iq9OzZU2VlZSopKVF5ebm2bNmiO++802dMUlKSDh48qJ07d0qSCgoKdPz4cQ0fPtw7xmazadiwYcrPz5fH45F09jSTw+FQQkKCd1zHjh0VGxur/Pz8xthFAADQAPweLTX59NNP1a5dO33nO9/Rvn37VFFRoe7du/uM6dGjhyTJ6XT6fDx/XHh4uE6ePKni4mLvuG7duslisVTbXtU2AABA0+P300Pn++yzz/Tuu+9q6tSpstlsOnbsmCTJ4XD4jKv6vGq9y+WS3W5XYGCgz7i2bdtKkkpKShQWFiaXy6U2bdpUe16Hw+HdVn20aFH7DrTZmmQ7opH54/vOa6154vuOq0WTipaDBw/q0UcfVXR0tCZOnOiz7vwjIzUtr2lM1WmhS4272PLLZbVaFBwcVK9toPlwOFr5ewpoJnit4WrRZKLl+PHjmjhxogIDA7V06VIFBARI+u+RkvOPgrhcLkn/PeLicDhUVlamsrIytWzZstq4qu04HA4VFRVVe36Xy1XtaE5tVVZ65HKdqvXjbDYrP1SaIZfrtNzuyksPbEC81ponf7zWgNpwOFpd1hHBJhEtZWVlmjx5sg4dOqS3335bwcHB3nVdunRRQECA9u7d63Px7J49eySdvWbl3I9Op1NRUVHecU6nU0FBQerQoYN33McffyyPx+NzZGXPnj3ebdTHmTP8YMDlcbsreb3giuC1hquF3090njlzRo899ph27dqlN954Q506dfJZb7fbFR8fr7y8PJ/lubm5Cg0N9QZKbGys2rRpo/Xr13vHuN1u5eXlKTEx0RsoiYmJcrlc2rRpk3dcUVGRCgoKvLdAAwCApsfvR1rmzZunP//5z3ryySdVWlqq7du3e9f16NFDrVu31tSpUzV27FjNmjVLSUlJKigoUE5OjubNmyer9Wx32e12TZ48WWlpaQoJCVFUVJRycnL09ddfKzU11bvNPn36aNCgQXr22Wc1c+ZMtW7dWunp6erUqZOSk5Ov9O4DAIDL5Pdo2bx5syT5vANulVWrVnnfan/JkiVKTU3VunXrFBYWplmzZmnUqFE+4ydMmCCPx6PVq1fr0KFDioiIUFZWliIjI33Gvfrqq1q0aJHmzp2riooKxcXFafHixdXuPAIAAE2HxVN1ew3qze2u1JEjJ2v9uBYtrAoODtIz6ev178KjjTAzNCXXdgrWgseG6ejRk1f8OoOq19rOlfN0unjfFX1uXHmtOnRR1P1z/PJaA2ojJCTosi7E9fs1LQAAAJeDaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEfweLf/5z380Z84c/ehHP1JUVJSGDx9e47j8/HyNGDFC0dHRGjJkiNasWVPjuOzsbA0ePFjR0dEaOXKktm7dWm3MiRMnNGfOHMXFxSkmJkaTJk1SYWFhg+4XAABoWH6Pln/961/Kz89X165dFR4eXuOYbdu2acqUKYqKitLy5cuVnJys+fPnKycnx2dcdna20tLSNGbMGGVlZalr166aOHGidu/e7TNu+vTp2rBhg2bPnq20tDQdOHBA48ePV2lpaaPtJwAAqJ8W/p7A4MGDdfvtt0uSZs6cqc8//7zamMzMTEVFRWnBggWSpPj4eBUVFSk9PV0jR46U1WpVeXm5li5dqnHjxiklJUWS1L9/fyUlJWnZsmVKS0uTJO3YsUMbN25UVlaWEhMTJUkREREaMmSI1q5dq3vuuedK7DYAAKglvx9psVovPoXy8nJt2bJFd955p8/ypKQkHTx4UDt37pQkFRQU6Pjx4z6nl2w2m4YNG6b8/Hx5PB5JZ08zORwOJSQkeMd17NhRsbGxys/Pb6jdAgAADczvR1ouZd++faqoqFD37t19lvfo0UOS5HQ61bt3bzmdTkmqNi48PFwnT55UcXGxwsLC5HQ61a1bN1kslmrb27x5c73n26JF7TvQZvN7O8IP/PF957XWPPF9x9WiyUfLsWPHJEkOh8NnedXnVetdLpfsdrsCAwN9xrVt21aSVFJSorCwMLlcLrVp06ba8zgcDu+26spqtSg4OKhe20Dz4XC08vcU0EzwWsPVoslHS5Xzj4zUtLymMVWnhS417mLLL1dlpUcu16laP85ms/JDpRlyuU7L7a68os/Ja6158sdrDagNh6PVZR0RbPLRUnWk5PyjIC6XS9J/j7g4HA6VlZWprKxMLVu2rDauajsOh0NFRUXVnsflclU7mlMXZ87wgwGXx+2u5PWCK4LXGq4WTf5EZ5cuXRQQEKC9e/f6LN+zZ48keW+TrvpYdW1LFafTqaCgIHXo0ME77quvvvIegTl3exe65RoAAPhfk48Wu92u+Ph45eXl+SzPzc1VaGiooqKiJEmxsbFq06aN1q9f7x3jdruVl5enxMRE76mfxMREuVwubdq0yTuuqKhIBQUF3lugAQBA0+P300OnT5/23mpcWFioEydO6IMPPpB09n1WQkJCNHXqVI0dO1azZs1SUlKSCgoKlJOTo3nz5nlvmbbb7Zo8ebLS0tIUEhKiqKgo5eTk6Ouvv1Zqaqr3+fr06aNBgwbp2Wef1cyZM9W6dWulp6erU6dOSk5OvvJfAAAAcFn8Hi2HDx/WY4895rOs6vNVq1Z532p/yZIlSk1N1bp16xQWFqZZs2Zp1KhRPo+bMGGCPB6PVq9erUOHDikiIkJZWVmKjIz0Gffqq69q0aJFmjt3rioqKhQXF6fFixdXu/MIAFB3VqtFVmv9bnCAOSorPaqs9Fx6YD1YPOdf3IE6c7srdeTIyVo/rkULq4KDg/RM+nr9u/BoI8wMTcm1nYK14LFhOnr05BW/OLLqtbZz5TydLt53RZ8bV16rDl0Udf8cv7zWrFaL2gW3ks1qu6LPC/9xV7pVcvR0ncIlJCTo6rh7CABgHqvVIpvVptfzV+nbY8X+ng4aWce2HfRw4jhZrZZGPdpCtAAAGs23x4r1n8Pf+HsauEo0+buHAAAAJKIFAAAYgmgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBGIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGCEZhstX331lVJSUtS3b18NGDBA8+fPV2lpqb+nBQAALqCFvyfgDy6XS/fff786duyo1157TUeOHNHChQtVUlKiV155xd/TAwAANWiW0fLrX/9aLpdL69atU0hIiCTJZrNpxowZmjx5ssLDw/08QwAAcL5meXroL3/5iwYMGOANFkm64447ZLfblZ+f78eZAQCAC2mWR1qcTqdGjhzps8xut6tLly5yOp113q7ValFISFCtH2exnP34/6UMlttdWefnhxlstrP/V2jbtpU8niv73FWvtevu/qk8le4r++S44ixWmyT/vtamD5mkM7zWrnot6vlas1otl/c8td+0+VwulxwOR7XlDodDx44dq/N2LRaLbLbL+8LXpG3rwDo/FuaxWv13oDMgqPrrH1cvf77WHK3a+O25ceU19mutWZ4euhCPxyOLpe7RAQAAGk+zjBaHwyGXy1Vt+fHjx2s8AgMAAPyvWUZLeHh4tWtXysvLtW/fPu4cAgCgiWqW0ZKQkKAtW7bo6NGj3mV//OMfVV5ersTERD/ODAAAXIjF47nS15T7n8vl0vDhw9WpUydNmTJFhw8f1ksvvaRbbrmFN5cDAKCJapbRIp19G//58+fr008/VWBgoIYPH64ZM2YoMJA7eAAAaIqabbQAAACzNMtrWgAAgHmIFgAAYASiBQAAGIFoAQAARiBaAACAEYgWAABgBKIFXosXL1ZkZKQGDhyoysrKausnTpyoyMhIPfzww/V+rg8++ECRkZH65ptvvMsiIyOVnZ1d723j6vHee+/p7rvvVr9+/RQbG6uhQ4fq2Wef1eHDh6/YHBYvXqyYmBjv5998840iIyP1wQcfXLE54Mo6/3t+sXV1/bnFz7u6aeHvCaBpCQgI0NGjR7V161YNGDDAu/zIkSP6+OOP9T//8z+N9txvv/22Onbs2Gjbh1mysrKUmpqqBx54QI8++qg8Ho/+9a9/6f3339eBAwf0ne98x99TBPi5dYURLfAREBCgAQMGKDc31yda8vLy1L59e3Xq1KnRnrtv376Ntm2YZ/Xq1UpOTtbMmTO9yxITE/Xggw/WeCQQ8Ad+bl1ZnB5CNcOHD9cf/vAHlZeXe5fl5uZq2LBhslgsPmP379+vGTNmKC4uTjfccIPGjBmjzz//3GdMRUWFXnzxRfXv31/9+vXTM888o9OnT1d73vMPlw4ePFjz5s3zGXP+aaWqQ/Xr1q3TrFmzdOONNyo+Pt67nd///ve64447FBsbq2nTpsnlctXvi4Mr5vjx42rfvn2N66zW//7oqnqdrFixQgkJCYqJidFTTz2lsrIyffnllxo9erT69u2rkSNHavfu3T7bWbFihUaOHKl+/fppwIABevjhh/XVV1816n7h6nL+zy2Px6OMjAzdfPPNiomJ0bRp05Sfn6/IyEht3brV57GVlZV67bXXdNNNNykuLk5PP/20Tp06daV3wShEC6oZPHiw3G63/vKXv0iSCgsLtW3bNiUlJfmMO3bsmO69917t2rVLs2fP1uLFi9WqVSvdf//9PtccpKam6le/+pVSUlL085//XG63W2lpaQ0655///Odq3bq10tPTNXToUP3sZz/TK6+8olWrVunJJ5/UnDlztGXLFr388ssN+rxoPL169dKvf/1r5eTk6ODBgxcd+9FHH2nLli164YUXNH36dK1fv14vvPCCnnrqKY0aNUrp6ekqLy/XY4895nOUZv/+/Ro7dqyWLFmi+fPnq7KyUqNHj1ZJSUkj7x1McObMmWp/LnWUb/Xq1crIyFBycrIWL16srl276rnnnqtx7Jo1a/Sf//xHL730kqZMmaL3339fS5YsaYxduWpwegjVBAYG6vbbb1dubq73Y3h4uK6//nqfcStXrpTL5VJOTo73+oIBAwZoyJAhys7O1lNPPaWSkhK99dZbmjhxovcC3oEDB2r06NEqLi5usDnHxMR4TyPEx8frD3/4g9asWaMNGzYoODhYkrR792795je/0QsvvNBgz4vG89xzz2natGmaNWuWJKlz58669dZb9cADD6hz584+Yy0WizIyMmS32yVJn3zyiXJycrR8+XIlJCRIOvu/2kmTJumf//yn97X8zDPPeLfhdrt18803a8CAAfrwww/1k5/85ErsJpqoU6dOqVevXjWuu9C1fW63W1lZWbrrrrs0Y8YMSdItt9yiw4cPa+3atdXGX3PNNXr11VclSQkJCfrss8/04Ycfeh+L6ogW1CgpKUnTpk3TyZMnlZubW+0oiyT99a9/VVxcnNq2baszZ85IOnvY/sYbb9Rnn30mSfrnP/+p0tJSDRkyxOexd9xxh7Zt29Zg873pppu8f7fZbPrud78ri8XiDRZJuvbaa+VyuXTy5EkFBQU12HOjcURERCg3N1d/+9vftHnzZv3973/X6tWr9e6772rNmjXq2bOnd+yNN97oDRbp7PfaarUqPj7eZ5kkFRUVeaNl+/btSk9P186dO32Orvz73/9u1H1D0xcYGKg333yz2vJ33nlHubm5NT5m//79OnjwoAYPHuyz/LbbbqsxWm6++Wafz3v06KEPP/ywHrO++hEtqNFNN92koKAgLVmyRP/85z9rPGR59OhRbd++vcb/jXTp0kWSvIf1z7/To6Hv/GjTpo3P5wEBAdX+NxQQECBJKisrI1oMYbfblZiYqMTEREnSpk2b9PDDDyszM1MZGRnecQ6Hw+dxAQEBCgwM9AmZc7//kvTtt99qwoQJ6t27t+bOnav27dsrICBADz/8sHcMmi+r1aro6Ohqyzdu3HjBx1T9vAsJCfFZfv7nVWp63Z57LSGqI1pQI5vNpqFDh2rFihWKiYnRd7/73Wpj2rZtq4EDB+qxxx6rtq7qH4vQ0FBJ0uHDh9WhQwfv+st5nw273a6KigqfZceOHavVfuDqMnDgQF1//fVyOp313tamTZt06tQpZWRkeP/xOHPmDK8x1FnVz7sjR474LD//c9Qd0YILuvvuu1VUVKQf/vCHNa6/6aab9N577yk8PPyC53gjIiIUGBioP/7xj4qKivIuv5xDoGFhYdX+cfrrX/9aiz2AyQ4dOqRrrrnGZ1lpaamKiorUo0ePem+/tLRUFotFLVr898dgXl6e91QnUFthYWEKDQ3VRx99pNtvv927/E9/+pMfZ3V1IVpwQT179rzolewPPPCA3n//fY0dO1bjxo1Tx44ddeTIEe3YsUMdOnTQAw88oHbt2mn06NFavny5AgMDFRUVpdzcXH377beXfP477rhDzz//vDIyMhQTE6ONGzd6r5XB1S8pKUm33nqrbrnlFrVv314HDhzQ6tWrdfToUd1///313n7V9S5PP/20Ro8erT179mjFihXVDtkDl8tms+mhhx7SggULdM011yguLk5btmzx3up87q36qBu+gqiz4OBgvf322+rZs6deeeUVTZgwQQsXLlRhYaFuuOEG77jp06dr9OjReuONN/TTn/5UFotFP/3pTy+5/VGjRmnChAn61a9+pccee0xlZWU1norC1WnatGk6cOCAXnrpJT3wwANauHChgoKC9Mtf/tLnf7F1FRkZqYULF+qLL77Qww8/rNzcXKWnp1e7Pgqojfvuu0/Tpk3Tb3/7W02bNk1Op9N7NxCvrfqzeDwej78nAQDA1SotLU2//OUvtXXrVgUGBvp7Okbj9BAAAA3E6XTqvffeU0xMjAICAvTJJ58oOztb99xzD8HSAIgWAAAaSGBgoLZv365f//rXOnHihDp06KCUlBQ98sgj/p7aVYHTQwAAwAhciAsAAIxAtAAAACMQLQAAwAhECwAAMALRAqDOtm/frkcffVS33HKLevfurZtvvlmPPvpovX6D97Jly2p82/OtW7cqMjLS++6itbFnzx4tXrxY33zzTZ3m5HQ69eSTT+q2225TdHS04uLilJycrHnz5unEiRPecTNnzqz2G34BNByiBUCdrF69Wvfcc4+Ki4s1Y8YM/eIXv9BTTz2l4uJi3XvvvXrzzTfrtN3XX3+9wX9Xy549e5SRkaHCwsJaP3bnzp2666675HQ6NXXqVL3xxhuaO3euEhMTtXnzZpWUlHjHTpkyxee3TwNoWLxPC4Ba+/TTT7VgwQIlJiYqIyPD55cO3nnnnZo2bZpefPFF9ezZU/369fPjTOtv5cqVslqtWrVqlVq3bu1d/oMf/EA//elPde67RnTp0sUfUwSaDY60AKi1rKwsWSwWPf/88z7BIkktWrTQc889J4vFouXLl0u68GmTxYsXKzIy0vt5ZGSkTp06pbVr1yoyMlKRkZG67777LjqXzz77TJMmTVL//v0VHR2tESNGaP369d717777rvd3Vo0bN8673Xffffey9rWkpERBQUEKCgqqcb3FYvH+/fz9rNq/mv7MnDnTO668vFxLlizRD37wA/Xu3Vvx8fF6+umndeTIkcuaI9BccKQFQK243W5t3bpVvXv3VlhYWI1j/vd//1e9evXSli1b5Ha7L3vbb7/9tu6//37FxcVpypQpkuRzdON8W7Zs0YMPPqg+ffro+eefV5s2bbR+/Xo9/vjjKi0t1V133aVBgwbpiSeeUGpqqubMmaNevXpJuvyjIn379tXGjRs1Y8YM/eQnP9ENN9xw2W/HPmrUKA0cONBn2R/+8AdlZ2erR48ekqTKykpNmTJFn376qVJSUhQbG6vCwkItXrxY//jHP/Tb3/6Wt38H/h+iBUCtHD16VKdPn1bnzp0vOq5z5876xz/+4XPNx6X07dtXVqtVISEh6tu37yXHz507V9ddd51WrlzpPeIzcOBAHT16VKmpqRoxYoRCQkLUtWtXSVKPHj0ua7vnSklJ0eeff67c3Fzl5ubKZrMpMjJSCQkJuv/++xUSEnLBx4aFhfmE3f/93//pzTffVFJSklJSUiRJeXl52rRpkxYvXqzvf//73rHXX3+97r77br377ru69957azVn4GrF6SEAjaLqWo9zT580pP/85z/au3evkpKSJElnzpzx/klISNDBgwf11Vdf1ft57Ha7MjMztX79ej399NMaNmyYjhw5omXLlmno0KHau3fvZW3H6XRqypQpiomJ0YIFC7xflz//+c9yOBy69dZbffahZ8+eCg0N1SeffFLvfQCuFhxpAVArwcHBatWq1SVvHy4sLFSrVq3Utm3bRpnHoUOHJEmLFi3SokWLahxz9OjRBnu+8PBwhYeHSzobZCtXrtTChQuVnp6u9PT0iz62uLhYDz74oDp06KCMjAzZ7XbvusOHD8vlcql3796Nvg+A6YgWALVis9kUFxenTZs2af/+/TVe17J//3598cUXSkhIkM1mk91uV3l5ebVx9fkHOTg4WJL08MMPa8iQITWO6datW523fzEWi0UPPPCAMjMz9a9//euiY0+cOKGHHnpIlZWVWr58udq0aeOzPjg4WO3atdMbb7xR4+MvdAEw0BwRLQBq7aGHHtJf/vIXPf/888rMzJTNZvOuc7vdev755+XxePTQQw9JOnt9y+HDh3Xo0CFdc801ks7eMbN58+Zq27bb7SotLb3kHLp3765rr71Wu3bt0hNPPHHRsVVHNi5nu+c7cOCA2rdvX215cXGxTpw44b2wtybl5eWaOnWqCgsL9dZbb9UYeIMGDdLvf/97VVZWqk+fPrWeH9CcEC0Aaq1fv3565plntGDBAt17770aM2aMOnbsqG+//VZvvfWWduzYoWeeeUaxsbGSpKFDh+q1117T448/rgcffFBlZWVavXp1jXcWRURE6JNPPtGGDRsUGhqqoKAgde/evcZ5zJ07VxMnTlRKSoqSk5PVoUMHHTt2TE6nU1988YVee+01SdJ1110nSXrnnXcUFBSkli1bqnPnzt6jNRczZ84cuVwuff/731dERISsVqv27t3rff+WiRMnXvCxCxcu1JYtW/TEE0/o1KlT2r59u3ddSEiIunTpojvvvFPvv/++HnroId1333264YYbFBAQoP3792vr1q267bbbLngkCWhuLJ5z3xkJAGph+/btWrFihT799FOVlJSobdu26tevnyZMmKCYmBifsfn5+UpLS9NXX32l0NBQjR8/XkeOHFFGRoZ2797tHbdr1y7NnTtXX375pU6fPq3+/ftr9erV2rp1q8aNG6dVq1YpLi7OZ/yyZcv0ySefyOVyqV27dgoPD9fQoUM1evRo77iVK1dq1apVKioqktvt1sKFC3XXXXddch83b96s9evXa8eOHSouLtbp06cVHBysmJgYpaSk+NyNNHPmTG9wSdJ99913wQtpk5OT9dJLL0k6exHxqlWr9Lvf/U5fffWVbDabwsLC9L3vfU8pKSneu5+A5o5oAQAARuCWZwAAYASuaQHQLHk8nku+W6/NZmu095kBUHtEC4Bmae3atXr66acvOub862cA+BfXtABolo4ePXrJN8jr1q3bRX/3EYAri2gBAABG4EJcAABgBKIFAAAYgWgBAABGIFoAAIARiBYAAGAEogUAABiBaAEAAEYgWgAAgBH+fxiFSxZOXYw+AAAAAElFTkSuQmCC\n","text/plain":["<Figure size 600x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Outlet Size column\n","plt.figure(figsize=(6,6))\n","sns.countplot(x='Outlet_Size', data=df)\n","plt.show()"]},{"cell_type":"markdown","id":"1fa7051a","metadata":{"papermill":{"duration":0.012091,"end_time":"2023-05-01T14:24:13.110646","exception":false,"start_time":"2023-05-01T14:24:13.098555","status":"completed"},"tags":[]},"source":["### Data Pre-Processing"]},{"cell_type":"code","execution_count":15,"id":"e5abe1a0","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.137234Z","iopub.status.busy":"2023-05-01T14:24:13.136203Z","iopub.status.idle":"2023-05-01T14:24:13.155281Z","shell.execute_reply":"2023-05-01T14:24:13.153843Z"},"papermill":{"duration":0.035471,"end_time":"2023-05-01T14:24:13.158104","exception":false,"start_time":"2023-05-01T14:24:13.122633","status":"completed"},"tags":[]},"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>Item_Identifier</th>\n","      <th>Item_Weight</th>\n","      <th>Item_Fat_Content</th>\n","      <th>Item_Visibility</th>\n","      <th>Item_Type</th>\n","      <th>Item_MRP</th>\n","      <th>Outlet_Identifier</th>\n","      <th>Outlet_Establishment_Year</th>\n","      <th>Outlet_Size</th>\n","      <th>Outlet_Location_Type</th>\n","      <th>Outlet_Type</th>\n","      <th>Item_Outlet_Sales</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>FDA15</td>\n","      <td>9.30</td>\n","      <td>Low Fat</td>\n","      <td>0.016047</td>\n","      <td>Dairy</td>\n","      <td>249.8092</td>\n","      <td>OUT049</td>\n","      <td>1999</td>\n","      <td>Medium</td>\n","      <td>Tier 1</td>\n","      <td>Supermarket Type1</td>\n","      <td>3735.1380</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>DRC01</td>\n","      <td>5.92</td>\n","      <td>Regular</td>\n","      <td>0.019278</td>\n","      <td>Soft Drinks</td>\n","      <td>48.2692</td>\n","      <td>OUT018</td>\n","      <td>2009</td>\n","      <td>Medium</td>\n","      <td>Tier 3</td>\n","      <td>Supermarket Type2</td>\n","      <td>443.4228</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>FDN15</td>\n","      <td>17.50</td>\n","      <td>Low Fat</td>\n","      <td>0.016760</td>\n","      <td>Meat</td>\n","      <td>141.6180</td>\n","      <td>OUT049</td>\n","      <td>1999</td>\n","      <td>Medium</td>\n","      <td>Tier 1</td>\n","      <td>Supermarket Type1</td>\n","      <td>2097.2700</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>FDX07</td>\n","      <td>19.20</td>\n","      <td>Regular</td>\n","      <td>0.000000</td>\n","      <td>Fruits and Vegetables</td>\n","      <td>182.0950</td>\n","      <td>OUT010</td>\n","      <td>1998</td>\n","      <td>Small</td>\n","      <td>Tier 3</td>\n","      <td>Grocery Store</td>\n","      <td>732.3800</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>NCD19</td>\n","      <td>8.93</td>\n","      <td>Low Fat</td>\n","      <td>0.000000</td>\n","      <td>Household</td>\n","      <td>53.8614</td>\n","      <td>OUT013</td>\n","      <td>1987</td>\n","      <td>High</td>\n","      <td>Tier 3</td>\n","      <td>Supermarket Type1</td>\n","      <td>994.7052</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  Item_Identifier  Item_Weight Item_Fat_Content  Item_Visibility  \\\n","0           FDA15         9.30          Low Fat         0.016047   \n","1           DRC01         5.92          Regular         0.019278   \n","2           FDN15        17.50          Low Fat         0.016760   \n","3           FDX07        19.20          Regular         0.000000   \n","4           NCD19         8.93          Low Fat         0.000000   \n","\n","               Item_Type  Item_MRP Outlet_Identifier  \\\n","0                  Dairy  249.8092            OUT049   \n","1            Soft Drinks   48.2692            OUT018   \n","2                   Meat  141.6180            OUT049   \n","3  Fruits and Vegetables  182.0950            OUT010   \n","4              Household   53.8614            OUT013   \n","\n","   Outlet_Establishment_Year Outlet_Size Outlet_Location_Type  \\\n","0                       1999      Medium               Tier 1   \n","1                       2009      Medium               Tier 3   \n","2                       1999      Medium               Tier 1   \n","3                       1998       Small               Tier 3   \n","4                       1987        High               Tier 3   \n","\n","         Outlet_Type  Item_Outlet_Sales  \n","0  Supermarket Type1          3735.1380  \n","1  Supermarket Type2           443.4228  \n","2  Supermarket Type1          2097.2700  \n","3      Grocery Store           732.3800  \n","4  Supermarket Type1           994.7052  "]},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":["df.head()"]},{"cell_type":"code","execution_count":16,"id":"179199f8","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.184576Z","iopub.status.busy":"2023-05-01T14:24:13.184175Z","iopub.status.idle":"2023-05-01T14:24:13.193581Z","shell.execute_reply":"2023-05-01T14:24:13.192379Z"},"papermill":{"duration":0.02526,"end_time":"2023-05-01T14:24:13.195779","exception":false,"start_time":"2023-05-01T14:24:13.170519","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Low Fat    5089\n","Regular    2889\n","LF          316\n","reg         117\n","low fat     112\n","Name: Item_Fat_Content, dtype: int64"]},"execution_count":16,"metadata":{},"output_type":"execute_result"}],"source":["df['Item_Fat_Content'].value_counts()"]},{"cell_type":"code","execution_count":17,"id":"0d522a5b","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.223136Z","iopub.status.busy":"2023-05-01T14:24:13.221909Z","iopub.status.idle":"2023-05-01T14:24:13.230833Z","shell.execute_reply":"2023-05-01T14:24:13.229501Z"},"papermill":{"duration":0.025602,"end_time":"2023-05-01T14:24:13.233682","exception":false,"start_time":"2023-05-01T14:24:13.20808","status":"completed"},"tags":[]},"outputs":[],"source":["df.replace({'Item_Fat_Content': {\n","    'low fat':'Low Fat','LF':'Low Fat', 'reg':'Regular'}}, inplace=True)"]},{"cell_type":"code","execution_count":18,"id":"22dba7f9","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.261446Z","iopub.status.busy":"2023-05-01T14:24:13.260566Z","iopub.status.idle":"2023-05-01T14:24:13.270427Z","shell.execute_reply":"2023-05-01T14:24:13.269225Z"},"papermill":{"duration":0.026314,"end_time":"2023-05-01T14:24:13.272822","exception":false,"start_time":"2023-05-01T14:24:13.246508","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Low Fat    5517\n","Regular    3006\n","Name: Item_Fat_Content, dtype: int64"]},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":["df['Item_Fat_Content'].value_counts()"]},{"cell_type":"code","execution_count":19,"id":"af2c913c","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.300446Z","iopub.status.busy":"2023-05-01T14:24:13.300043Z","iopub.status.idle":"2023-05-01T14:24:13.304922Z","shell.execute_reply":"2023-05-01T14:24:13.303775Z"},"papermill":{"duration":0.021748,"end_time":"2023-05-01T14:24:13.307354","exception":false,"start_time":"2023-05-01T14:24:13.285606","status":"completed"},"tags":[]},"outputs":[],"source":["encoder = LabelEncoder()"]},{"cell_type":"code","execution_count":20,"id":"a3b543ab","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.335119Z","iopub.status.busy":"2023-05-01T14:24:13.334704Z","iopub.status.idle":"2023-05-01T14:24:13.365148Z","shell.execute_reply":"2023-05-01T14:24:13.36401Z"},"papermill":{"duration":0.047526,"end_time":"2023-05-01T14:24:13.367789","exception":false,"start_time":"2023-05-01T14:24:13.320263","status":"completed"},"tags":[]},"outputs":[],"source":["# Change Strings to int for easier use\n","df['Item_Identifier'] = encoder.fit_transform(df['Item_Identifier'])\n","\n","df['Item_Fat_Content'] = encoder.fit_transform(df['Item_Fat_Content'])\n","\n","df['Item_Type'] = encoder.fit_transform(df['Item_Type'])\n","\n","df['Outlet_Identifier'] = encoder.fit_transform(df['Outlet_Identifier'])\n","\n","df['Outlet_Size'] = encoder.fit_transform(df['Outlet_Size'])\n","\n","df['Outlet_Location_Type'] = encoder.fit_transform(df['Outlet_Location_Type'])\n","\n","df['Outlet_Type'] = encoder.fit_transform(df['Outlet_Type'])"]},{"cell_type":"code","execution_count":21,"id":"8739eff5","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.396054Z","iopub.status.busy":"2023-05-01T14:24:13.39502Z","iopub.status.idle":"2023-05-01T14:24:13.411168Z","shell.execute_reply":"2023-05-01T14:24:13.409961Z"},"papermill":{"duration":0.032863,"end_time":"2023-05-01T14:24:13.413791","exception":false,"start_time":"2023-05-01T14:24:13.380928","status":"completed"},"tags":[]},"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>Item_Identifier</th>\n","      <th>Item_Weight</th>\n","      <th>Item_Fat_Content</th>\n","      <th>Item_Visibility</th>\n","      <th>Item_Type</th>\n","      <th>Item_MRP</th>\n","      <th>Outlet_Identifier</th>\n","      <th>Outlet_Establishment_Year</th>\n","      <th>Outlet_Size</th>\n","      <th>Outlet_Location_Type</th>\n","      <th>Outlet_Type</th>\n","      <th>Item_Outlet_Sales</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>156</td>\n","      <td>9.30</td>\n","      <td>0</td>\n","      <td>0.016047</td>\n","      <td>4</td>\n","      <td>249.8092</td>\n","      <td>9</td>\n","      <td>1999</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>3735.1380</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>8</td>\n","      <td>5.92</td>\n","      <td>1</td>\n","      <td>0.019278</td>\n","      <td>14</td>\n","      <td>48.2692</td>\n","      <td>3</td>\n","      <td>2009</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>443.4228</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>662</td>\n","      <td>17.50</td>\n","      <td>0</td>\n","      <td>0.016760</td>\n","      <td>10</td>\n","      <td>141.6180</td>\n","      <td>9</td>\n","      <td>1999</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>2097.2700</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1121</td>\n","      <td>19.20</td>\n","      <td>1</td>\n","      <td>0.000000</td>\n","      <td>6</td>\n","      <td>182.0950</td>\n","      <td>0</td>\n","      <td>1998</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>0</td>\n","      <td>732.3800</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1297</td>\n","      <td>8.93</td>\n","      <td>0</td>\n","      <td>0.000000</td>\n","      <td>9</td>\n","      <td>53.8614</td>\n","      <td>1</td>\n","      <td>1987</td>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>994.7052</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Item_Identifier  Item_Weight  Item_Fat_Content  Item_Visibility  Item_Type  \\\n","0              156         9.30                 0         0.016047          4   \n","1                8         5.92                 1         0.019278         14   \n","2              662        17.50                 0         0.016760         10   \n","3             1121        19.20                 1         0.000000          6   \n","4             1297         8.93                 0         0.000000          9   \n","\n","   Item_MRP  Outlet_Identifier  Outlet_Establishment_Year  Outlet_Size  \\\n","0  249.8092                  9                       1999            1   \n","1   48.2692                  3                       2009            1   \n","2  141.6180                  9                       1999            1   \n","3  182.0950                  0                       1998            2   \n","4   53.8614                  1                       1987            0   \n","\n","   Outlet_Location_Type  Outlet_Type  Item_Outlet_Sales  \n","0                     0            1          3735.1380  \n","1                     2            2           443.4228  \n","2                     0            1          2097.2700  \n","3                     2            0           732.3800  \n","4                     2            1           994.7052  "]},"execution_count":21,"metadata":{},"output_type":"execute_result"}],"source":["df.head()"]},{"cell_type":"code","execution_count":22,"id":"e1fd59cd","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.441914Z","iopub.status.busy":"2023-05-01T14:24:13.441463Z","iopub.status.idle":"2023-05-01T14:24:13.450432Z","shell.execute_reply":"2023-05-01T14:24:13.449267Z"},"papermill":{"duration":0.026301,"end_time":"2023-05-01T14:24:13.453116","exception":false,"start_time":"2023-05-01T14:24:13.426815","status":"completed"},"tags":[]},"outputs":[],"source":["# Splitting features and Target\n","x = df.drop(columns='Item_Outlet_Sales', axis=1)\n","y = df['Item_Outlet_Sales']"]},{"cell_type":"markdown","id":"ad1fbc0f","metadata":{"papermill":{"duration":0.01263,"end_time":"2023-05-01T14:24:13.478856","exception":false,"start_time":"2023-05-01T14:24:13.466226","status":"completed"},"tags":[]},"source":["<a id='2'></a>\n","### Training Data"]},{"cell_type":"code","execution_count":23,"id":"e0284c0f","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.506953Z","iopub.status.busy":"2023-05-01T14:24:13.50655Z","iopub.status.idle":"2023-05-01T14:24:13.51518Z","shell.execute_reply":"2023-05-01T14:24:13.514272Z"},"papermill":{"duration":0.025641,"end_time":"2023-05-01T14:24:13.517486","exception":false,"start_time":"2023-05-01T14:24:13.491845","status":"completed"},"tags":[]},"outputs":[],"source":["x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=42)\n"]},{"cell_type":"code","execution_count":24,"id":"41ca62f5","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:13.546159Z","iopub.status.busy":"2023-05-01T14:24:13.545117Z","iopub.status.idle":"2023-05-01T14:24:14.291197Z","shell.execute_reply":"2023-05-01T14:24:14.290076Z"},"papermill":{"duration":0.763086,"end_time":"2023-05-01T14:24:14.293702","exception":false,"start_time":"2023-05-01T14:24:13.530616","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["XGBRegressor(base_score=0.5, booster='gbtree', callbacks=None,\n","             colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n","             early_stopping_rounds=None, enable_categorical=False,\n","             eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n","             importance_type=None, interaction_constraints='',\n","             learning_rate=0.300000012, max_bin=256, max_cat_to_onehot=4,\n","             max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,\n","             missing=nan, monotone_constraints='()', n_estimators=100, n_jobs=0,\n","             num_parallel_tree=1, predictor='auto', random_state=0, reg_alpha=0,\n","             reg_lambda=1, ...)"]},"execution_count":24,"metadata":{},"output_type":"execute_result"}],"source":["model = XGBRegressor()\n","model.fit(x_train, y_train)"]},{"cell_type":"markdown","id":"610029c3","metadata":{"papermill":{"duration":0.013199,"end_time":"2023-05-01T14:24:14.320989","exception":false,"start_time":"2023-05-01T14:24:14.30779","status":"completed"},"tags":[]},"source":["<a id='3'></a>\n","### 3-Evaluation"]},{"cell_type":"code","execution_count":25,"id":"739da3ff","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:14.349247Z","iopub.status.busy":"2023-05-01T14:24:14.348494Z","iopub.status.idle":"2023-05-01T14:24:14.37297Z","shell.execute_reply":"2023-05-01T14:24:14.371971Z"},"papermill":{"duration":0.041607,"end_time":"2023-05-01T14:24:14.375648","exception":false,"start_time":"2023-05-01T14:24:14.334041","status":"completed"},"tags":[]},"outputs":[],"source":["# Making predictions\n","training_data_pred = model.predict(x_train)\n","test_data_pred = model.predict(x_test)"]},{"cell_type":"code","execution_count":26,"id":"e508e4f5","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:14.406369Z","iopub.status.busy":"2023-05-01T14:24:14.40534Z","iopub.status.idle":"2023-05-01T14:24:14.412743Z","shell.execute_reply":"2023-05-01T14:24:14.411731Z"},"papermill":{"duration":0.024059,"end_time":"2023-05-01T14:24:14.415214","exception":false,"start_time":"2023-05-01T14:24:14.391155","status":"completed"},"tags":[]},"outputs":[],"source":["# R squared Value\n","r2_train = metrics.r2_score(y_train, training_data_pred)\n","r2_test = metrics.r2_score(y_test, test_data_pred)"]},{"cell_type":"code","execution_count":27,"id":"7889d2f0","metadata":{"execution":{"iopub.execute_input":"2023-05-01T14:24:14.444328Z","iopub.status.busy":"2023-05-01T14:24:14.443081Z","iopub.status.idle":"2023-05-01T14:24:14.450131Z","shell.execute_reply":"2023-05-01T14:24:14.448385Z"},"papermill":{"duration":0.024432,"end_time":"2023-05-01T14:24:14.452749","exception":false,"start_time":"2023-05-01T14:24:14.428317","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Training data R squered value: 0.8596212466140883\n","Test data R squered value: 0.5293798650563337\n"]}],"source":["print(f\"Training data R squered value: {r2_train}\\nTest data R squered value: {r2_test}\")"]}],"metadata":{"kernelspec":{"display_name":"Python 3","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":"3.7.12"},"papermill":{"default_parameters":{},"duration":16.671017,"end_time":"2023-05-01T14:24:15.289036","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2023-05-01T14:23:58.618019","version":"2.4.0"}},"nbformat":4,"nbformat_minor":5}