Mayank_Maiti_Clustering.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "f7dc5c8d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  CustomerID        CustomerName         Region  SignupDate\n",
      "0      C0001    Lawrence Carroll  South America  2022-07-10\n",
      "1      C0002      Elizabeth Lutz           Asia  2022-02-13\n",
      "2      C0003      Michael Rivera  South America  2024-03-07\n",
      "3      C0004  Kathleen Rodriguez  South America  2022-10-09\n",
      "4      C0005         Laura Weber           Asia  2022-08-15\n",
      "  TransactionID CustomerID ProductID TransactionDate  Quantity  TotalValue  \\\n",
      "0        T00001      C0199      P067      25-08-2024         1      300.68   \n",
      "1        T00112      C0146      P067      27-05-2024         1      300.68   \n",
      "2        T00166      C0127      P067      25-04-2024         1      300.68   \n",
      "3        T00272      C0087      P067      26-03-2024         2      601.36   \n",
      "4        T00363      C0070      P067      21-03-2024         3      902.04   \n",
      "\n",
      "    Price  \n",
      "0  300.68  \n",
      "1  300.68  \n",
      "2  300.68  \n",
      "3  300.68  \n",
      "4  300.68  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "a=\"E:/DA_Projects/2/Customers.csv\"\n",
    "b=\"E:/DA_Projects/2/Transactions.csv\"\n",
    "customers = pd.read_csv(a)\n",
    "transactions = pd.read_csv(b)\n",
    "\n",
    "print(customers.head())\n",
    "print(transactions.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "e89f9e8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  CustomerID        CustomerName         Region  SignupDate\n",
      "0      C0001    Lawrence Carroll  South America  2022-07-10\n",
      "1      C0002      Elizabeth Lutz           Asia  2022-02-13\n",
      "2      C0003      Michael Rivera  South America  2024-03-07\n",
      "3      C0004  Kathleen Rodriguez  South America  2022-10-09\n",
      "4      C0005         Laura Weber           Asia  2022-08-15\n",
      "  TransactionID CustomerID ProductID TransactionDate  Quantity  TotalValue  \\\n",
      "0        T00001      C0199      P067      25-08-2024         1      300.68   \n",
      "1        T00112      C0146      P067      27-05-2024         1      300.68   \n",
      "2        T00166      C0127      P067      25-04-2024         1      300.68   \n",
      "3        T00272      C0087      P067      26-03-2024         2      601.36   \n",
      "4        T00363      C0070      P067      21-03-2024         3      902.04   \n",
      "\n",
      "    Price  \n",
      "0  300.68  \n",
      "1  300.68  \n",
      "2  300.68  \n",
      "3  300.68  \n",
      "4  300.68  \n"
     ]
    }
   ],
   "source": [
    "a = \"E:/DA_Projects/2/Customers.csv\"\n",
    "b = \"E:/DA_Projects/2/Transactions.csv\"\n",
    "customers = pd.read_csv(a)\n",
    "transactions = pd.read_csv(b)\n",
    "print(customers.head())\n",
    "print(transactions.head())\n",
    "merged_df = pd.merge(customers, transactions, on=\"CustomerID\", how=\"inner\")\n",
    "merged_df.to_csv(\"E:/DA_Projects/2/cluster.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "145bef24",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  CustomerID        CustomerName         Region  SignupDate\n",
      "0      C0001    Lawrence Carroll  South America  2022-07-10\n",
      "1      C0002      Elizabeth Lutz           Asia  2022-02-13\n",
      "2      C0003      Michael Rivera  South America  2024-03-07\n",
      "3      C0004  Kathleen Rodriguez  South America  2022-10-09\n",
      "4      C0005         Laura Weber           Asia  2022-08-15\n",
      "Basic Info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 11 columns):\n",
      " #   Column           Non-Null Count  Dtype         \n",
      "---  ------           --------------  -----         \n",
      " 0   CustomerID       1000 non-null   object        \n",
      " 1   CustomerName     1000 non-null   object        \n",
      " 2   Region           1000 non-null   object        \n",
      " 3   SignupDate       1000 non-null   datetime64[ns]\n",
      " 4   TransactionID    1000 non-null   object        \n",
      " 5   ProductID        1000 non-null   object        \n",
      " 6   TransactionDate  1000 non-null   datetime64[ns]\n",
      " 7   Quantity         1000 non-null   int64         \n",
      " 8   TotalValue       1000 non-null   float64       \n",
      " 9   Price            1000 non-null   float64       \n",
      " 10  DaysSinceSignup  1000 non-null   int64         \n",
      "dtypes: datetime64[ns](2), float64(2), int64(2), object(5)\n",
      "memory usage: 86.1+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "c=\"E:/DA_Projects/2/cluster.csv\"\n",
    "cluster = pd.read_csv(c)\n",
    "print(customers.head())\n",
    "print(\"Basic Info:\")\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "314d1630",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  CustomerID  Quantity  TotalValue  DaysSinceSignup  Cluster\n",
      "0      C0001        12     3354.52            684.2        0\n",
      "1      C0002        10     1862.74            882.0        0\n",
      "2      C0003        14     2725.38             63.0        2\n",
      "3      C0004        23     5354.88            675.0        1\n",
      "4      C0005         7     2034.24            604.0        0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '31-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '31-12-2023' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '31-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '31-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '31-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-12-2023' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '25-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '30-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '16-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '24-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '19-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '28-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '23-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '20-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '21-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '27-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '29-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '13-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '14-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '15-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '22-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '18-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '17-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\1070868925.py:7: UserWarning: Parsing '26-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "df = pd.read_csv(c) \n",
    "df[\"SignupDate\"] = pd.to_datetime(df[\"SignupDate\"])\n",
    "df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
    "\n",
    "df[\"DaysSinceSignup\"] = (df[\"TransactionDate\"] - df[\"SignupDate\"]).dt.days\n",
    "\n",
    "customer_data = df.groupby(\"CustomerID\").agg({\n",
    "    \"Quantity\": \"sum\",\n",
    "    \"TotalValue\": \"sum\",\n",
    "    \"DaysSinceSignup\": \"mean\"\n",
    "}).reset_index()\n",
    "\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(customer_data.iloc[:, 1:])  # Exclude CustomerID\n",
    "kmeans = KMeans(n_clusters=3, random_state=42)\n",
    "customer_data[\"Cluster\"] = kmeans.fit_predict(X_scaled)\n",
    "print(customer_data.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "9c6bc1d8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '31-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '31-12-2023' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '31-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '31-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '31-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-12-2023' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '25-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-02-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '30-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-09-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '16-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '24-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '19-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-01-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '28-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '23-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '20-11-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-07-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '21-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '27-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '29-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '13-05-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-04-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '14-12-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '15-06-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '22-03-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '18-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '17-08-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
      "C:\\Users\\mayan\\AppData\\Local\\Temp\\ipykernel_18564\\519524443.py:7: UserWarning: Parsing '26-10-2024' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import davies_bouldin_score\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "df = pd.read_csv(c) \n",
    "\n",
    "df[\"SignupDate\"] = pd.to_datetime(df[\"SignupDate\"])\n",
    "df[\"TransactionDate\"] = pd.to_datetime(df[\"TransactionDate\"])\n",
    "\n",
    "df[\"DaysSinceSignup\"] = (df[\"TransactionDate\"] - df[\"SignupDate\"]).dt.days\n",
    "\n",
    "customer_data = df.groupby(\"CustomerID\").agg({\n",
    "    \"Quantity\": \"sum\",\n",
    "    \"TotalValue\": \"sum\",\n",
    "    \"DaysSinceSignup\": \"mean\"\n",
    "}).reset_index()\n",
    "\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(customer_data.iloc[:, 1:])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "4af48040",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Davies-Bouldin Index: 0.8390\n"
     ]
    },
    {
     "data": {
      "image/png": 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lcc899+B2u/ne9753yv0jkQg7d+7EarUSHR19Rp/VlssuuwxN0/jb3/7WbP0LL7yA3W7nwgsvPOnxaWlp7N69u8X3ct26dQBtVq47pqKigp07dzJo0KAW2zRNY/DgwQwfPpxIJMKjjz7KuHHjmiUwX/va19i3bx8bNmxoWhcOh3n55ZeZOnVqi5atY90Cz7TYghBCdAUZxC9ELzd9+nSefPJJ7rjjDiZOnMjtt9/OyJEjCYVCbN26lWeeeYZRo0Y1vc2//vrr+fnPf84vfvEL5s6dy549e/jLX/7Sohzs1KlTufjiixkzZgyxsbHs3buXl156ienTpzeNSzn2cPz73/+exYsXYzQaGTNmDOeffz4XXHABP/nJT6itrWXmzJns2LGDBx54gPHjx59Ryd1Tefrpp1m8eDEXXHABN910E+np6VRVVbF37162bNnCq6++elbndbvdvPnmm1x88cWMHz++2USWBw4c4OWXX2b79u1cccUVbZ6jM+71zJkz+e53v8vNN9/Mpk2bmDNnDk6nk+LiYlavXs3o0aO5/fbbT3qtTz31FJ9++ikXXXQRWVlZ+P1+nnvuOYBWJ5o83rx585pmnz9+vNIxu3btahqXU1ZWxueff87zzz+P0Wjk9ddfb9HNEGDz5s1N96i0tJTnnnuOffv2cffdd5+yu9qxhOBU42BGjhzJd77zHR544AGMRiOTJ09m+fLlPPPMM/zmN79p1gXrV7/6Fb/61a/45JNPmiaI/NGPfsTll1/O+eefz913301CQgLr16/noYceYsSIESxevBhonJzy/PPP59prr2Xw4MHY7Xb279/Po48+SiAQ4IEHHmgW1/e///2mctaHDx/mscceo6CgoEWXtG9/+9s8/vjjXH311fzud78jKSmJJ554gpycHD7++OMW17t+/XqMRmOzJEgIIbqtrpqARgjRubZt26ZuvPFGlZWVpSwWi3I6nWr8+PHqF7/4hSorK2vaLxAIqHvvvVdlZmYqu92u5s6dq7Zt26ays7PVjTfe2LTffffdpyZNmqRiY2OV1WpVAwYMUHfffbeqqKhodq5bbrlFJSYmKk3TFKByc3OVUkr5fD71k5/8RGVnZyuz2axSU1PV7bff3mwyPqWUys7OVhdddFGL6wHUnXfe2WxdW5MXbt++XX39619XSUlJymw2q5SUFLVgwQL11FNPNe1zsokVT6akpET95Cc/USNHjlQOh0NZrVY1aNAg9b3vfU/t3Lmzab/WJrLsrHutlFLPPfecmjp1qnI6ncput6uBAweqG264odmkiHPnzlUjR45scY3r1q1TX/va11R2drayWq0qPj5ezZ07V7311lunvD8HDx5UmqapV155pdn6Y/f72GKxWFRSUpKaO3eu+u1vf9vsZ/LEe3j8EhcXp6ZOnaqee+45FYlEmvZt62chOztbZWdnnzJupZQKBoPqgQceaPo3M2TIEPXYY4+1Gddnn33WbP2nn36qFi1apFJSUpTdbldDhgxR//Vf/9Xs++b3+9Utt9yihg8frqKiopTJZFIZGRnqW9/6ltq9e3eLz7rssstUampq08/xTTfdpI4cOdJq/CUlJeqGG25QcXFxymazqWnTpqmPPvqo1X1nz56tLrnkktO6L0II0dU0pWTWKiGEEB3nkksuIRwO8/7773d1KKIVhw4dYvDgwXz44Yecf/75XR2OEEKckiQwQgghOtSuXbsYP348a9eubRrELrqPm2++mYKCAj766KOuDkUIIU6LDOIXQgjRoUaNGsXzzz/foqKX6HrhcJiBAwc2FWUQQoieQFpghBBCCCGEED2GtMAIIYQQQgjRBzz55JOMGTOG6OhooqOjmT59+inHJ65cuZKJEydis9kYMGAATz31VCdF2zZJYIQQQgghhOgDMjIy+N3vfsemTZvYtGkTCxYs4LLLLmP37t2t7p+bm8uSJUuYPXs2W7du5ac//Sk/+MEPWLZsWSdH3px0IRNCCCGEEKKPiouL449//CPf+c53Wmz7yU9+wltvvcXevXub1t12221s3769aWLeriATWZ6CrusUFRXhcrnQNK2rwxFCCCGEECdQSlFXV0daWhoGQ/frYOT3+wkGgx1ybqVUi2dUq9WK1Wo96XGRSIRXX30Vr9fL9OnTW91n3bp1LFq0qNm6Cy64gGeffZZQKITZbD634M+SJDCnUFRURGZmZleHIYQQQgghTiE/P5+MjIyuDqMZv99P/35xlJT6OuT8UVFR1NfXN1v3wAMP8Mtf/rLV/Xfu3Mn06dPx+/1ERUXx+uuvM2LEiFb3LSkpITk5udm65ORkwuEwFRUVpKamtss1nClJYE7B5XIBjf8goqOjuzgaIYQQQghxotraWjIzM5ue27qTYDBISamPozuvJdpladdz19YFyR79jxbPqSdrfRk6dCjbtm2jpqaGZcuWceONN7Jy5co2k5gTW3eOjT7pyp5JksCcwrFvzrFqDUIIIYQQonvqzt39XS4Truj2ffRW6MCZPadaLBYGDRoEwKRJk9i4cSOPPvooTz/9dIt9U1JSWszhVVZWhslkIj4+/hyjP3uSwAghhBBCCNHBdKXQ27l2VnucTylFIBBoddv06dN5++23m61bvnw5kyZN6rLxLyBllIUQQgghhOgTfvrTn/L5559z5MgRdu7cyc9+9jNWrFjBddddB8D999/PDTfc0LT/bbfdxtGjR1m6dCl79+7lueee49lnn+Wee+7pqksApAVGCCGEEEKIDqej0GnnFpgzPF9paSnXX389xcXFuN1uxowZwwcffMD5558PQHFxMXl5eU379+/fn/fee4+7776bxx9/nLS0NB577DGuvPLKdr2OMyXzwJxCbW0tbrcbj8cjY2CEEEIIIbqh7vy8diy2stxvER3dzoP4a4Mk9X+5W153R5IWGCGEEEIIITqY+vJ/7X3OvqjHjIF56KGHmDx5Mi6Xi6SkJC6//HJycnJOedzKlSuZOHEiNpuNAQMG8NRTT3VCtEIIIYQQQoiO0GMSmJUrV3LnnXeyfv16PvroI8LhMIsWLcLr9bZ5TG5uLkuWLGH27Nls3bqVn/70p/zgBz9g2bJlnRi5EEIIIYTo63RUUyWydlv6aAtMj+lC9sEHHzT7+vnnnycpKYnNmzczZ86cVo956qmnyMrK4pFHHgFg+PDhbNq0iYcffrjLBx8JIYQQQgghzlyPaYE5kcfjASAuLq7NfdatW8eiRYuarbvgggvYtGkToVCo1WMCgQC1tbXNFiGEEEIIIc6F3kFLX9QjExilFEuXLmXWrFmMGjWqzf1KSkpITk5uti45OZlwOExFRUWrxzz00EO43e6mJTMzs11jF0IIIYQQfc+xMsrtvfRFPTKBueuuu9ixYwf//Oc/T7mvpmnNvj5WNfrE9cfcf//9eDyepiU/P//cAxZCCCGEEEK0ix4zBuaY73//+7z11lusWrWKjIyMk+6bkpJCSUlJs3VlZWWYTCbi4+NbPcZqtWK1WtstXiGEEEIIIaSMcvvpMS0wSinuuusuXnvtNT799FP69+9/ymOmT5/ORx991Gzd8uXLmTRpEmazuaNCFaJPUkpR6/VTXddARO+rvXKFEEII0dF6TAvMnXfeyT/+8Q/efPNNXC5XU8uK2+3GbrcDjd2/CgsLefHFFwG47bbb+Mtf/sLSpUu59dZbWbduHc8+++xpdT0TQpy+Tfvz+WBjDvsLylFKkRIXzXnjB7NgwiDMRmNXhyeEEEJ0uY4YsyJjYLq5J598Eo/Hw7x580hNTW1a/v3vfzftU1xcTF5eXtPX/fv357333mPFihWMGzeOX//61zz22GNSQlmIdvTBxn38+T+r2HKgAINBw2wycqS0ir++t55n3llPOCKtMUIIIYRoPz2mBebY4PuTeeGFF1qsmzt3Llu2bOmAiIQQxVW1/POzrSgUmUkxTetdDiv1vgArth9i3KB0Zo7s12UxCiGEEN2Bov3LHvfN9pce1AIjhOh+1u4+Qm1DgES3s8W2KLsVXSlWbD/YBZEJIYQQorfqMS0wQojup6SqDo22y5LbrWbyy2o6NSYhhBCiO+qIiSf7aidtSWCEEGfNZjFxst6d4UgEm0Uq/gkhhBC6alza+5x9kXQhE0KctXGD0jGZDPiCoRbbdF0nEIwwQ8a/CCGEEKIdSQIjhDhrYwekMSo7hbLqery+YFOxjUAoTGFFLanxLuaNHXjOnxOO6ITCkXM+jxBCCNFVVActfZF0IRNCnDWT0cAPr5jNU++sY/vhIqrqGgAwGg0MSI3n9kumkxQTddbnz8kv46MtB9h6sBBd18lOjuO8CYOZMaIfBkPr426EEEII0btJAiOEOCcxUXZ+cs18DhRWsDevjIiuk50Uy5iBqec0ieWaXbk8/e566nwBomwWNIPGztxi9hwtIaegnJsXTZYkRgghRI8hg/jbjyQwQohzpmkaQzISGZKR2C7nq6z18uwHX+APhshMdDdVOYuNslPb4Gf5phxGZSczdXh2u3yeEEIIIXoOGQMjOlVE18nJL+OLfXnsy298Wy/EidbtOUp1vY/k2KgWJZqjHTZCEZ3Pth/qouiEEEKIM3esCll7L32RtMCITrP1YCH/WrGNoyVVBMMRzCYj2cmxXDNvHBMHZ3R1eKIbKSj3gFIYDK2/Y3FYzRwuruzkqIQQQgjRHUgLjOgU2w4V8j/LVnGgsJxop430RDdup42DhZU8+trnbD5Q0NUhim7EYj752JmIrmM2nf34GiGEEKKz6WgdsvRFksCIDqfrildWbKfeFyAjwY3dasagaditZjISo6n3BXhl5Xb0vtoOKloY2S8Fo9FAIBhusU0phT8QYpqMfxFCCNGDSALTfiSBER3ucHElh0uqiHc7Woxn0DSNBLeTo6VVHCyq6KIIRXczYVA6QzOSKKmuw3/cJJnhiE5hRS3xbifz22F+GSGEEEL0PDIGRnS4Ol+AUDiC1dz6j5vVbCIYjuDx+js5MtFdmU1GfnTlbB57fTU5+WWEIl40GhPe5Ngobrt4BhmJMV0dphBCCHHalNJQqn1bTNr7fD2FJDCiw7mdNixmI/5gGKfN0mK7PxTCYjLhdtq6IDrRXSW6o3jg+kVfzv1SSjiik50cy+Shma3+HAkhhBCib5AERnS4/ilxDEqNZ/fRUhxWc7NuZEopKj0NDMtMYlBaQhdGKbojk9HA+EHpjB+U3tWhCCGEEOck8uXS3ufsi2QMjOhwmqbxjfnjcTttFJR78PqDhCM6Xn+QgnIP0U4b18wfJ7OqCyGEEEKIU5IWGNEpRvZL4Z6r5/Hvlds5WFhBTb0Ps8nIyOxkvj5vHKP7p3Z1iEIIIYQQHUZhQG/ntgPVR9siJIERnWZkvxQezE4mt6SK2gY/0Q4b/VPiWlQmE0IIIYQQoi2SwIhOpWmaJC1CCCGE6HPUl0t7n7MvkgRGdIpAKMyqHYdZsf0QxVW1uOxWZo3qz4Lxg4iPdnZ1eEIIIYQQHaojJp7sqxNZSgIjOpwvEOJ/lq1i84ECNE3DbjVRWlPHPz7byupdufz46/NkTo8OoJRiX34Zh4orQcGA1HiGZyVJ65cQQgghejRJYESHe2vdbjbuzycpxonNYm5aH9F18spreOa9DTx4wyJ5sG5HZTX1PPHWWvbllxEMhQGwmI0My0zi9ktmkBzr6uIIhRBCiL5FVxp6O0882d7n6yn6ZukC0Wl8gRCfbT+EzWJqlrwAGA0G4qMd7C8oZ39BeRdF2Ps0+IP86T8r2XaoEJfdQkaim4xENy67lW2HivjTf1bi9Qe7OkwhhBBCiLMiCYzoUGU19Xi8PlwOa6vbHVYzwVCY/PKazg2sF1u/L48DBeWkxUfjsFnQNA1N03DYLKTFR3OwsIL1e452dZhCCCFEn6J/WUa5vZe+qG9eteg0RoOGAQ1db71OxrG1JqOx84Lq5Tbm5KFpGmZTy3tqNhnRNI0v9ud3QWQ9T0TXmyZeFUIIIUT3IGNgRIdKjY8mIymGQ0WVOG2WFttrvX6i7FaGZyV1QXS9U70viMnY9rsJk9GA1xfoxIh6nlqvn4+27GfF9kPUNvixmc3MGt2fRROHyPghIYQQZ0WqkLUfaYERHcpoMLBk8jAMmkZlrRelGttclFLU+wLUegPMHNlPHgrbUUaim2A40nSvTxQMR0hPcHdyVD1Hdb2Ph/75CS9/soVyTz0GTaPOH2DZ5zv49d8/Jq+suqtDFEIIIfo0SWBEh5szZgDfnD8Og2Ygv8xDXmkN+WU1eP1BZo/uzw3nT+rqEHuV2aP6Y7OYqG3wt9jm8fqxmk3MHj2gCyLrGf6zajt788tIjXORHOsi2mkj0e0kI9FNYbmH5z7Y2GZyKIQQQrTlWBWy9l76IulCJjqcpml8bdZopg7PYt2eo1TUenHarEwYlC7zknSA4VnJLJ48nLfX7cbrC+FyWtGAWm8ABVw8bTgjs5O7OsxuyeP1s3b3EVwOa4sxREaDgXi3g5yCMg4VVTIoPaGLohRCCNETKTRUO3f5au/z9RSSwIhOkxbv5srZY7o6jF5P0zS+tXACGYlulm/KoaDCA8DAtHjOnziE+WMHSdLYhpKqWhoCIeJc9la3O6xmKmsbKKqqlQRGCCGE6CKSwAjRCxkMGgvGDWLemIFU1nkBiHc5MRgkcTkZs8mIwaAR1hUtS06ArhQGDSytVHgTQgghTkYG8bcfGQMjRC9mMGgkuqNIdEdJ8nIaspJiyUiIobquodXt1XU+YqMcjMiSLnhCCCFEV5EERgghvmQyGrh46nCMBgPlNfVN8xcppaiu9+EPhjlvwhCinbYujlQIIURPc6wFpr2Xvki6kAkhxHHmjBlAna+xbHJhhQcN0AGnzcIl00Zw5ZzRXR2iEEII0adJAiOEEMfRNI2Lp41g2vBsvsjJo7rOh9NuYdLgDDISY7o6PCGEED2UwoDezp2fVB/tTCUJjBBCtCLB7WTJlOFdHYYQQgghTiAJjBBCCCGEEB1MV7T7xJN6H51XWRIYIYQQQgghOpiUUW4/ksAIIYQQPYBSisriavSITmyyG7PF3NUhCSFEl5AERgghhOjGlFJs/GAbn/5zNfn7ClFKEZ8ay+wrpzH/mzMlkRGih1BKQ7VzF7L2Pl9PIQmMEEII0Y198NynvPG/7xMOhYmOd2EwGCjLq+Dfv3+Do7vzufn/fROTWf6cCyH6DvmNJ4QQQnRTRYdKePeZjzFZTCRlJTStd0Tbaajz8cX7WxkzbyRTl0zowiiFEKcjgoFIO5c9bu/z9RR986qFEEKIHmDjB9vwerzEJrtbbHO47Oi6zrq3NnVBZEII0XWkBUYIIYTopsryK9AMBjSt9X7uNqeN4sOlnRyVEOJs6F8u7X3OvkhaYIQQQohuyhnd2MrSlnAwjCPa3okRCSFE1+tRCcyqVau45JJLSEtLQ9M03njjjZPuv2LFCjRNa7Hs27evcwIWQgghzsGoWcMxW0z4vf4W2yLhCEF/kMkXju+CyIQQZ0ph6JClL+pRV+31ehk7dix/+ctfzui4nJwciouLm5bBgwd3UIRCCCFE+xk5Yygjpg+horCK+movSjVOu+2r91N8uJT0walMv3RSF0cphDgdutI6ZOmLetQYmMWLF7N48eIzPi4pKYmYmJj2D0iILpBfXsOGfXnU1PmIsluYNCSTgWnxbfaRF0L0XEaTkVt+9y3+/ptl7Fi1B8/BWtA0zBYTgycO5MYHv05sUssB/kII0Zv1qATmbI0fPx6/38+IESP47//+b+bPn9/mvoFAgEAg0PR1bW1tZ4QoxCnpuuKVldt4Z8NevL5g0/q31u1h9pj+3HLhVMwmYxdG2D6UUpRW1xOORIh3O7G30yR9vkCIDfvy2JSTT50/QEaCm5kj+zM8K0mSP9GtuWKj+N7DN1Cwv4iDW48QCUfIGJLKkEkDMRh6VEcKIfo0HQ2d9v17097n6yl6dQKTmprKM888w8SJEwkEArz00kssXLiQFStWMGfOnFaPeeihh3jwwQc7OVIhTm355hz+8/lO7FYTmUluNE1DKUVdQ4CPNu3Hbbdx7cKeOxeEUooN+/J4d/0eDpdUo5ROtNPO/LEDuWTaCBw2y1mfu9xTz5//s4r9BeWAwmg0sONwMZ9uO8jiycP51sIJGAx984+A6Bk0TSNzaDqZQ9O7OhQhhOhyvTqBGTp0KEOHDm36evr06eTn5/Pwww+3mcDcf//9LF26tOnr2tpaMjMzOzxWIU4mFI7w/sZ9GA0acS5H03pN04h22ghFInyy7SAXTRuB22nrwkgblXvqWbP7CHuOlKJQDM9KZtao/iTFRLV5zIebcvjb8k0EwxFiomwYDWZqvT7+tWIb+wsruOequditzVtjQuEI/lAYh9WMsY030Uopnnp7HXvzSkmNj8byZSuVUgqP18/b63aTkehmwbhB7XcD+gBd1/HV+7HYzJjbqZVMCCF6M9UBY1aUjIHpG6ZNm8bLL7/c5nar1YrVau3EiIQ4tdySKkqq6oiJaj05iYmyU1RRy778MqYOy+rk6JrbfqiIv7y5hopaL8YvWzU27S/gvS/2cvslM5g4OKPFMeWeev69YhtokJH4VX9+u9VMIBhm28FCPtt+kCVThgOQV1bD8k05rN97lFA4QkyUnfnjB3H+hCE4T2ipOVBYwZ6jpSS4nU3JCzQmfzFRdhr8IZZvymHemIHSCnMaGup8rHp1HWve+AJPeS0mi4mJi8Yy75oZpA9K7erwhBBC9AF9rvPs1q1bSU2VP7KiZwlHdJRSbfZ3N2ga6sv9ulK5p56/vLmG6roGMhLcpH+5ZCS4qan38cRbaymuajmubMO+PDxePwnRzhbbrBYTBoPGZ9sOoZQiJ7+M3/z9I97ZsAd/KITBoFFSXceLyzfxx1c+o94XaHb8gcIKAuHGVprWRDutFFR4qKz1ts9N6MW8tQ08/sPneOXhtyjLq8BgMhDwBfn4pZX8z3ef5uC23K4OUQghui0dQ4csfVGPuur6+nq2bdvGtm3bAMjNzWXbtm3k5eUBjd2/brjhhqb9H3nkEd544w0OHDjA7t27uf/++1m2bBl33XVXV4QvxFlLT3ATZbdS3xBodXu9L4jDaiYzsWurEa3emUtFrZfU+OhmrRkGg0ZafDRVtQ18vrPlQ26Fx9u0X2scVjMVnnr8wTB/fW8DFR4vmUkxxEc7iXbaSIlzkRQbxfbDxby9bk+zYxUK1KljP41d+ryPXlzJnrU5JGbEkZSVgCs2iriUGNIGpVJVUs3ff7OMSDjS1WEKIYRow0MPPcTkyZNxuVwkJSVx+eWXk5OTc9JjuuO8ij2qC9mmTZuaVRA7Nlblxhtv5IUXXqC4uLgpmQEIBoPcc889FBYWYrfbGTlyJO+++y5Llizp9NiFOBdup42ZI/vxzvq9RNktWMxf/dMNR3Sq6hqYNjybrKTYLowSdh0pwWjQWk1ENE3DbDKwI7eIr88d22ybw2pB0TgupbWKYKFwhGinnX35peSVVZMYE4XhhP2sZhN2i4mVOw5x+axRTdXLBqbGYzEb8QVCrRYCqPUG6J8aR3y0o8U2gMPFlazYfojth4pQwMh+KcwfO5AhGYmneVd6B39DgDVvfIEtyoblhPtoMGgkpMdTsL+Ivev3M2rW8C6KUgghui+lGpf2PueZWLlyJXfeeSeTJ08mHA7zs5/9jEWLFrFnzx6czpa9II6Xk5NDdHR009eJiV33d7BHJTDz5s1rmsSrNS+88EKzr++9917uvffeDo5KiM5x9ZyxHCmtZveREoxGA3aLiUAoQjAUZkBqPDdfMLmrQ2wzAWmi0WpTx/hB6byxZif1viAuR/MxaLqu4wuEuGjqcIqr6gjrCpul9V9dTruV2oYA1XUN2OMbW6OGZSYxLDOZbYcKSTMZm5Warv1ydvPzJwxptQjA6l25/PXd9dQ2BLBZTWjAB1/s5fOdh7nh/Iksmji0xTG9VXVpDd4aL842Ej2r3UIkrFOWV9HJkQkhhDhdH3zwQbOvn3/+eZKSkti8eXObBa6O6U7zKvaoLmRC9GXRThv3fWMBtyyZSr/kOExGI6lx0dxw/iR+/q3zSY51UVZTz+4jJRwuriSid/54mOFZyYTDeqsvGpRSBEM6I7KTW2wblBbPtBH9qK73UVPvQz8223ggRGFFLanx0SwcPwSryQRKNW0/USSiYzBozZIUTdO4/ZLpDElPpKS6nsJyD6XVdeSV1eALhrhwyjAWjG9ZgayospZn39+ALxQiM8lNUkwUiTFRZCbFENF1Xvp4M4eLK8/2VvU4ZqsZzWhos4uYrje+WjS3MdZICCH6uo4cA1NbW9tsOX5Ow5PxeDwAxMXFnXLf8ePHk5qaysKFC/nss8/O/ka0gx7VAiNEX+e0WVgyZThLpgxv1tpRVOnhhQ83svVgAb5gGJPRQHZSLJfPHMW04dmdFt/s0QN4f+M+iivrSI13NcWnlKKkqo7YKBtzRg9ocZymady6ZCp2s4nPd+VSWO4BDcxGI0MzErn1ommkxLkwGDSi7FY8Xj+xUfZm52gsi+xj7ID0FsUAkmNd/OL681m/9ygb9uVR7wuSmehm5qj+jOmf2mqr0ZpdudTU+8hMimm2XdM0Et1O8ss9rNxxmAGp8e1x67q9+NRYBozOZs/aHJxuR4t7VldVh9PtYPi0wV0UoRBCdG8dOZHliVN+PPDAA/zyl7886bFKKZYuXcqsWbMYNWpUm/udzbyKHU0SGCF6qGMPkCVVdfzuX5+SV1ZDTJSdRLeTUCTCgcIK/vf11fiDYeaNHdgpMaXEufjexdN56u115Jd7msoWB0JhYqPs3LJkGhmJMa0ea7eYufWiaVw6YyS7jpQQDuukJ7oZnpXU1L0rKSaKOWMG8N6GvRg0jWiHFU3TiOg65TVebBYzF00b3mpCEmW3ct6EIZw3YchpXcv+wnKMRkOr59I0DavZyL68stO8M92PUoqiylpq6n24HFYyE2NO2v1P0zTOv2Euh7YfoTy/kvi0WIwmI0op6qu91Fd7Oe/6OSSk942ETgghupP8/Pxm41NOZ0qQu+66ix07drB69eqT7nc28yp2NElghOjh3lq3m7yyGjIS3U0P+maTEUeiheKqWv712VamDstqMQlkR5k6LIuMBDcrdxxi95FSlFKM7JfMnDEDyWwjeTlecqyL5FhXm9uvP28i4YjO5zsPk1/mQTMACuKiHVy3YEKr88ycDaPBcNLBkbpSmIw9sxfuwcIK/r1yG3uOlhEMhzEbjQxOT+CqOWMY3b/tMvNj5ozgup9dyWuPvEvJkXI0rbHrmD3Kxtyvz+CqpZd04lUIcW7CoTC71+ZwaOsRIhGdjCGpjFswCns3mAxY9E4d2QITHR3dLIE5le9///u89dZbrFq1ioyMM/+7eap5FTuaJDBC9GB1vgDr9hzF5bC2Ogg90e2kpKqeLQcLmTmyX6fFlZ7g5toFE9rtfPW+AF/k5FNY4cFsNDB7VH8unDSUbYeL8PlDJLidTBmWhbsdHzxG90/li315RHS9xb3VlSIU0hk/KK3dPq+zHCys4Pf//oxyTz1xLgdup5VgKMKO3GKOlFZz95WzGTcwvc3jZ14+hdFzhrP1k11UFVdjc1oZPWcEGYNlfi3Rc5TlV/B/9/2d3J1Hm8Z1aZqB5OwEbvr1NxgysXNarYXobEopvv/97/P666+zYsUK+vfvf1bn6ep5FSWBEaIHq2vwEwiFcdpbb10xGRu7cFXXN3RmWO1q8/4C/vr+Bsqq64DGImavr9nFqP6p3HXZzBZjYdpSXe8jv6wGg0FjQEpcqyWVjzdjZD/e3bCXoi+LCBxrbYnoOsWVdSS4ncwaNYBAKExOfjmBUJhEt5Ps5NiTV2LrQkop/r1yG+WeerKOG9tjNhlx2MwUVHj4x6dbGd0/tdWE+JjoOBdzr57eWWEL0a6C/iDP/PglDm3LJTEzAau98XdBOBim5EgZf/3Jy/z4+TtJykzo4khFb6OUhlLt+/fhTM9355138o9//IM333wTl8tFSUkJAG63G7u98e/p/fffT2FhIS+++CLQOK9iv379GDlyJMFgkJdffplly5axbNmydr2WMyEJjBA9mNNmxWwyEAxFcLTS3fVYJTKX/dR9Ybujw8WV/OXN1dT5As2SiAZ/kM378/nLm2v42TcXtjkBJjS2Ur2yYhurd+VS7wuCBnEuB+dPGMxlM0Y1q1h2vNgoOz/82iwee2M1xZW1KGhq+E+MieKOS6azI7eIt9btobS6jkhEx2YxMyI7mW8tnEC/lFNXdOlshRUe9hwtI87VchC+pmkkuJ0cLa0mJ7+81WpxQvQG2z7bTe7OoyRlJ2I5rmutyWIidUAyRQdLWPfWJi6788IujFKIjvHkk08CjVOTHO/555/npptuAugR8ypKAiNED+Z22pg0JJNPth4g2mlrMbljZW0DsVF2xp+kS1B3tnzzfmq8fjIT3c0euB02C4ka7MotZk9eKaP6pTRtq673sWrHYdbtPUKt109ZdT31/iAJbieJsU6UAk+9j398to3yWi+3XDiVw8WV1PuDxLsczVpQhmYm8btbLmLdniPk5JejK8Xg9ASmj+jHml25vPjRZjQNEqIdmIxGGgJBNu0voKjSw8+uPY/0BHen37OT8Xj9BMNh3M7WE1qb2UR5KEJ1va+TIxOi8+xZl4Me0ZslL8cYDAasditbPt4hCYxodx05BuZ0nWw+xWN6wryKksAI0cNdMm0EO3OLKSj3kBDtwG41E47oVNU1oOtw2YyRRPfAQakRXWdjTj5Om7nVLlkOq4WKmgZ2Hi5uSmAKymt4+NWVHC2rxmw04AuGKauuw2g0YDWbiHPZG8sgx0RR1xDgvQ372HawCE+9j1BEx2o2MSQjkWsXjGdIRuMMwy67lUUThzabtNLj9fP6ml0YjRpJMVFN66PsVhxWC/nlNbyzYS/fu2haB9+lMxNlt2I2GgmGIq22PAXDEcwmQ49tsRPidIT8IQwn6SJpMBkIBUKdGJEQ4kz1zBI6Qogm/VLiuOfqeYzKTqbOFyS/3ENZTT2xLgffuXAKF08b0dUhnpVIRG91AP3xNA1CkcYBuLquePLtdRwtrSI9PprU+GjCkQgmkxGLyUhFrZdyj7fp2GA4THlNPQeLKoiOspEa78JhNbP9UCF/fGUFh4ranlF+84ECqusaiG9lVnqDQcNlt7Jh71G8/uA53IH2l5UUw6D0BCrrGlp9C1fh8ZIW31i6WojeKn1wKrquGidfbYW/3k/WiPapZijE8XQFutLaeenqq+oa0gIjRC8wJCORX910IQcKKyj3eLFbTAzPTsZu6bmzoptNRjIS3OzLKyOmlYH64YgOmkZafGPZyD15pRwsqiAxJgrjl2NlgqEIRk3DZDQQ1nUqPF4S3VEopVNcVYdCYbeYm+6T027BYTOTV1bDa6t38uOvz281ttoGP5qmtZlcWS0mfIEwXn8Q5ymKBXQmTdO4es4YjpZWU1jhId7txGY2EQxHqPB4sZpNXD1nTJvjgoToDSYvHs+Hf1tBRWEliRnxzVp4ayvrMNvMzLh0chdGKHorHQN6O7cdtPf5egpJYIToJTRNY0hGYlPXp55O0zQWjB9MTn45Xl8Qp/2rREApRVl1PYluJ1OHZwNwpLSKUERvNt+N2WQkEAoDYDIYCQTDhMIRfMEggWAYo2Zommzz+M+NjbKz43AxZTX1zbqIHRPjbEyoIhG9KVk6nj8Yxmo2EtWNkpdjRvdP5UdXzOYfn24lr6ya8nAEs9FARkIMV88Zw8xRZ1dSU3QcpRR7Nxxgw7ubKdhfjMNlZ/yCUUxePB5XbMufz45UfLiUwoMlGE0GBo7rR3Rc23M2dVeJGfF8/Z5L+cdDr1F4sBhntBODUcPracBoMnL+DXMZPXt4V4cphDgJSWCEEN3WnNED2HOkhJU7DlNT78NptxDRFV5fAHeUnVsWT20ar2HQNJRSKKWa3qjGRTuo8wW+7CqimsqIhcKN3dNMRkOrrTtWi4mGOh8er7/VBGbi4HTiXA4qar0tJt2M6Dr1vgAXTx1xylLNXWX8oHRG909lf0EZ1fV+XHYrw7OSpOWlG9J1nf/8+W0+/ftqAv4gVruFcDDM7jX7WPnqOm77842k9u/4inGVxdX8+w9vsHtNDg21PjSDhjvexcyvTeHSOy9sdUB8dzbz8ikkZMSz6tV17F6bg1I6o2YNY9YV05i0aGy3LYUuejaFhmrnQfztfb6eQhIYIUS3ZTIauO2SGYzol8KnWw9QUOHBajYyc2Q/zp8whEHpX83TMCwzCbvFjNcfJOrLpCbOZaeqtoG6Bj8RpXA7rBg0jYZAEF1XRLtsrQ5YDwTDWEzGNifGdDlsXDV7DM8v/4KiylriXPbGKmT+INX1PjITY7r92COT0cCI7JRT79gNKKXI3ZlHyZEyzBYTQyYNxJ1w+jNO92Tr397MRy+uxBHtIDEzvml9OBQhb28Bz//3v/jJi3dhNHZc8llXXc8TP3yOQzuOEpMYTfqgFHRdp7ayjvf+72Pqquq56dff6HEP/UMnDWTopIFEwhF0Xcfcg7vcCtHXSAIjhOjWTEYDC8YNYv7YgQTDEYwGQ9N8MMfrnxLH2IGprNtzFJPRgM1ixmgw0D8llkNFldT5ghgMBkqr64hxNs6DYkDjxJdXSilq6n1MH9Gv1daXYxZNGoLVYuKttbsprPQQ0RvngZk5sh/fnD+elHPoWhOKRNhxqJhthwrxBcOkxrmYMbIfqXF946H9eAUHivnnb1/j0PYjBH1B0DSi413MvnIql95xQa9+6FRKsfLVtShdER3X/GfRZDaSkB7PkV155HxxkBHTh7ZxlnO37q1N5O7MI7VfEiZL42OD0WAkNjkGs9XMhve2MPuqaQwa13b3w0g4QsmRMvSITmJmArbWJq7qIkaTESPS+ig6nvpy4H17n7MvkgRGCNEjaJqG1dz2ryxN0/jeRdPxBcLsPlJCWPdi0DR0XZEU6+LaBYMZkZ2M0WhgUFoCO3OLefLttY2D2aMdWExGfMEwlbUNJLijuGLW6FPGM2/sQGaO6sfhokr8wTCJMU7S4s9t7pfqeh+PvvY5u4+WEA7raBooBW+t280354/nwsnDzun8nSUYCLFnbQ6e8lrsLjsjZwzB6Xae0TkqCit54ofPUZxbRlxKDAnpcShd4amo5b1nPsbvDXDdz67soCvoerWVdRQeLGlznIvNaaWyOMKR3QUdmsCsf3czJoupKXk5ntPtoLrMw7ZPd7WawCilWP3aBj7712qKD5ehlMKdEM2sr03h/BvndatERgjRc0gC00spvQr0WjBEoxm634zgQnSEmCg7P7t2IVsPFrL5QAEN/hCp8S5mjOhHv5Tm/w5mjeqP0WBg2ec7yC+vIfzlPDBj+qdy3cIJzbqnnYzZaGRoZvuUHVZK8eRba9l2qJDk2ChsX7YuKKUo93h58aPNJMZEMXFw9y7xuuWTnSz7n7cpPVqBiuigQUySmwu/vYDzvjXntLsarXx1HUWHSkkflILhy1Y3zagRmxyD0VTH2je+YO7XZ5AxOLUjL6fLaJqGBihar5OqlAKl6OieW7UVdVhsrbd0aZqGQdOor/a2uv2tJz7gnac/BhTueBeawUBtZR2vP/YeR/cW8t0/Xt/jxs8Icbb0DmiBae/z9RSSwPQyKnwE5fsPBDeACoJmQVmmoNmvQjNJdaGeIhRunA29IRBix+EiNuzLo94XIDMxhtmjBzBpSMZJ50fpy8wmI1OGZTFlWNYp950+IpvJQzM5WFSB1xck1mWnf0pcl/XlP1BYwc7cYhLczqbkBRofEpNiosgv9/DBxn1MGJTebccb7Fqzj+d+9g/89X4S0uMwW81EwhGqSz28+vBbGAwGFl43+5TniUQibHh3Cw6XrSl5OZ4rLoqigyXsWLmn1yYwrrgoMoelk7PxYKutMH5vALPVzIAx2R0aR1xqLId3HG1127HCGTFJLVse83MKWf63ldgclmbbbU4rfq+fbZ/uZNMH25hxmZQsFkKcGUlgehEVPoiq/TVEisEQAwY3KD/4P0KFdkL0L9BMg7o6zD5LKUVY1zEZDG0+fPqDYT7YuI9Pth6gpLqesurGuUrczsbB5vllNXyxL4/54wZx65JprY4FEWfGZDQwrJ1aUM7VnrxSAqHGrmitiXZY2Z9fTr0vgMvReoGBrqSU4v1nP6GhtoG0gSlNP+dGk5GE9DjKCyr54PlPmXHZJOytVH87XtAfanxAb6OSm6ZpoGk01Da0+3V0F5qmMe+amRzcmktNmQd3YnTTPQ0Fw1QWVTFi+lAGTxzQoXFMv2QSB7fmEvQFsdibfz9qK+uxu+yMP69ll8vNy3fQUNtAeisJps1pQ6ka1r21URIY0WfoaOjtXDWsvc/XU0gC00sopVDevzUmL8Zs0L58sNXsoLkhkofyPg/Rv+m2b257q3JPPZ9uPcjKHYfxBULERzuYN24g88cOajbJYSAU5pHXVvHFvjzMJgNVtQ0EQmEMmoan3k+0w05mUgz1vgCfbDlA/5S4HjMeQpyeSERHQ2vz36hB0wihE+6mUy+X5JaRuyOPmER3q9cQm+ymLK+CvRsOMmHhyccY2RxW3AkuyvIqWgxgh8bywrTx5r83mXzhOIpzS/nwuc8oPFCCyWIiEo6gaTBwXD9u/s03MHRwa+y0Syayafk2dq/NIcrtICrGif7lWKRwMMIFN88ja1h6i+MqiqrQTvLCxua0UXq0vENjF6I7kTLK7UcSmN4ichRCu8CQ8FXycoxmAEM8hPZAJBdMHfu2TnyloLyGP7zyGfllHmwWExazkbyyap57/ws27svnnq/Payrju2LbITbm5JMQ4yQc1imqrMVuNWEwGAiGwhRW1OB2WomyW6ltCPDR5v2cN2GItML0IllJsRgMGoFQuNWCBXUNAfqnxuHuhq0vAL56P+FwBLO19T8tJrMJpSv89f5TnkvTNGZePoVX/vgmoUAI8wnjJKpLPETFRjH+FIlQT6dpGpfefgGjZw3ni/e3UHSwBFuUjXHzRjH+vNHY2yj13Z7sTht3/M9NvPXkh3zx7lYqi6sxGAzEp8cx/xszWXDtrFaTlKgYB0rX2zxvKBAiKq53TLwrhOhcksD0Fnp5Y3cxQ3zr2zUH6NWgVwCSwHQGpRT/9/4X5Jd5SE+MbhqzEhNlJxAKs+NwMa+v3skN509CKcWn2w9iMGjYLWZKvXXousJobjzGYjLhD4aprveRFBNFtMNKSXU9VXUNJy31K3qWcQPTyEqKIbekivSE6GZv1ut9ARSK8yYMxmDonm/cYlNisNot+Or9WFrp+uVvCGCymIhNiTmt882+cipbP9tFzhcHiYpx4Ix2EIno1JTXYjQauPz7i4lPjW3nq+h+NE1jwJjssxrrUlddz4Z3t7Bp+Ta8NQ2k9Eti6sUTGb9gFMYzmLjU6Xbyzfuu4KLvnk/x4TKMJgNZw9Jb/T4fM2bOCD795xoa6nw4XM27DIZDEULBMFMWTzjjaxKip5IuZO1HEpjeQnOAZgKCQGt9y0ON2zVHJwfWdx0sqiSnoIx4t6PFgHur2YTDZmbVzsN8bdZobGYTpdV1OL58y9xYe0hrmlX+2MvNYCgCgAK+HALQpxwpqWLljsPsySvFqGmMGZjGnNEDSIvvHfOjmE1Gbr9kBn9etpKC8lqsFiMmowFfoLEr4YJxg1gwbnBXh9mm2CQ34+aP5PNlG4iKcTZ7QFZKUVVcTfaITIac5pgNp9vJnY/ezLvPfMQX72+jprwWg1Eje3g6510/l2kXT+yoS+kVyvIrePLuFzi6Ox+j2YjZYqLwUAnbPtvF1IsmcOOvrjnjeXSi41xEn+YcR0OnDGLs3BFs+nAb4WC4sRCBBg11PqpLasgansH0S+R7KIQ4c5LA9BamoWDMhPBRMLVSYlWvAGNW436iUxRWeBrnBmlj7guXw0p1nY/SqjoGpMZjMRnx+oMAOO0WDAaNiK4wGbWmIqrH3rx76v0My0wiIfrM5tXoyT7bdpDnP9xIXUMAq8WIUrA3r4yPNu/njktndPvSwqdrUHoCv7zhAlZuP8TaPUfwBUKMyEph7tiBTB2W1e27DF78vUUc3pFH4YFiXHFR2JxWQv4QnopaYhLdXH3PpWf05j86zsU377uCS267gPL8CkwWE2mDUjp05vneQCnFi798hSO78kjpn4zJ/NX9aqj1se6tTWQMTefCm+d3WAxGo5Fv/79v4oxxsunDbRQdKgHA6rAwevZwvvXzq3AnnP7Lh2AgxK7P91KSW4bJYmLY1MFkDk2TcZ2ix5Ayyu1HEpheQtNMYL8aVf8oRIrAkAiaGVSosXsZJjT71Wia1NvvLCajoXEOhy9bUQLBMFX1DTT4Qxg0DavZiMGgYTY1/v+MEf14Y+0u4lwOHFYz0Q4r1fW+pokMDQaNaLuVqtoGjAYDF04e2mf+cB8uruT5DzcSDIfJTPpqgLhSiqLKWp56ex0PfWcJCWc4UWJ3lRQTxdVzx3L13LFdHcoZS85O5IdP3sr7z37Clo93UFdVj8lsYtIF47jg5vknna39ZKJinES1UZ1NtHR4x1EObs0lLiW2WfIC4Ii2U1/jZfWy9Sy8btYZt8KcCXuUnZsevIYltyzk4JZcIhGdjMEp9BuVdUa/v3I2HeLlX71K8eFSlN5YutnmtDFuwUi+9fOrW3RRE0L0bpLA9CbWeWiEUA3/gEgJoAMaGJPQHNeCtePetPUVSjW2hZzOH94RWclEO23U1PtRQH55DaGwjqYpUBrhSAR3lB39y3OeN2Ew6/YepbDCQ1JsFNnJsUR0HY/XT0RXOG1mqup8OO0Wrp4zhlmj+s68Pit3HKKuIdAseYHG70NqXDQFFR5W787l8hmjujBKcUxSZgI3/vIavvaDJXjKa3FEO/rEWJXuJH9fIUFfiIT01gf5u+KiqCyupqKgitQByR0eT1JmAkmZpzc57IkKDxbzzI9fpKbUQ0JmPBarGaUU3poG1r21iXAowu1/vqnPvNARPZdSGqqdW0za+3w9hSQwvYimaWBbBJZZENraOGjfEAPmCWgGGftyLg4WVvDJtoNsPVBARFcMzUxkwbhBjD/JhIJx0Q7mjx3Eqyu3Ue31owF2ixE0jVAoAjS20PzljdX89jtLyEiMYemVc3j63fXkl9WgK4XNYsZmNhPjsjMkPZHs5Bimj+jHgNQ2ijX0UruPlGK1GFu91wZD40zg+/OlHGt3cybjJUT70gwGoO1y20pvbBlubZLQ7mblq+uoLK4mY1Aq2pfdaDVNIyrWiWbQ2LFyD4e2Hznr1j0hRM8jCUwvpBkcYJ3Z1WH0Gmt2H+Hpd9ZR1+DHYbOgaRprdx9h0/4Crpg1iqvnjG0zifnG/HGs2nGIitoGDJqGP9g4CN9kNJCRGEOcy8GR0mo27S9g5sh+DM1M4ve3XMSOw8UUVnowGQ2M6pdKVlJMJ15x92M45ZtV1W0rcwnRFQaO64c9ykZ9TQOu2JZd72or68gank5CRlwXRHf6IpEIW5bvwOmyNyUvx3NE26ku9bB7TY4kMKLbkxaY9iMJjBAnUV5Tz7Pvb8AfDJGZFNOUqMRHO6iua+D1NbsYlpnMmAEtZ5oGsJiMGI0GMhPdoGlEIjpmk5HYKDtWS+M/P13XyckvY+bIfkBjJaqJQzKYSO8YlN4exg5M5UBhedN4ouNFdB2lYHhWx3eDEaKnyBicyui5I1j/9mbMVhM2R+N8U0opaivqQIN535jV7YshREIRQsEQJkvrjyuapqEZIOgLdnJkQpy5CBqRdi573N7n6ym6f9uxEF1ozZ4jVNf7SI51tXhwjnU5CATDrNh+8KTn0HWF1WImLT6azKQYUuJcTckLAJqG3k1nVu8uZo8eSEyUneLKuqYxQ9CY/BVX1pEU62LGlwmgEKLRtT+9grFzR1Bd6qHgQDHFh0spPFBMOBRh8S0LmfW1KV0d4imZrWYSM+JpqPO1uj0S0UFBQkbf6lYrRF8nLTBCnMSRkio0jTa7J9msZvYXVrR5vKZpDMtKYu2eI8TTchxSONI4BVX/lO7djaOrZSXFcNvF03n6vfUUlHkwGjWUAl0pkmNd/ODymcRGSRUiIY4XHefirr98h12r97F9xW68ngaSshOZtGgs/UZm9ohB75qmMeuKqeT+Kh+/14/N+VVRAqUUFQWVxCS5mXj+mC6MUojTozjZyLSzP2dfJAmMECdhMjbON9IWXdcxn2IQ7IJxg9i0v4CqugbiXF8lMbpSlFTVkRLnYsrwrPYK+YT4FOWeenSlSHA7MXfz7iInM3V4Nv1S4li9K5f9BeVomsaofinMHNmPWJcUqRCiNWaLmfELRjN+weiuDuWszbhsMrvX5rDlox2YLCacbgeRcIS6qnrsLjtX33Mp0fFSLEKIvkQSGCFOYnS/FD7bdpBQOIL5hMn3lFL4g2EmDck86TnGD0rnqtmjeW31LvLLarBZTER0RTAUIcHt5PZLZuCyW9s1bqUUq3Yc5oNN+8gr8wCKxJgozpswmAsmDm1xLT1FcqyLK2fLm1Yh+hKLzcKtv/8WKyas5fNl66kurcFgNDBx0Vjmf3MWI6YN6eoQhTgtCgNKte/oDdVHR4NIAiPESUwZlkW/5FgOF1eSEh+N5csH/3BEp7S6jgS3k/njBp70HJqmceXsMQzLSmbVjkPkFJRjMRmZNCSTuWMGktLOZWaVUryycjvLPt+JrhRupxVN0yiurOX5DzaSW1zF7ZfM6PYzugshxDEWm4VFN85j4XWzqa2qx2wxycSmQvRhksAIcRJ2q5m7r5zDo69/Tm5xFWFdBxrL+ibFurj94umkxbtPeZ5j3Z1G9Uvp6JDJLanirXV7sFqMzbqsOW0WvL4gq3YeZvLQTKYNz+7wWM5WOKJT4fECkOB2UlTpYdWOw+zJK8WgaYwZkMbs0f1JjYvu4kiFEJ3JaDISm3Tq37lCdEeKxinG2/ucfZEkMEKcQkZiDL+5eTGb9heQk19GRNfJTo5l+vBsXI7WZ7nuSuv2HKHBHySzlT/yTruF6nofq3Yc7pYJTETX+WTrAZZv2k9xVS3QWFa6uq4BDQ2rxYRCsftIKR9uyuGOS2cwcbCUmxZCCCH6EklghDgNVrOJmSP7Nc3V0p0VVdZhNGptVhiyWkwUVnjaPL7eF2DNriOs3nWYaq+f5JgoZo8ewPQR2VjNHfcrQynFC8s38f4Xe9E0DbfThj8YJie/cf6X1DgXybFRaJqGUoqiylqeensdv/3OYhLdUR0Wl+h8R/fks/r1L9ixag8qojN4wgBmXD6FEdOH9IjKWUII0RpdaejtPPFke5+vp5AERohurLqugd1HSwmFI6QnuBmcnnDKBzinzUzkJPPKhMIRnHZLq9sqa708/MoKcgrKMRg0rGYTxZW1bDtUxNrdR7j7yjnYreZzuqa27DpSwkebc3DZrUR/WSq1us6HQdMwmQ1U1HqJcdmJdtjQNI3UuGgKKjys2X2Ey2eM6pCYROfb+OE2XnrwVeqq6rBH2dAMBta9vYktn+zgktsuYPEtCyWJEUL0SApDuw+6l0H8QohuIxSO8K8V2/h06wE8Xj+KxlagIRmJfOfCKWQnx7Z57MQhmXy67SD+YAibpXmyEY7ohCN6m5M+Pv/hRvbml5EWH92sUpk/GGLj/nxeW72D6xZObI9LbGH1rlwCoQjJsV8VNahrCGAwgNloxBcOUVXrI/rLbnsGg4bRoLEvrwxmdEhIopNVFlfzj98sw1fvJ31w6leJSkoM1aU1vPP0cgaMzWbYlMFdG6gQQogu1TfTNiG6MaUUz3+4kddX7yQc0UlPiCYz0U2U3cLO3GL++OoKymrq2zx+wqB0RvdLpbTaS11DAKUUSika/EGKKjz0T4lj9qgBLY4rKK9h26EiYl32FmWWbRYzDquZFdsPU+8LtPs1AxRWeJqqvDU57kW7QdPwh0LNNisFx55xc/LLePKdtXz/L6/zg8ff4NkPNnC4uLJDYhUdY+P7W6kp95CUFd+ilSU2OQafN8C6tzZ1UXRCCHFudNUxS18kCYwQ3czR0mpW7jhEtNNGXLQDg8GApmk4bRbSE6IpKK/ho805bR5vNhn50ZVzmDmyH4FQmIJyD/llNVTX+xickch/XTUHt7Nl8YGjpdV4/cE256SJdljxeP0nHT9zLqLsVsKR5vVZoh1WdF01Vm5RYDJ89StL13V0pRiRlcyHm3L49d8/Zvmm/VTWein31PPOuj08+OJyVu/K7ZB4Rfs7urcAg9GAwdD6nya708rBbUc6NyghhBDdjiQwoonS61GBVSjfu6jAWpTqmDft4uQ2HyigIRAi2tEykTAaDDisZj7fdYSI3nYxRrfTxj1Xz+WXN1zA1GFZOGwWlILiylqefncDa3YfQanmr200g4YGLdYfoyuFptHmw+W5mjIsC4BgONK0Lt7lxGwy4g80trzERNkbY9EVRZV1JMdEkRYfzcsfbyai62QmukmMiSIpJorMpBh8oRDPvr+BosraDolZtC+T2Yh+kteJekRhtkjPZyFEz6QAhdbOS98kCYxo7GLkextVczuq9iFU/f+ian+Dqr4DFVjV1eH1OQ2BEJpGmwOVLebGB/rjH/RbE9EVH23OYWNOPsFwhJgoG2aTkd1HSvjf1z/nzXW7m+0/NCORaKcNj9ff6vk8Xj9JMVFkJcWc1XWdyvTh2QzJSKS4shavL4hSCqvFSFJMFJEvkyd/IExhhYeCCg8J0U7uvGwm2w8XU+8LkOh2NrtnmqaREuuipt7PGmmF6RGGTh6EpmmEg+EW25SuCPgCjJk7ogsiE0II0Z3IqywB/vdR3mcAAxjTQDOBCoJegqp7FDQbmmVKV0fZZ8S67KAaWxkMhpZJjC8QJjUuGtspShpv2p/PZ9sP4Y6yEXVctzCXw0plrZdln+9gwqB0spIaCwLERzuZNao/767fi8VswmlrrFSmlKK2IUAorLNo4pAOK6Vst5pZetUcnn5nPXuOllBV3wCAzWxi4bjBDM5IoKC8BoNmYGS/FGaN6kd8tJOXP96M1WJqNeHTNA2jUeNAYUWHxCza14TzxrD8hRXk7y8kOTupqbUlEo5QmldBXEos0y+d1MVRCiHE2VFKQ7Vz2eP2Pl9PIQlMH6eUD+V7FdDAeNws8ZoFDOkQyUM1vALmyVK6tJNMHZbFqyt3UFnrJTGm+fwmwVCYUDjC/HGDTvn9WLH9EBFdNUtejolzOcgrq2HtnqNNCQzAdQsmUFPvY2NOPpWeBgwGDV3XsVstLJkyjMVThrfPRbYh0R3Fz65dyIHCiqYB+APTEhiU1nJQ9zEmoxG9jW5v0DjQ32SUxuaewOGy892Hb+Cv975Ewf4i9IgOWmPXxvj0OG588BpS+yd3dZhCCCG6WI9KYFatWsUf//hHNm/eTHFxMa+//jqXX375SY9ZuXIlS5cuZffu3aSlpXHvvfdy2223dU7APUFoF0RKwdjKQ4GmgSEBwgchkgumlpWrRPtLdEdx9dwxvPzRZgoraomNsmE0Gqj3BfD6gozqn8rC8YNOeZ6C8hrsbYwX0DQNo8FA8QljQ+xWM3dfOYfdR0rZmJNHTb2fBLeT6SOyT2sOmvagaRpDMhIZkpF4WvuPG5jG7qOl6EphOCG+iK6jlGJU/5Q2jhbdTcbgVO7/+w/Z9ukuDmw9jB7WyRqewcRFY4iOc536BK0IBUNs+Xgn69/ZROmRcqJinExePJ6pF00463MKIcSZ0tHQaeeJLNv5fD1Fj0pgvF4vY8eO5eabb+bKK6885f65ubksWbKEW2+9lZdffpk1a9Zwxx13kJiYeFrH9wnKC0SANiYn1MygwqAaOjOqPu+iKcOJdth4d8Ne8stqiOg6LruV88YP4YpZo1ttVTmRw2ahzNN2uWVd13HYWn7fjQYDYwakMmZA6jldQ2vCEZ2IrmMxGdstGZo9egDLN++nqKKW1HgXxi+LDIQjOsWVtaTERTNjRL92+SzROWwOK9Munsi0i899zqGgP8hzP/snm5ZvQ+kKq8NKeUEVB7fmsuaNL7jjkZtJykxoh6iFEOLkpAtZ++lRCczixYtZvHjxae//1FNPkZWVxSOPPALA8OHD2bRpEw8//LAkMMcYEkGzgvKB5mi5XTWAZmtsiRGdRtM05owewMyR/Sis8BAKR0iKdbVZ4rg104dnc6CwgoiuNz3UH+MPhjAZjUwYlNHeobfqSEkVH23Zz4a9eYR1ndS4aBaOH8TcMQNbzDlzplLiXHz/8lk88dYaiioaW5QUjfcwLT6aH3xtdlP1MtH3fPTiSr54fwtxKbHYo74qHx4ORTi6O5+//+Y//Oip70kXWSGE6EF6VAJzptatW8eiRYuarbvgggt49tlnCYVCmM0t3z4HAgECga/KB9fW9vLyq6bhYBoIoT2gZYF23IOuioBeDdaFaEbpgtMVjAZDszEqZ2LumIF8tv0g+eUeEmOc2C1mlFJ4/UEqaxsYNzCdcQPT2jnilrYfKuKxN1ZTWeslym7BaDBwsLCCAwXl7Mwt4a7LZp5zEjNmQCq/u+Ui1u05ysGixgH7wzKTmDYi+4ySPtG7BP1BPn9tAxabpVnyAo0lm2NTYti/6TBHdufTf1RWF0UphOgr9C+X9j5nX9SrE5iSkhKSk5uP7UhOTiYcDlNRUUFqassuMg899BAPPvhgZ4XY5TTNAM7voGp/C5GjYIj9qkVG94AxE83xza4OU5yFuGgH91w9jyffWsuh4ioqIl4AbBYz04Zn872Lp59z4nAqvkCIZ95bj8frIysppuktd0yUnQZ/kDW7chmRlcwFk4ee82fFRNlZPGXYOZ9H9B5l+ZXUlHlwxTpb3e5w2akp9ZC/r1ASGCGE6EF6dQIDLefSODZJX1vdBe6//36WLl3a9HVtbS2ZmZkdF2A3oJlHQfQDKN8yCG1pTFw0G9gWo9mvRjN1Tjcj0f6ykmL5zbcXsyu3hKNl1RgMGsMykhh4kqpe7WnzgQJKqupIjo1q8XkOm4Uar5+Ptx7g/IlDWi0ZLcS5MBg0NIOGamtyTAVoYJAqdUKITiBjYNpPr05gUlJSKCkpabaurKwMk8lEfHx8q8dYrVas1r7X5UQzD0Uz/xQVqQBVB4YYNMPZdV0S3YvRYGDswDTGdkJ3sRMVVHgA1WZLT5TdQml1Hd5AULp6iXaXnJ1ISr8kCvYXYXe1HAdVV+PF4bIzaHz/LohOCCHE2erVr52mT5/ORx991Gzd8uXLmTRpUqvjXwRoxgQ0U39JXkS7MBsN6Oqrls8TRSIKo0GTeVpEhzCajMz/xkxQ4CmvbfZz6Kv34ymvZfyC0aT0S+rCKIUQfcWxFpj2XvqiHvXUUF9fz7Zt29i2bRvQWCZ527Zt5OXlAY3dv2644Yam/W+77TaOHj3K0qVL2bt3L8899xzPPvss99xzT1eEL0SfM7p/KjaLiQZ/qMU2pRR1vgDjBqVjt8gLBdExZl85jcW3LiQcjlB4oJjiw6UU7C/CU1HLhPNG8437Lu/qEIUQQpyhHtWFbNOmTcyfP7/p62NjVW688UZeeOEFiouLm5IZgP79+/Pee+9x99138/jjj5OWlsZjjz0mJZSF6CSD0xMYNzCN9XvyQAOH1YymaUR0nbLqelx2K+dPGNLVYYpeTNM0vvb9JUw8bwyblm+nPL8SZ4yDcfNGMWL6EIwdXMhCCCGOkYks20+PSmDmzZvXZlcUgBdeeKHFurlz57Jly5YOjEoI0RZN07jjkhkoBdsOFVJZ29D0qzY+2snNF05mRHbySc8hxLnSNI3sEZlkj+jdBVmEEN2bUo1Le5+zL+pRCYwQvUEwFKai1ovJaCTR7ez1E+i5HDZ+cs189uaVsSO3mFA4QnJsFNOGZRPttJ36BEIIIYQQx5EERohO4g+GeXfDHj7bdpCqOh8Gg0b/5FgWTx3O9OHZvTqR0TSNEdnJ0toihBCiz1Id0IVMSRcyIURHCYTCPPr6KjbszcNiNuKyW9GVYk9eGQeKKqiqa+DiqSO6OkwhxDmKhCP46v1Y7BYsVilOIYQQHUESGCE6wec7D/PFvnwS3E7sxz3URNmtlHu8vLpyO5MGZ5IS5+rCKHseXyBEMBwhym7BaOhRRRVFL+OtbWDlK+tY88YGaivrMZmNTDhvDPO/OYuMwaldHZ4QohuQiSzbjyQwQnSCFdsPoWk0S16OiY92UFDuYf3eo1w+c1QXRNfz7Dlayoebcth+uAhdVyTGRLFw/CAWjh+M1Sy/1kTn8nq8PPGjF9i7fj9mmxl7lJ1QIMQn//ic7St2c9ufbpTJMoUQoh3JK0shOphSiqLKWhxtdCcxaBooqPB4OzmynmndnqP87l+fsmrHYXSlMBo18suqefb9L/jfN1YTDIW7OkTRx3z4wgr2rMshMTOBpMwEXLFOYpNjSB+USlVJDX//f8uIhCNdHaYQooupDlr6InlVKUQH0zQNp81Cuae+xTalFOFIhIgewWqW+ShOpa7Bz/MffoE/GCIzyd1U+CDaYaMhEGL9nqOM7p/KBZOGdlgMoXCEbYeK2JdfRkTXyU6KZcqwLJw2S4d9pui+fF4/697ehD3KhsXW/CWFwaCRkB5Hwf4i9m44wKiZw7ooSiGE6F0kgRGiE8wa1Z9/fbaNiK5jNBhQSlFT76O8xkudL4CuK77IyScrOZY5owectCKZ1x/kSEkVulJkJ8X2qVLEG/blUeHxkhYf3eIeOaxmajSNT7cdZNHEIR1S1a24qpZHX/ucQ0WVhCM6aAqDppHyeTR3XDKDkf1S2v0zRfdWU+qhvtqL0+1odbvVbiES1inLq4CZnRycEKJb0ZWG3s5jVtr7fD2FJDCi11KRIgisBr0SNCdYpoBpaJeUK14wbhCf7zxMYXktCW4HNV4/xZW1RHQdpSDaYaWospbH31xDXlkN31o4oUWcwVCY19fs4pOtB6iu9wGNLQ9zRw/g6rljWx1f09uUVNUBYDS23vvVabdQWlWHPxTGbmnf++EPhvmfZas4UFBOcpyraaxNOKJTUlXHo69/zi9vuIC0+Oh2/VzRvZltZgwmQ5tdxHRdBxTmPvDvUwhxcjKIv/3IGBjR6yilUA2voGp+iPI+i/K9gWr4O8pzH6r+f1Aq0OkxJcZEcc/V8xiWmUi5x0t+WQ3hiI7ZZCQ5NoohGUlkJLqxW828t2Evu46UNDs+ous89c46/r1iG/X+IAluJ4luJ4FQiNfX7uKR1z4n1Af62FvMpsY+v21MPRyO6BiNBszG9u+Ot2l/PoeKKkmJj25WKMBkNJCWEE25x8vK7Yfa/XNF9xafGsuA0dl4Kmpb/bmsrazH6XYyfNrgLohOCCF6J0lgRO8T+ATV8CKoCBizwNQPjNmg2cH/Icr7QpeE1S8ljt98ezHThmXhcljpnxLH8Kxk+qXEYTQ2vkGJibLjD4VZvTO32bG7cktYs/sIcS4HiW4nFpMRs8lIfLSTxBgnmw/k80VO/hnHpJSirKaegvIafMFQu1xnRxo7IBWr2USDv2WsSim8vgBThmVhaqOF5lzsOFyMUgqLqWVyZNA0rGYjG/ef+fdA9GyapnH+DXOxO22U51c2tcQopaitrMPr8TLz8ikkpMV1caRCiK4mg/jbj3QhE72KUmGU701QCkyJX23QNNCigVBjgmO/Es2Y0OnxGQ0GguEIMVF2kmKjWt3HajZypLS62bq1e48QDEdw2lsOFLdbzCgFa3blMnNkv9OOZWNOPu9u2MvBogp0XRHtsDJ3zEAumT6CKLv1jK6rswzJSGTi4HTW7D6CQuG0WdA0jVA4QllNPbEuB+dP6Jg33aFIhJNNeGw0GKQCWh81Zs4Irvvvq1j2yDuUHClD0zSUrrC77Mz/xkyu+NFFXR2iEEL0KpLAiN4lUgCRfDDEtr5di23cHtoJxvmdG9uXHDYLkYje5vZwRMdxQjWjCo/3pK0KFpORspqWVc7a8snWAzz3wRf4gmFinDaMRgO1DX5eWbmdnIJy7v36PBzdsKqWpmncdskMNE1jy4FCqut8TWOFUuJcfHfJNAakxrfLZ1XWejlUVImmaQxIjSMrMQalQFeNA/dP5AuEmDQks10+W/Q8My6bzOg5w9n6yU6qSmqwOW2Mnj2M9EEyiaUQopFCQ53sTdhZnrMvkgRG9DJhQAetrTEQ2nH7dY2JgzNYt+cIoXAE8wndkcIRHV1XTBma1Wx9vMtx0qQnGI4QH916FaQTVdf7+MenW4noOpmJ7qb1DquZQCjMjtwiPt56gEunjzyDq+o8LruV/7pqLoeKKtl1pIRQOEJqfDQTh2S0y8B9rz/I3z/ZwtrdR6ht8AMQ7bQxdkAq0Q4rZdX1JMdGNSuyUFPvw2I2Mm/swHP+fNFzuWKjmHPV9K4OQwghej1JYETvYkgBQzTodWBspbyw8oJmBWPXvSmfOiyL979IYH9hOUkxUU3Vw/zBEGXV9fRLiWPGCV3Bpg7P5rPth2jwB1u0jASCjcnYice05Yt9eVTXNZCW0LJaltVswmw08unWg1w8dQQGQ/d8s6NpGoPSExiU3r7dAIOhMI+8topNOQW4HName1Tr9bNqZy7p8W4iuo/8cg9OmwWDBvX+EGajgUunj2TcwLR2jUcIIUTvIWWU248M4he9imaIAstCUPVwYrUxFQG9AszDwdRxEx2eisNmYelVcxndPxWP109+eQ35ZTVU1/kYmpnEf101F/cJc7uMHZDGlKFZVHgaqKptIBLRieg61fU+SqvrGDMglanDsk/r8ys8XqBxzEar8VnNVNc34O8Bg/rb28b9BWw9WEhSrJNYlx2jwYDRYCDW5SAxxklJdR2XTR/JwvGDsZpNGI1GJg5O5+4r53DtgvFdUqJbCCGE6GukBUb0OprjalRkPwS3gWYAzQEqCMoPxmw05x1d/qCZEufilzcsYveRUg4UlgMwIDWe0f1TWx3rYjIauOuymSS4nazacYjiqjqUUrgcNi6YPIzrFk7AZjm9f87HWnyUUq3eh2A4gsNqwWxu/1LE3d36PUfRdYWtla5odosZXfeSX1HD0ivnousKXakOqXgmhBCiF1Ja49Le5+yDJIERvY5miALXzyHwMcr/MehlYEhEs80H6yI0Y+KpT9IJjAYDYwakMmbA6Q3ytVvN3HzBZC6fOYrDRZXoStEvJZZEd+vVzNoyYVA6yz7fQV1DgOgTWnp0XeH1B1k4fnC7zKWilGJ/QTl788uIRHSyk2MZOyCtxdif7qKqvuGksZlNRqpqGwAwGDQMfXTwpBBCCNGVJIERvZJmcID9UjT7pSgVAQxd3urSXmKj7EwcknHWx2cnxzJrZH8+2rKfiFK4HTYMBg1/MER5jZfkWBeLJg455zir63088dYaduaWEAyF0dAwGDSykmK4/ZIZ7T5+pT0kRjvZe7S0ze2hcISkmDNLGHuSisJKdn6+D1+dj5hkN2PnjcR5msUhhBBCnJyuGpf2PueZeOihh3jttdfYt28fdrudGTNm8Pvf/56hQ0/etX7lypUsXbqU3bt3k5aWxr333sttt912DpGfG0lgRK+ntVmRrG/SNI1vL56C2Wxk1Y7DFFZ4gMZuaoPSErhlyVQyEmPO6TNCkQiPvraKbYeKSHA7ccQ40TSNQChMbkkVf162kgdvuIDEbpYMTB/ZjzV7jrRaLMHrD2I0Gpg+ol/XBNeBIuEIr//ve6x8ZR3eGm/jPCY0zjJ/xY8uYvolk7o6xB5LKUXp0XL83gBxKTFEx7u6OiQhRBfpDmWUV65cyZ133snkyZMJh8P87Gc/Y9GiRezZswen09nqMbm5uSxZsoRbb72Vl19+mTVr1nDHHXeQmJjIlVde2R6XccYkgRG9ilIRSVhOg9Vs4pbFU7l0+kh25hY3liKOi2Zkv5R2GdOx7WARu4+Ukhwb1Ww8idVsIj0hmoLyWlZsP8TVc8ee82e1pwmD05k6LIs1u4/gCISautjVev00BELMGtWf8YPSuzjK9vfO08t5//8+xe6ykTowGYPBQDgUobKoipd/9SqOaDtj53bPstrd2a7Ve/ng+c/I3XGUcDiCzWll4vljWXLreSSkxXV1eEKIPuiDDz5o9vXzzz9PUlISmzdvZs6cOa0e89RTT5GVlcUjjzwCwPDhw9m0aRMPP/ywJDBCnC2l14B/OSrwCegelCEWzXoe2M5HM7QsFSy+khQTxcLx7T9z/fZDRYR1vdXB8AaDAavFyNo9R7pdAmM2GrnrslmkxUfz2bZDTRXbYpx2Lpo6nCtnj+l1g/Y9FbWs+NdabE4rsUlfzQtkMhtJykqg6FAJy19YwZg5I3pNN8zOsPmj7Tz/3/+koc5HTKIbp8WEr97Pp/9czcGtufzwye8Sn9rGhLtCiF5JKQ3VzoPuj52vtra22Xqr1YrVaj3l8R5PYy+MuLi2X6qsW7eORYsWNVt3wQUX8OyzzxIKhTCbz30OtjMlCYzo0VSkDFX7awjvb5zfRbNCpADlfQaCn0P0L9AM8qazs/mCoZM2apuMBnzBrptM9GRsFhPXLpjAJdNHkldaDTSOG4qyn/oPQU+0b8MBPJV1pPRParFN0zRiEt3k7sqjLK+C5OzuUQCjuwv4Arz6p7fxNwRJG5jSlPhZ7RZcsU7y9hay/G+f8c37rujiSIUQvUVmZvP57R544AF++ctfnvQYpRRLly5l1qxZjBo1qs39SkpKSE5ObrYuOTmZcDhMRUUFqamnV4yoPUkCI3o05X0OwjlgzADtuDcAKgihPSjv39Bcd3ddgH1UWnw0SrVdqrkhEGZkdkznB3YGXHYrI/uldHUYHS7gCwJgbKNlyWQ2oof1pv3Eqe1avY+KgkoSMuJb/PwbTUaiYhxsfH8bl925GIfL3kVRCiE6W+PfxfY/J0B+fj7R0V/1Ojmd1pe77rqLHTt2sHr16lPue+LvMvXlB3dVy3zv6gsh+hQVKYTgRjDENk9eADQLGNwQXIuKlHVNgH3Y9BH9iHZYm7pgHa/eF8Bo0Jg7dmAXRCZOlJARj8lsxN8QaHV7Q50Pe7Sd+NSYzg2sB6su9aB0hbmNuZlsTht+rx9PRW2r24UQ4kxFR0c3W06VwHz/+9/nrbfe4rPPPiMj4+SVTVNSUigpKWm2rqysDJPJRHx8/DnHfjYkgRE9VzgfVANobVT10aJB90KkoHPjOk5ZTT3vrN/Dy59s4a11uymq7BsPLGnx0Xxj/nhAI7/cg8frp64hQFFFLR6vnwVjBzFlaFZXhymAoZMGkjk0jcqiKtQJ9TjDwTD1NQ1MWTwOp7v16jSiJYfLjgL0iN7q9lAghNFsktYXIfoY1UHLGcWgFHfddRevvfYan376Kf379z/lMdOnT+ejjz5qtm758uVMmjSpS8a/gHQhEz2ZZgI0QAdaqzwWAc3QsnWmEyilWPb5Dt5at4c6XwCNxl8yr67azuLJw7hm3jiMht79/mDxlGEkxUTxwaZ97M8vJ4TOgLR4Fo4fxIJxg3vdYPieymgy8s37r+DJpS9QcKAYV6wTs9WM3+vHV+9n0Pj+LP7Owq4Os0cZOXMo7ngXNWUe4k4YqK+UwlNRx/RLJ+FOkCIjQojOdeedd/KPf/yDN998E5fL1dSy4na7sdsbX6rcf//9FBYW8uKLLwJw22238Ze//IWlS5dy6623sm7dOp599ln++c9/dtl1SAIjei7TMDAmgF4FxuSW2/VqMCSBqf2rbJ3K8k37+ffK7VjNRjIS3Rg0DaUU1fU+Xlu9C6fNwmUz2h4w11tMHJLBhMHp1PsChPWvJs0U3cug8f350VPf5eOXV7H9s90E/EGiYpycd8NcFl47u8sftJVShAIhzFZzj6iE5k6I5rzr5/DG/75PZVEVMUlujKbGbnpVRdXEJrtZdMPcrg5TCNHJusM8ME8++SQA8+bNa7b++eef56abbgKguLiYvLy8pm39+/fnvffe4+677+bxxx8nLS2Nxx57rMtKKIMkMKIH0wxRKOsSaPhbY7KixYCmfTlKrhpUCM1+MZpm69S4gqEw72zYg0HTiI/+qtuNpmnEuRyUhet5f2MOiyYOxW7tmqbXzqRpGi5H534PxJnLHJrOzb/+Jg11PvxeP1ExTiwnTObZ2SqLq1n1n3VseGczvno/0QkuZl42hdlXTu32XdoW37IQg9HAxy+vovRIOYrGgghZIzK45t7L6D86u6tDFEJ0tg4oo8wZnk+dRhWBF154ocW6uXPnsmXLljP6rI4kCYzo0TTHVSjlAf+HoB89boMT7FeB7bJOj+lgUSVlNfXEttG/PdZlp7zGS05BGeMG9r5JEcXZU0pxuLiS9XvzqKj1Eu2wMnloFiOykjut5crhsneLsRnFuaU8/oPnKDxQjM1pw2w1U3a0glf++CZbP9vFnY/eTHRc953V3mAwsPg7C5lz1TT2rD+A3xsgPi2WoZMGYjTJZLtCCHEuJIERPZqmmcD5XbCdD8H1oHsaq5JZpqOZuuYNZygcIaLrbY5xMRoMRHSdQDDSyZGJ7iyi6/z94y18uDkHrz+IwaChdMUHG3OYNjyb2y6Zjr2ViUF7I6UU//rd6xQeKCZ1QPJxD/wuQoEQOV8c5J2nP+La+7v/PCpOt5PJF4zr6jCEEN1AR5ZR7mskgRE9nqZpYBrQuHQDafHROKwW6n0BYqKav8kOhiIUVNRQU+/nsTc+J3NNDPPHDmLO2AF95uFUtO7DTTm8tW43TruFrKSYprEeXl+QVTsPE+208Z0Lp3RxlJ0jb28B+zcfJjY5pkVrhdlqJirGycb3tnLx987v1q0wQgghOoaUARKinSXGRDFpSAYer5/wcWVUfYEQOflllFbVYzYaMRoMHCqq5On31vOnV1fS4JeJAvuqUDjCBxtzMBoNxETZmw1Ud9otRNktfL7zMFW1DV0YZecpyS0j4A3giG69K5vT7cBb20BZXkUnRyaEEGevO5RR7i0kgRGiA3xzwXgGpSVQVFlLWXU9nno/+wvKqfcFcTmsDM5IINZlJy0hmkS3g80HCnhr3e6uDlt0kaOl1ZTV1BET1XqxgxinjVqvn30FfWNSVpPFBJrW5jwqkXAEg9HQ5kSRQgghejdJYIToAInuKH523XlcO388sS4HDYEg4YhOSlwUQzISsB334GWzmLFbTKzYfghfINSFUYuuoiuFUmBoo0SwpmmNEyPqfeNd2+CJA3AnuPBU1LW63VNRS0q/JDKGpHVyZEIIcY6U1r5LHyUJjBAdJDbKztVzx/K/d13OjYsmkeh20i8lDou55VvjKIcVj9dPWU19F0QqulpafDTRDhu1DYFWt9f7gjisjWNj+oLoOBezr5yGv95PbWVdU9lPXVdUldQAGgu/NUeqeQkhRB8l7e9CdDCjwYDTZm18i64ap6o5ka4rDJoms9P3UVF2K3PHDGDZ5zvx20PYjivoEApHqK7zMX1ENllJsSc5S+9yye2L8NX7WfPGFxQeKEEzNFbbiYpx8rUfLGHW1/pGQQMhRO+hKw29nVtN2vt8PYUkMEJ0ghHZyUTZrXga/MRGtRyYXFPnY1B6AqlxXTvjueh4Sin2F5SzaudhDhZWYjEbmTgkg/ljB3G0tJotBwvRAJvVRCAUIRLRGZyRwM0XTu7q0DuV2WLm2p9ewZyrprFj5R68ngbcidFMOG8MiRnxXR2eEEKcuY4Ydd83eha3cEYJTHFxMZ988glxcXGcd955WCxfzdLs9Xr505/+xC9+8Yt2D1KInsQXCFFaXYfJaCA1PhqjwUBSTBSzRvXn/Y37MBkNRNksaJqGrhRVtQ0YjQaWTB3eaZMViq6hlOKNNbv4z+c7aPAHsVpMRHTFriMlLN+Uwx2XzmT6yH6s3H6I0pp6MhJtzBrVn7mjB+BytD7AvzfTNI3MoelkDpUJX4UQQnzltBOYjRs3smjRInRdJxQKkZGRweuvv87IkSMBqK+v58EHH5QERvRZDf4gb67dzYodh6j1+hsfvpJiWDJlGHNGD+D68yfiC4ZYv+co1bU+Gl+baLgcVr4+dxyzR/Xv6ksQHWzrwUJeWbUdo8FA5nFzvei6TmFFLc+8u57f33IRC8YNavX4Wq+fLQcLqW3w43bYmDAkA5fd2pmXIIQQ4iwpNBTt+6Kyvc/XU5x2AvPTn/6UK664gr/+9a94vV7uu+8+5s6dy0cffcT48eM7MkYhuj1fMMSflq1iy4EC7BYTLqcVXVccKqrkibfWUl3v4/IZo/jB5bO4cNJQthwoxBsIkhDtZNrwbFL6yGR8dQ1+1u09ys7DJYQiEQalxTNzVP8+03Xu020HCQTDZJ4wGN9gMJAS56KwwsOm/fnMHt18UlalFO9v3Mdrq3dSXedrWh/ncnDV7DEsmjSk2dwx4uxUl3nI21uApmlkj8jAndA3fi6FEKKnOe0EZvPmzTz++OMYDAZcLhePP/442dnZLFy4kA8//JCsrKyOjFOIbm3V9sNsPVhIUoyz2QBsp81ChcfLa5/vZNqwxkRlaGYSQzOTujDarnG4uJJHXltFQbkHTdPQNNiwN493N+zl5gunMOeEh/beRtcVe46W4rRbWt1uNhlRqjHpPTGB+WTrAf62fBMGTSM13oXRYCAc0ams9fL88i+wWkzMGzuwMy6jV2qo8/H6Y+/xxXtbqK/xAhAVG8W0iyZw+fcXY29l3JoQQpwppRqX9j5nX3RGJY/8fn+zr++9915++tOfsmjRItauXduugQnRk3y2/SBGTWuWvBwTH+2gzhdg3Z4jZ33+UDhCdb0PfzB8DlF2nQZ/kEdf/5yCcg+p8dFkJLpJT3CTmeSmIRDi/97bwMHC3j2ruqY1juk45YDLExpSgqEwb63bg0KRFBuF0dD4a9tkNJAc6yKiK95cu4tQJNIxgfdyoWCIv/7kZT5+aSV6RCcpK4G4lBgCvgAfvrCCZ+//O6GgzM8khBDdyWm3wIwaNYq1a9cyZsyYZuvvuecelFJ885vfbPfghOgJdF1RVlOP3doyeYEvJyFUisrahjM+d1VtA+9v3MfnOw/jDQSxmExMH57NkqnDSIt3n2vozSilyC2potzjxWYxMSwzCWsrc9acjS9y8iko95AS72pWKlrTNJJjo8gvq+GTbQcZlJ7QLp/XHWmaxuj+KazacZi4aEeL7cFwBIOmMTg9sdn6/YUVlFTVtnoMNHYjK6qs5WBhBcOzkjsk9t5s22e72blqD/FpcfjqfOTuzMPvbZyPx2wxsfatTUy/bAoTzxtzijMJIYToLKf9dHLDDTewcuVKbrvtthbbfvzjH6OU4sknn2zX4IToCQwGDafNQrmn9UkolWocYuewtZ7gtKXcU8/v/vUZh4oqcFjN2KxmAqEw72zYw5aDBfz46/PpnxLXDlfQ2L3rxY82s7+gHH8whNFoICXWxWUzRrJw/OBzHl+Rk1+GruuYjS0nHtQ0DbvNwvZDhef0GT3BwvGD2ZiTT3lNPQluZ9N9DUd0Sirr6J8ax6QhGc2O8QVChNu4dwBmk4FIRO+xrXNdbeMHW4lEIlSX1lBeUAkKjObGex3wBan3NPDP377GhIWjZZyREEJ0E6fdheyWW27hpZdeanP7vffeS25ubrsEdTJPPPEE/fv3x2azMXHiRD7//PM2912xYsWXfe2bL/v27evwOEXfMmtUfwLBMBFdb7HN6w9is5iZODijlSPb9urK7RwqqiA9wU1iTBQuu5X4aAeZiTEUV9bxwocbm2YoPxd5ZTX84d+fsf1QEQ6rmYxENwnRDkpr6vjrext4f+O5/3vRVWPFtbZogN4H+vGO7p/KDedNwmQ0kl9WQ1FlLQXlHoora8lOjuUHl89q0eqVHBuF3WKmIRBs9ZwN/saJL5NiojrjEnqdmrJadF1RUViF0WjE6rBiMpswmU1YHVaMRgOHtx9h/+bDXR2qEKKHU0rrkKUv6lETWf773//mRz/6EU888QQzZ87k6aefZvHixezZs+ekRQRycnKIjv6qmkxiYmKb+wpxNhaMH8Sa3bnkl3lIcDuwW80oBZ4GP3UNAeaNHciQjNP/uauqbWDDvnyinbZmXa6gscUn3u1gf2E5B4sqGXyO3a7eXrebkuo6MhNjmuahsZhNpMZFU1Zdz+urdzF79IBzKtc7MC0eTYNIRMdobPnepCEQYtrw7LM+f09yweShDM9O4vOduRwuqcRqMjFuUBrTh2e3OtdLZmIMI7KT2ZhTgMNqaTZXkK7rVNU1MG14NukJ7dulsK+IT4ulvsqLHtGx2FopsKABmsYX721m6CQplCCEEN3BGQ3i72p//vOf+c53vsMtt9zC8OHDeeSRR8jMzDxl17WkpCRSUlKaFmMbXTGEOFuJ7ih+/PX5jOqfQp0vSEG5h8IKDyhYMmUY371o2hl1PymtqcMXCOJs7YEKcFjN+INhSqvrzinuWq+fjTmNiVJrk2jGRTuoqmtgy4GCc/qcacOySYp1UVxV92VrTCOlFBUeLw6LmfltzH3SG2UlxXLdwgn8/Lrzufea+SyaOLTNiSo1TeNbCyeSFu8iv7yGqroGvP4gVXUN5Jd7SE9wc+2CCZ18Bb3H5AvGEQ63XgBBD0cwGA04Y5wUHSrr5MiEEEK0pce0wASDQTZv3sx9993XbP3pVEAbP348fr+fESNG8N///d/Mnz+/zX0DgQCBQKDp69ra2nMLXPQZmYkx/OrGC9hfUE5+eQ0mo5ER2cln1bXHajY1lcq1mFom3BFdYdC0cx5kX+8PEAxHcNpbH59zrPWnzhdodfsxSilKq+up9wWIibKT4HY22x7ttHHnpTN47PXVFJR5sJiNGDQNfzCEw2blmwvGMapfyjldS2+WnRzLz649j3c27GX9nqP4AiGsZhNLpgzn4mkjSIuX+UrO1pi5I0jOjCc/p4iQKYTpy39T4VCYSDhCTJIbs8WEw9V6gimEEKerI7p8SReybq6iooJIJEJycvMqO8nJyZSUlLR6TGpqKs888wwTJ04kEAjw0ksvsXDhQlasWMGcOXNaPeahhx7iwQcfbPf4Rd+gaVq7zPOSnRxLRmIMuSWVOKwtuwZV1TUQH+1gRPa5VZ1yOWxYzSb8wTAOa8vWnnCkcUxPjLPteTBy8st4bfUudh8tIRSOYDWbGD8onStnjyYrKbZpv9H9U/n1TRfy+c7DbD5QQCgSYUhGEvPGDOjQeXFKq+uoqmvAabOSmejusQOx0xPcfO+iaVy3YDz1viAuh7XNFjpx+kxmE1//yeU89V9/IxKMEPQ3jjUyWUwkpMcRmxpLZWEV4xaM7uJIhRBCHHPGCcyLL77INddcg9XavD98MBjkX//6FzfccEO7BdeaEx8+lFJtPpAMHTqUoUOHNn09ffp08vPzefjhh9tMYO6//36WLl3a9HVtbS2ZmZntELkQp89oMHDp9BE8/tZayqrriXc7MBoM6Lqiut5HKKyzePKw03qAVUqxv6Cc4qo6LGYjI7NTcDsb3ya77FamDc/i/Y37iHHaMBia9yqt8HhJiHYyflB6q+fefaSEP/1nJVV1DcS67ETZLfiDIVbuOEROQTn3XTOffsdVSkuJc3H13LFcPXfsOdyd03O0tJpXV21n+6EiAqEIZqOBQekJXDF7NGMHpHX453eUKLuVqHMYjyRamnHpZNa+uZGDW3NxRjuw2C3Yo6yEgxHK8ysYOLYfE8+XMspCiHMjE1m2nzNOYG6++WYuvPBCkpKavzGtq6vj5ptv7rAEJiEhAaPR2KK1paysrEWrzMlMmzaNl19+uc3tVqu1RXImRFeYNao/Df4Qr6zaTlFFbdN8Mi67lavnjOHSGSNPeY7DxZU8/8EXHCiqJBAKowGxLjvnTxjKlXNGYzYauWT6CHbkFpNf7iE2yo7DZiEUiVBV24DZZOTrc8e2mijpuuKljzdTU+8jKymm6UWC1WzCZbeRX17DKyu3c+81bXfZ7Ch5ZdX87l+fUlxVS2yUnSiHlVAows7cYnJLqvjhFbPPuCqc6L0cLju3//kmXvj5vzi4LZe6yjrqKuuw2CyMnD6Um379DRyutlshhRBCdK4zTmDaavEoKCjA7e64KjgWi4WJEyfy0Ucf8bWvfa1p/UcffcRll1122ufZunUrqampHRGiEO1K0zQumDyUaSOy2ZiTR3WdD5fDysTBGSSexriaokoPD7+6guLKOhLcDpJinOhKUV3n49VV2wmEwty4aBJp8W7u/8YC/vnZVrYfLqa0ug6TwUC/5DgunzmKmSP7tXr+nIIyjpRUNZvP5BiDQSM2ys6O3GKKq2pJjevcMRqvrtpBcVVt88pqJiMOm5nCilr+/skWxgxIbXNuFdH3JGbE81/P3s6BLbkc3Z0PQL9RmQyeMKDHdjsUQoje6rQTmPHjxzfNo7Jw4UJMpq8OjUQi5ObmcuGFF3ZIkMcsXbqU66+/nkmTJjF9+nSeeeYZ8vLymibXvP/++yksLOTFF18E4JFHHqFfv36MHDmSYDDIyy+/zLJly1i2bFmHxilEe3I7bZw3YcgZH/fBxhyKKps/xBs1jQS3k+p6Hx9v2c/5EweTFu8mIzGGH399PkWVHso9XuwWMwNS41uUcD5eVZ2PQDiCzdL6rxG71Uy9x0tVbUOnJjDlNfVsO1RITJS9RWU1TdNIdDspKK9hz5FSxg7suV3JRPszGAwMnTRQyiULIUQ3d9oJzOWXXw7Atm3buOCCC4iK+uoNsMVioV+/flx55ZXtHuDxrrnmGiorK/nVr35FcXExo0aN4r333iM7u3H+iOLiYvLy8pr2DwaD3HPPPRQWFmK32xk5ciTvvvsuS5Ys6dA4hehqoXCEdXuO4rRZWi2PHOO0kV/uYfP+AtKmf9VymhbvJi3+9FpSnTYzJqOBUFjHYm7ZkhEMRzAbjZ0+0Ly63kcwFCHO1frnWi0mwhGd6npfp8YlhBCij1P/n737jo+juho+/rsz27XSqleruPeGC9jGmG6bGiAkBEwgCYSEEEgIEHiSJyFPQkgvvEAIhITQUugQqgMYbGNj3HuRLVu9d22fue8fawsLSbYkr7SSdb/57IdoZ3fmrLzanTP33nNE5BbtfQ5DPU5gfvzjHwNQUFDAF7/4RRyO2JSUvPnmm7n55pu73PbEE090+Pmuu+7irrvuGoCoFGVw8QdDBELhLhMLiIxECKDN33V3956YmJdBZlI8VQ0tZH2mjK+UkrpmL5PzM8jPSOpmD/3D7bRh0XUCYQNbF2WmQ2EDTRO4naqCl6IoijJw1CL+6Ol1I8vrrrsOh8NBMBiktLSU4uLiDjdFUWLPabfhdtrxB8JdbjfMSHnk5ARXn49ht1q4/PSpaJpGZX0LocPNAIOhMOW1zbidNi4/feqArx/ISk5gQl46Dc1eZBef7LXNbaQnuplSoNbCKYqiKMpQ1OtF/Pv27eOrX/1qp+aRRxb3G0bXHY0VRRk4Fl3jrOmjefb9TYTCBtbPNMOsa/KS6HYyZ3zeCR3nzOmjMaXkhZVbqW5sxTQluqaRk5bI1WfN4JQYVPoSQnDF6VPYX15LWW0zqR4XDpuVYNigrrkNTWhcsXBat2t3FEVRFKVfyMO3aO9zGOr1N/j111+PxWLhP//5D1lZWao6i6IMUufPHs/GfaXsKqkm3mknzmkjbJg0tviwWHS+uGgGSe4TKw0rhOCcmWOZP7mAbQcqaPUHSYxzMHVkVqekaSBNys/ku5efwdPvbqS4uoFguA2LppGR5ObyhdM4a7papH20UDBE6d4KjJBBen4qCcnxsQ5JAWrL6ljz2ga2fbiTUDDMqGn5zLtkNmNmjIx1aIqiKDHV6wRm8+bNbNiwgQkTJvRHPIoSU0emHJ0MibknzsFdV53NCx9u5aOdB2lo8aFrkWaOF582ifndlEfuC6fNytwJJzaaE23TR2czuSCTPSXV1Ld4iXPYmFyQib2LdTHDlZSSFf/6iPeeXUl1SS3SlMQluJizdCYXf/N84pOOX65b6R971u/nL3c/TW1pPVa7BU3XOLijhDWvrefSby3h/OvOPCk+pxRlOJEIJNH9u432/oaKXn+TT5o0idra2v6IRVFiQkoJwY+R/ncgvBuEBWmdi3Ccj7D2vnzxYJLkdnLDBady5aLp1DS2YrPqjEhN7LIy2cnIomtMLsiMdRiD1qsPv8VrjyxH0wSetAR0XaO10cvyJ1dQuqecWx78mmrgGANtTW387Yf/oL6igewxGWhaZLmqlJKGqiZefvBNcsdnM2ne+BhHqiiKEhu9XsT/y1/+krvuuosVK1ZQV1dHc3Nzh5uiDCVSSqT378iWn0PwI5BBMFvB/xqy+YfIwOpYhxgVnjgHY3JSyUtPGjbJy3AS8AU4sPUQ+7ccxNfD8tAVB6pY/uQHOOPsZOSn4XDZsdqtJGV4SM9LY/e6fax5dX0/R650ZcPyrVQX15KRn9aevEBkZDg5M5FAW4DVL38SwwgVRekT2U+3YajXIzDnnnsuAOecc06H+9Ui/qFLyjCgIUTP81lptkJoOxAALQssY4fmdIbQevC9CMIB+lFVqWQqmOXI1ofAMgGhp8QuxpNURX0zmwrL8AZCpCbEMXvcCNxOe6zDGlLCoTDv/P0DPnjuIxqqmkBKPKkJnH75XJZ+7Rxsx+jBs2H5VtqafOSM7TxCZXNY0a0WVr+yjnOuWdifL0HpQvHuMqRponezjswZ72TPJ4UDHJWiKMrg0esE5v333++POJQBJqUJwZWHp03tBzSkbQ7CsRRh7X59k5QG0vcS+F8FowYwIyf/lglI5+UIy0jQUnuVDMWS9C+PjLronympKwRomWCUQPBDcF4WmwBPQqGwwdPvbuS9zfto9QXRhEBKSZrHzbJzT2Hh1FGxDnFIME2Tp3/6PCufX4vVYSUxLQEBtDS08vKDb1G+v4obf7kMSzdrfppqmgHZ7YUHR5yd+orG9otTysA57u9bSjWSqihDkapCFjW9TmAWLVrUH3EoA0hKE9n2KPj+AxiguUGGwP8mMrgG3Lci7Kd3/VzvP8H3DGADPRukBmYp+N8B/ztIPQcso8F5AdjPG/yJTHgPiG56oYjI1U8ZPjhkl8iFDZPmNj8WXSPeZR8UJ6L/XLGZ19buxO20kZvmQQhB2DCpaWzlz6+vxe20M3NMTqzDHPR2rytkzWvrSUiNx50Y135/ijMZX6ufDcu3MnfpDmadN73L58d5Iu/77hKUoD9Iem5qVN4zNaV1rH55Hevf2ULAG2DE2CzmXzqHU86d1u0ow3A2alo+mq4TCoaxfqbct5QSb4uPuRfMjFF0iqIosdens8uVK1eybNky5s+fT1lZGQBPPfUUq1atimpwSj8JrgH/65HExZIHWjLoqaAXgPQiWx9GmvWdniaNavC/DDhBzwAsYJaAWUnkEkAYZCuEC5EtDyDb/tZlI8HBxQqYx9gugaHXsT0UNnj9413c9dh/uO3hl7nlwZf4xT/fY1NhWUzjqmtu491N+4izW0lyO9tPji26RmZyPF5/kNfW7BwC75vYW//2ZoK+YIfk5Qin24FpmHz8xsZunz/9rMk43A5aG9s6bQuHDIK+IPMunn3CcR7YeojffPUhXnnwTWpL6/C1+Nj64U4evespnv7p8xhhNe34s2acPYWcMZlUHazu8PuRpqSmtI44TxwLLjs1hhEqiqLEVq8TmBdeeIHFixfjdDrZuHEjgUAAgJaWFn7+859HPUAl+qT/nciIi+bpuOHItCmzDgJdJKPBdWC2RBIeANkMZjWgg+YEYQPZFpmOpbkj08zC2/v99ZwQ2zyQPujqhFkGAR1hmzrgYZ2IUNjgwVdW89e31lFa24jVqqNpgk/2lPCb51bw7sZ9MYttW1ElzW1+Et2OTtuEECS6newtq6GmqfNJtdJRXXk9Fpu12+02h5Xa0rputxdMzuW0i2bRXNdKfWUjRthASklrYxsVB6rImziCBZfNPaEYQ8EQf//xv6gpqSN7dCZpI1JIykgke3Qm8UluVr74MatfXndCxzgZOeMc3PDLZeSMzaLyYDVl+yupKKqmrLACu9PO1f9zueoFoyhDkuin2/DT6wTmZz/7GY888giPPfYYVuunX57z589n48bur/Ypg4OUEsKFILrp79A+baq4iye3AgKOTAsza0EaII68DzQioxkGCA9IP9L/QZRfQXQJx7mgpYBRCjL86QYZAKMMLGPBNrSudK7cXsTqHUUkxzvJSk4g3mnHE+dgRJoHwzR5+t2N1MYoQQgEwyBEh8pKR7PoGoZp4g+Gu9yufCohJR4j1P3vKRQIkZCS0O12IQRX/8/lXHjjOdgcVioP1lC2r5KAL8gp503jWw98FU9q98/viW0rd1NWWElabiqa3vHf/MgUtg+fX6NG3LqQNyGHe56+let+chWzz5/OtDMmcdmtF/I/z97G/EvnxDo8RVGUmOr1Gpg9e/ZwxhlndLo/ISGBxsbGaMSk9CMhBFJYQXqP87gupk1pSYA8nLToIP2fJjMAGETeUnpkNEfYIovgBzFhyYf425GtD0QSlvYVdhawTEIk3IkQQ6sy1orNhUgJrs9UoBJCkOZxU1rbxNpdh7jotEkDHltGshuLJvAHwzhsnT9+2vxB3A47KQndrEtS2p1y7jTWvLYBf5sfR1zHEa2gPwTA3KXHXidhtVm54rsXc951Z1K4sYhwyCB7TCY5YzKjsvalbG85pmFic3Q9UuROjKPqYA0tDa0kJMef8PFONnGeOBZdOY9FV86LdSiKokSDWsQfNb1OYLKysigsLKSgoKDD/atWrWLUKFU9aEiwLQDfcyDNzyQgRJISLGCd1sXzTo2MVpg1oGcCemTqlSCyL2lE1sYcHsVBhrsf6RlEhG02JD4YmTZnHAJ0sE4G25yuE7lBzDQlpbVNxHVzwnikclFlQ8tAhtVuSkEWuelJFFXWMyI1ocNJcjBs4PUHWTJnAnHHKP+rRExdOJFpZ0xk07vbiE92E5/sRiBoaWyjqaaZyfPHc8p5XfwddyEhOZ5Tzu3ZY3tDt1pAym4LBUjTRGii20ppiqIoitKVXk8hu+mmm7jtttv4+OOPEUJQXl7OM888wx133MHNN9/cHzEqUSYc54GWGhlx6DBtygdGBVgngu2Uzs/TEhGuqyM/hEsOV++SYAYiiY8Wdzix4fD6ERD20/r51USH0BIQzgsQ7m8i3F9H2BcMueQFIgNfdquFkHGswgTgiNEJo0XX+NqSuaTEuyiubqS+xUurL0B1QyuV9S1MzMvgknmTYxLbUGOxWrjhF8s486oFSAkV+6soK6zECBks+NxcbvrNl3G4Yjt6OG7WKGwOG75Wf5fbWxraGDtrFK545wBHpiiKEgOqkWXU9Pos5q677qKpqYmzzjoLv9/PGWecgd1u54477uCWW27pjxiVKBOWAoi/4zPTpoisZbFOR8Tf2f3Ju+MChHAhfS9CuOjwVLIgiJRIFTOskU72Zg1YJ0VGe5QBI4Rg/uQCXli5FdPs3CvC6w9is+hMH50dowhhUn4GP7j6HN5ct5tP9pYQDBkkxTs5c/oYlsweT0Jc5wX+Stdc8U6uu/eLXPj18yjaegiAvIkjyMhPi3FkEaNnFDDh1DFsfn8HWq7WnlCZpqS+vB6Hy85ZX1SfEYqiKErvCNnH1ZNer5edO3dimiaTJk3C7R78U4X6orm5GY/HQ1NTEwkJJ7agdbCRZisEV0O4OJKIWKeCdSZCHD+vlTIMxkFkuCxSWjl8ILLwHUDYwToF4b4VoWf074tQOimva+L/nlpOdWMrGUlubFYLUkra/EHqm33MnZDL97949qBohOcLhPAHQ7iddqyqH8hJqbGmice+/zR7P9lPOBRGaAJpSuKT47niOxey6AvzYx2ioigngcF8vnYktmUvP4ktLrprPINtXp7+3JcH5evuT32eR+JyuZg9+8R7BCixIzQ3OBb37bnCApYxCMsYpP0MCO+C8N7IRss4sEwcFE0Th6PsFA/fveIMHvnPGkpqGpEyUn3OYbOyYEoBN1142qBIXgCcditOe/elgJWhLzHNw3f/fBM7PtrDjo/2EGgLkFGQzuzF00nPTY11eIqiKAMm8n0c/X0OR71OYNra2vjFL37Bu+++S3V1NabZca79gQMHohacMjQIISLTxawDX9VK6dr43HR+deNFbN5fTmlNIxZdY3JBJiMzk1ViqQw4i9XC9EWTmb5IrW9SFEVRTlyvE5gbbriBDz74gGuvvZasrCx1MqQog5TVojNnfC5zxufGOhRFURRFUVQZ5ajpdQLz5ptv8vrrr7NggVp4qSiKoiiKoihK1wzDYNWqVUybNo2kpKSo7bfXZZSTkpJITk6OWgCKoiiKoiiKctKTon9ug5iu6yxevDjqze57ncD89Kc/5Uc/+hFe77E7uSuKoiiKoiiKMrxNnTo16mvkez2F7Le//S379+8nIyODgoICrNaOFYQ2btwYteAURVEURVEU5WQgDt+ivc/B7r777uOOO+7gpz/9KbNmzSIuLq7D9r6Uf+51AvO5z32u1wdRFGX4CYbCFFc3YkpJTqqHOEc3zVEVRVEURTlpLVmyBIBLLrmkQ/EvKSVCCAzD6PU+e53A/PjHP+71QRRFGT7Chsmb63bxzoa91DS2IgFPnIMzp4/msgVTVd+XYaqt2cumd7dRWVSN1W5l4mljGXvKKFXJUlGU4WOYViF7//33o77PPjey3LBhA7t27UIIwaRJk5g5c2Y041IUZQiSUvL35et58+NdWCwaHrcDIQTN3gDPfbiVkupGvnvFGdisff7oUYagze9v59mfv0hdWX3k+9uUvPmXd5k0fxzX//QqEpLj2x/bXN/Chne2Ur6/Et2iM2HuGCYvGI/VphJfRVFOAkMg4Yi2RYsWRX2fvT6LqK6u5qqrrmLFihUkJiYipaSpqYmzzjqLf/7zn6SlpUU9SEVRhoa9pTW8u3EvbpcdT5yj/f40jwVfMMS6PSWs3V3MGVNHxTBKZSAVbS/mbz/8B23NXtLz07BYdaSU+Fr9bHp3G1LCrQ/dgBCCze9v5+mfPU99eQPycHvp/z79IaOm5fP1Xy0jNSclxq9GURRF6YuVK1fy5z//mQMHDvDcc8+Rk5PDU089xciRIzn99NN7vb9eVyH79re/TXNzMzt27KC+vp6Ghga2b99Oc3Mzt956a68DUBTl5LF21yF8gRAJLnunbc7DV9BXbotuJRJlcFvxr9U017WQWZCOxaoDIITAFe8kOSuJXWv2sm/jAQ7tKuVv//tPGqubyByZzohx2YwYl01yZiL7Nuzn0bueJhQMxfjVKIqiKL31wgsvsHjxYpxOJxs3biQQCADQ0tLCz3/+8z7ts9cJzFtvvcWf/vQnJk6c2H7fpEmTeOihh3jzzTf7FISiKCeHmsY2dF3rdl2D3Wahsr5lgKNSYiUcCrP1g53EeeK6fE843Q6C/iC71u5j1Ysf01zbTGZBOrpFb3+M3WkjLTeVoq2H2LF6z0CGryiKokTBz372Mx555BEee+yxDtWL58+f3+fqxb1OYEzT7FQ6GcBqtWKaZp+CUBTl5JAQ58Awu5/gGwoZJLmdAxiREkvhkIERNtEtXX/VCCFACELBEJvf344z3tllomN32giHwuz5ZH9/h6woitJ/ZD/dBrk9e/ZwxhlndLo/ISGhzw0ue53AnH322dx2222Ul5e331dWVsZ3v/tdzjnnnD4FoSjHIsPFSN/LSO8/kYEVSFM1UR2s5k7IxarreP3BTttCYQPDNFkwZWQMIlM+S0rZvs6kv9idNjIK0mhr7vpvNhyKlM7MyE8nHDLQ9GN/JYVD4ajH2J9CwRCb3tvGP+5/iSfv/RfLn/yAhqrGWIelKIoyoLKysigsLOx0/6pVqxg1qm9rYnu9iP/BBx/k0ksvpaCggNzcXIQQFBcXM3XqVJ5++uk+BaEoXZHSj2x9FAIrQHppb9ekZ0HcTQj7qbEMT+nClIIs5owfwUc7DhIfMvDEORACWnwBGlv8TMhNY8HkgliHOWyZpsmGd7aw+uV1HNpRisVuYcbZUzjjitPIHZ8T9eMJIVh4+akUbT2Et8WHK/7T0TcpJTWltaTmJHPKuVPZ+N8tbPlgJ0npnk77McIGQgiyR2dGPcb+UlfRwKN3PcX+TUUYYQMOjyy98Zf/ctXdl3HqBafEOEJFUQbcMC2jfNNNN3Hbbbfx17/+FSEE5eXlrFmzhjvuuIMf/ehHfdpnrxOY3NxcNm7cyPLly9m9ezdSSiZNmsS5557bpwAUpTuy9VHwvw5aImh5kRMAGQKjEtn6W9DuRVgnxThK5WgWXeOWS08nMc7Jqh0HKattQgJxDhsLphTwlcVzcDs7L/BXToyvLVLR6+D2EqSUjJySx8xzpuA8arqeaZr88xcvs+KfqzEMA1e8k4A/yH+f/JBP3tzMV+/7EtPOiP7f07xLZrPnk/18/PoGmmqbiUtwYYQN2pq8JKTEc80PriAuwcXpl53KjtV7aKlvJT7Z3f58KSXVJbUkZycx6/xpUY+vPxhhg7/c/TR7PikkPTcVuzPSxNU0TGpK63jq/54jJSuJMTPVaKSiKCe/u+66q71isd/v54wzzsBut3PHHXdwyy239GmfQvb3HIIhrrm5GY/HQ1NTEwkJCbEOZ9iQ4WJk43dBWCIJTIeNEoxDYD8bLeH7MYlPOb6aplb2ltYipaQgI4kRaYmxDumkVLS9mMfveYby/VXIw+sQNV0joyCdG+6/hlHT8gH45K1NPHrX08R5XMQnxbU/X0pJZVE1SZmJ/Pj5O3AnxnV5nBMRCoZY8+p6Vr74MVUHa9AtGtPPnMyiL8xn5JS89jj+9etXeP/ZlYRCkQTLDJv4Wv0kpMbz1Z99ielnTo56bP1h+6pd/PHmv5CYnoDjMxX5pJSUFVay8PJT+ep9V8coQkU5+Qzm87UjsS3799PYXK6o7jvo9fL0F5YNytf9WV6vl507d2KaJpMmTcLtdh//Sd3oUze5d999l9///vftjSwnTJjAd77zHTUKo0RPaCPItsjIy2cJAVoChDYgzVaE1vc/AKX/pHncpHnUv01/aqpt5tE7n6LyYDWZ+WlYbJGP9HAoTGVRNY/e+RTff+rbJKV7WPnix5iG0SF5gcg0r/S8VCoPVrPxv1s54/Pzoh6n1WbljM/PY+EVpxH0B9EtOpbPNDMVQvDFOy9l7MyRrHppHQd3lGBx6yy4bC4LrziNvAnRn+LWX/auP0A4FO6UvEDkdcYluNi2chdG2OhQcU1RFOVk9NWvfpU//vGPxMfHM3v27Pb729ra+Pa3v81f//rXXu+z14v4H3zwQZYsWUJ8fDy33XYbt956KwkJCVxwwQU8+OCDvQ5AUbokA4BonzfemRWkcfhxijI8rXtzE5UHq8kamd6evABYrBayRqZTVVzDujc2YhgGxbtKcSV0feVPt+ggobywsl/jFUJgd9o7JS9Hb5913nRue/hGfrfiJ/xq+Y+45gdXDKnkBQ6v2TnGdk0XmKapKncqynAzTKuQ/f3vf8fn83W63+fz8eSTT/Zpn70egbn//vv5/e9/32HO2q233sqCBQu47777+jyXTRm+pJRgHACzCTQP6KNAP7xYV4ZAdC7bjWwFLQ20+IEN9ugQZBBC2w7HkgyWSQihrqYqA2fH6t3outblVXxN17BYdLat2sX5152JbtEJBbqv4iUBvZvEIha66yXUU0F/kC0f7KRwYxGGYTBibBannDeNhOT+/8zIGZuF0AThkNHevPNobU0+Jp42Fquti882RVFOXsNsEX9zc3N7xcuWlhYcDkf7NsMweOONN0hPT+/Tvnv9bdXc3MySJUs63X/++efz/e+r9QhK78jgFqT3WQjvARkEYQPLeHB9PlJtzKgEfUTHkRgZABlAOM5DCNvAxywlBN5Hev8BRjkQjsStj4S46xE2VV1oOJNSsru5nNU1uyluq8Op25idMop5qeNwWx3H30EvhILhY5Ye1nSNcCCMEIIZZ03hvWdXkpTh6ZQc+L0BLFadCXPHRDW+WKkoquKx7z/NoR2lmIYJSIQQvP7Yf7nu3i8w5fSJx93HiZh5zhTSclOpLq4ha2QGQvv0993S0IamCxZecVq/xqAoihJriYmJCCEQQjBu3LhO24UQ/OQnP+nTvnudwFxyySW89NJL3HnnnR3uf+WVV7j44ov7FIQyPMngFmTLz8FsBC0VtBSQfghthpaD4LgU/K9EFuxrCUSmjbVGEhjbKeC4KDaBB95Ftj4IhEFPA2yAH8J7kS2/hIQfIKxDo1qSEl1SSp4rXstrZRvwhYPYNAuGNNlYf4B3KrbwnQkXkuNKjtrxCqbksXP1HqSUnZISKSVBf5CRUyPryBZecRrr395M5cEa0nNT2kdtAr4gNaV1TDx1LJPmdf6COVFSSnavK2TNq59wYOshLDYL0xZNYsGlc8nIT4v68fzeAI/e+RQHtxeTnp+GzR4Z5TDCBtXFtTz+g39w519v7teSzE63ky/f+wUev/sZygorcMQ50C0a3lY/FovOWVedzpwlM/rt+IqiKN358MMP+fWvf82GDRuoqKjgpZde4nOf+1y3j1+xYgVnnXVWp/t37drFhAkTjnms999/HyklZ599Ni+88ALJyZ9+/9lsNvLz88nOzu7T6+h1AjNx4kTuu+8+VqxYwbx5kcWea9euZfXq1Xzve9/jgQceaH/srbfe2qeglKFHSgmhrcjAh5FRCS0BYZ8HtnkI0Xkhq5QS6X0qkrzo+Z+OsAg3iDgwiiG0CeLvhcB/IPhJJHHR0hGO88BxYUwW70sZQHr/SSR5OXpevhP0PDAOIb3/goSpJzwFRhl61tbu4+WSdTh0G6mulPb3QNg0KGqt4eG97/CTaVdi0aIz1fC0C0/hw39/RF15AynZSR3ec/UVjcR5XJx64SwACibnct3/XcWz971A5cFqpASkxGKzMGHuWG74xbKoLyiXUvL6o//l9UeX4/cGcMbZMQ3JoR2lrH5pHV+7/xomnRbdpGnLih0U7yojIz8Nq/3TKVq6RSdzZDpl+ypY/conXHl7/15wm3TaOO74682senkdG5dvIRQIM37uGOZfMoeZ50xF03q9BFVRFOWEtbW1MX36dL7yla9wxRVX9Ph5e/bs6VDlLC3t+BegFi1aBEBRURF5eXlRPS/qdQLz+OOPk5SUxM6dO9m5c2f7/YmJiTz++OPtPwshVAIzTEgZRrY9Cv63IkmGsIEMRZIZ6zRI+D5C+8xV5/C+yE1L67xQX4jIiEx4L0LoiPg7kebhkRctAdHVmpij4zFbwGwAzd35uCcqtBWMCtC7mLMpRGQUKbQLjFKw5Eb32MqgJqXkv5XbCEuTRFvHSl8WTSfdkcCB1iq2N5UwI6kgKsfMHZ/D52+/mH//+hXKCivbG0X6Wn04XA4uu/VCCiZ/+j485ZypjJlRwIblW6k4UIXFqjN+7hgmzx/f7cL6E7Fj9W7+8+d3sNgsjBib1X6/NCUVRdU88b//5MfPf484T/RKN+/5pBDTMDokL0cIIXC47Gx+b1u/JzAAWaMyuPL2iwfkWIqiDH5CRm7R3mdvLF26lKVLl/b6OOnp6SQmJvb6eRAZrSkpKeH0008H4KGHHuKxxx5j0qRJPPTQQyQlJfV6n73+xioqKur1QZSTnP8N8P0nMs1L//QkBRmA0CZk658QCT/o+BzZFFnzonWzJkA4wKyLPA4Oj7Yce8RFGhVI7wsQXBWZiiasSOtshPNyhHVs58dLCeGdkYX4GKAXgG12lyNG7cwW2te8dBm3HWQzyJZjxqqcfIpaq9nRVIpNsyCRiM/UoXLoNsKyhf0tVVFLYAAWfWE+maMyWPXiWnZ9vA8kzDxnKqdfNpcJczu/7xNS4jnrqgVRO/6xrHp5HUF/kLQRKR3uF5ogIz+VyoM1rH9nK4uujF7p5nAw3GHNyWdpukY4aETteIqiKINBc3Nzh5/tdjt2e/QaR8+cORO/38+kSZP44Q9/2OW0su7ceeed/PKXvwRg27Zt3H777Xzve9/jvffe4/bbb+dvf/tbr+MZPCVnlCFJyhDS/wYIPVJB7GjCHhmRCG5Ahg8iLAVHbYuPVBeTARBdlHY9MpIjelYxSBplyKZ7P10vI+KBYGS9SmgrJPwPwvppEzxp1iNb/gChLUeVYtZAz4X42xDWbjqSa8mH4/ZHkqxOgfgAe+RxyrBQ5q3nX4c+YlP9Qcq8dQgE9cFWMh2JnUZi+qtczPjZoxk/ezRH+hIPlumLhRuL2keFPku36EjTpHh3aVSPOWJcNlJGut53VeDA1+Zn2hBpiDmYtDW1sf7tLWz9cCcBX5C8iTmceuEs8ieOiHVoijKEiMO3aO8TcnM7zvr48Y9/zL333nvCe8/KyuLRRx9l1qxZBAIBnnrqKc455xxWrFjBGWec0aN9FBUVMWlS5LzqhRde4OKLL+bnP/85Gzdu5IILLuhTXL1OYKSUPP/887z//vtUV1d3qmP/4osv9ikQZYgyKiKVwoSn6+0iHsz6SJWxoxMYyziwjILQbhB5n6kyJsGsBeuEyON6QHqfjSQvel4kmQLABSIBjBJk21/A81uE0CJT3lp+DcENoKWDlhE5vgxG1rC0/AI89yP0LnpPWKdEjhEuiiQ7HeI2I6/VfgZC778FwsrgUeFr4Fc7X6HMW4/H6iLB6qI55KMtHKCorZo8mUqKPZKE+40gFqEzJr7/3huDJXE5QtM1pHnspE3Xo7vuZs6SGbz11/eoLqklIz+tw++kqbYZm8PGgkvnRPWYJ7uywgoe+d7fKdtbgdAEukVnx+rdfPDcGi69eQnnfXnRoHvvKcpwU1JS0mGNSrRGX8aPH8/48ePbf543bx4lJSX85je/6XECY7PZ8Hq9APz3v//ly1/+MgDJycmdRo56qterCG+77TauvfZaioqKcLvdeDyeDrf+9vDDDzNy5EgcDgezZs1i5cqVx3z8Bx98wKxZs3A4HIwaNYpHHnmk32McXo6cnBzry0vw2SvPQmgI17JIHxejODJyIc3If43iyPoV1zUIcfy3qDSqIbgOtMSjkpcjB9Ii62zC+yPTxSBSHCC0LdJrRos7qoCALZKUGJVI/3+7fiXCgoj7CmjuSMJktkYSH7PpcAKViXB96bgxKyeH10o3UOqtJ8eVgscWR7ojAV1o6EJgmpJyXwOGNAmbBtX+JkbHZzDZM3yuWE85fQLeVn/7yNDRQoEQmq4xZubIqB4zKSORa354Bc54J2WFldSVN9BQ1UhZYQVBX4ilXzubyQuOXTlH+VQoGOLxe56hdE85GQXpZI/OJCM/jZyxWWBKXnrgDXas3h3rMBVlaOjHRpYJCQkdbtGcPvZZp512Gvv27evx408//XRuv/12fvrTn7Ju3TouvPBCAPbu3cuIEX37Tuz1CMzTTz/Niy++2OchnxPxr3/9i+985zs8/PDDLFiwgD//+c8sXbqUnTt3kpeX1+nxRUVFXHDBBdx44408/fTTrF69mptvvpm0tLReVV5QjkHPioximJVAV1PBWkE4wdK5v4SwzYb4u5BtT4FxsEMfGBG3LLK9J8zaSOKjdVMRQ3NBuBqMGrACwU2HG2R2MbVFaJH7A6sg7roudydscyD+nki1sfDew+t07GBbiIj7EsIyumdxK0NaS8jHurpCEqxO9MOJdqI1jkxHkKpAExKJNxzgQGsVTt3GSHcGN49dHLUKZEPBwstP5ZM3N1FdXEtabira4bUp4WCYqkM15E/KZfqZ3UzXPAGzzptOak4yq15ax5YVOzDCBpPmj+f0y05l6sKJarSgF7at3E3xrjLS89I6NOUUQpCclURZYQUfPLem33vrKMpJ4SRpZLlp0yaysrKO/8DDHnzwQW6++Waef/55/vSnP5GTE5nh8uabb3bZW7Inep3AeDweRo0a1aeDnajf/e53fO1rX+OGG24A4A9/+ANvv/02f/rTn7j//vs7Pf6RRx4hLy+PP/zhD0CkBPT69ev5zW9+oxKYKBHCBs4lyNbHIgvctaPWrMhgJLmwLQC965N6YZsD1lMgvDsyiqElRhKY3nS0Fy7A8mkC9FkyBGjtCYtsX/PSHStI77EPaTsFrDMjoy6yBbTkrqecKSet5pCPgBnGrX+6FkoIQZYziQSbi4ZAK7WBFvJcqVyWN5fTUsZGvZHlYDdyaj7LfnQl//j5i5QXVrRPKROaIG/iCG745TLszv65Spg/KZf8Sblc84MruuyTo/TMwW3FGIaJzdF19cc4Txx7NxwgFAxhtR27QqQyfEgp20dZ+6PCodJ3ra2tFBYWtv9cVFTE5s2bSU5OJi8vj3vuuYeysjKefPJJIHKuXVBQwOTJkwkGgzz99NO88MILvPDCCz0+Zl5eHv/5z3863f/73/++z6+j1++qe++9l5/85Cf89a9/xensenFmfwgGg2zYsIG77767w/3nn38+H330UZfPWbNmDeeff36H+xYvXszjjz9OKBTCau38YRsIBAgEPj3B7evcvGHFcTGED0HgXQjXHa7EFQIkWKcg3N865smDEDpYT2BRrZ4fGeEJbY/0kPnsscy6SNnjw80lhZ4duWAhzciIy2fJtsj6m+MQQnRc16MMK3EWB1ahEzBDOPk0cRZC4LY4cGhWhBBcVbCAhenDd8rSqRecwujp+ax7czPFu0qx2CxMOm0cM8+ZgtM9MN8hKnnpOynlcScIx+QSsDIoGWGDj1/fyMoX11JeWInQBFMXTmTRlfOjPl10KOq/Jfw9t379+g4VxG6//XYArrvuOp544gkqKiooLi5u3x4MBrnjjjsoKyvD6XQyefJkXn/99V7NxDp6f13pahbV8fQ6gbnyyiv5xz/+QXp6OgUFBZ2SgI0bN/Y6iJ6ora3FMAwyMjI63J+RkUFlZWWXz6msrOzy8eFwmNra2i6Hv+6//35+8pOfRC/wYUAIK7hvBfvpyMAKMMpAeBD2BWBbgNCi1+OhS7IlMpUtsCJSVEC4IwmLSATZABgI5xUI7fAUN/vp4HsOzCrQMjsmPGYLoCEc5/ZvzCchQ5q0hvxYNJ04S//NvR0sEm0uTkkeyftVO0iwutA+c5JcH2wl2eZmZhRLJg9VqTkpXHDDObEOQ+mD/Mm5aLpGMBDC1kVvndYmLzPOnqJGXxQMw+DZn7/Ah8+vxTQlcQkujKDBqpfWsfm97Vz74y8wd+nMWIc57J155pldrks84oknnujw81133cVdd911QscsKCg45oUkw+h9afteJzDXX389GzZsYNmyZWRkZAz4la3PHu94UwO6enxX9x9xzz33tGejEBmB+WxpOqUzIXSwzYlMCRtA0qhGNv8sshZFxB/uL9ME4cZImWPLWITrC5FRoiOx6hkQ9xVk658PFwxIALTDyYsEx3lgO31AX8dQFjLDvFu5nfeqtlPjb0YgmJKYy/lZ05mSeHL/7VycM4sdTaWUeutItcfj1G2EpEF9oBWAz+XOGXbTxpSTy7QzJpIzNovi3WVkjUxHt0Sm90opaaxuxma3csYVp8U4SmUw2PDOVj58bi3upDjciZ9euExMT6C6uJZ//uIlxs0eRWJa/xd8GrROkjUwvbVp06YOP4dCITZt2sTvfvc77rvvvj7ts9cJzOuvv87bb7/d3k1zoKSmpqLreqfRlurq6k6jLEdkZmZ2+XiLxUJKSkqXz4l24x+lf8m2xyLrZ/QRh/uzGJEExmyLNJS0LUA4L+/0POFYDFo60v86hLYCBljHRu63n4cQas5uT4TMMA/vfYfVNXvQhYbb4sCQJmtq97K14RBfG3M2C9NP3sW9+e40bp94Ic8UraKwpZLaYAsWoZHu8HBxzizOzZwa6xAJh8LUVzaiaZFF15rW6+KTyjBmc9j46s+v5tE7n6RifxWaRUe3aAR9QZxuJxd943ymq746CrDqpY+R0uyQvEDkgnHaiBTKD1Sx4Z2tnHPNwhhFqMTK9OnTO903e/ZssrOz+fWvf83ll3c+TzueXp+l5ebmdqgzPVBsNhuzZs1i+fLlXHbZZe33L1++nEsvvbTL58ybN4/XXnutw33vvPMOs2fP7nL9izK0yHDx4V4uh5tLQqSMskiO3GfUQnAN0rwOoXV+zwrbTIRtJtJsAwwQ8WqufC+trN7NRzV7Sba5cR01bcxjdVHlb+KpopVMTczroqHjyWNsfBY/nvp59rdWURtowanbmJCQjV2P7WdMOBTm/X+uZuULa6ktrUdoguwxmZz1xQXMu2S2eq8rPZY/cQR3PXEL697cxJYVOwj6Q+RPzOHUi2Yxevqxp4Yow4OUkpI95d2ua9N0DaSksqh6gCMbZIbpCEx3xo0bxyeffNKn5/Y6gfntb3/LXXfdxSOPPEJBQUGfDtpXt99+O9deey2zZ89m3rx5PProoxQXF/ONb3wDoFPlhG984xs8+OCD3H777dx4442sWbOGxx9/nH/84x8DGrfST4yDkQX3WmrX27UEMGvAKAWt+1Kt/b5G5yS2omoHAjokL3D4ipsjgXJfA2tr97Eke0ZM4hsoQgjGxGf2a5PK3jDCBk/95DlWvbQOi1XHnRiHlJKibYc4tKOEmtJaLrl5iTrxVHrMk5rAedcu4rxrF8U6FGWQstosBNqOXeXTalezG4ajzxbEklJSUVHBvffey9ixY/u0z16/k5YtW4bX62X06NG4XK5OIxn19fV9CqQnvvjFL1JXV8f//d//UVFRwZQpU3jjjTfIz88H6FQ5YeTIkbzxxht897vf5aGHHiI7O5sHHnhAlVA+aehE6m+Yh///Z5lEerWqKTP9IWwalPsaOiUvR0R6o0iq/E0DG5jClhU7+OjV9XjS4olL+LQ/U5zHRWN1E+88sYIZZ00hf9LJvUZJUZSBIYRg1nnTeOuv7yHNRITW8eKI3xvAYrMw8bRxMYpQiaXExMQu16Tn5ubyz3/+s0/77HUCc6SnSqzcfPPN3HzzzV1u+2zlBIBFixb1W2U0JcasEyN9Y8xG0LtY02Q2gJYBltj0LRqsfOEgGxuKqPA1YNMsTE3MoyAurddX43WhYdUstIX9XW6XUiIl2DV1xW2grf3Peoyw0SF5OcKTlkDZvgrWvbVZJTCKokTNgstO5eM3NlJxsJr03JT2/i++Vj+1ZfVMnj+eSfOGeQIzTKeQvf/++x1+1jSNtLQ0xowZg8XSt3OEXj/ruuu67k6uKANNaMlI+zngex5MW6R8shAgJchGkGGE88JIs00FgM0NB/lr4ftU+hsBkEgcuo05yaP52pize1X+WAjBaaljea10A9LWuRqgzwhi1y1MS8qP5ktQeqDiQDUOV9fveyEEukWn+lDNAEelKMrJbMTYLG64/xqe/MlzVBfXRr6KpcRqtzLl9Al87f5r2qvYKcPLokXRn3rap7THMAxefvlldu3ahRCCSZMmcckll6Dr6o2pDCwR92WkbILAh5GGlUemlIk4cF7WoXzycLe/pYqH9rxNc8hHhiMRq6YjpaQ17OfD6p1IJLeOX9qrkZhzMqewpmYvZb560h0ebJoFKSVt4QD1wVbmpoxmQkJ2P74qpSsuj4vKg90vljUNkzhP59EZRVGUEzFp3nh+/Pz32PTudsr3V2KxWhg/dwzjZo9S54gwrEZgXn311R4/9pJLLun1/nudwBQWFnLBBRdQVlbG+PHjkVKyd+9ecnNzef311xk9enSvg1CUvhLCDu7vgWMJBD9Gmo0ILRXsC0AfrRYpH2V5xRYagq3kulLbfy9CCOKtTgSC9fUHONBaxeheLEQf4Urh1glLeazwXcq9DUgkUkocFhvz08Zx45hz0IRagzTQZp8/nX3r9xMOGVisHU8aAt4Amq4xbZEqfasoSvQ53U7mXzqwPeGUwedzn/tcjx4nhBiYRpa33noro0ePZu3atSQnJwNQV1fHsmXLuPXWW3n99dd7HYSinAghBFingHUKA5WuSBmE8D6QQdCzI80xB7GAEWJDQxFui7PLpC7OYqfB18q2xpJeJTAAkzwj+MWMq9nccJBSbz1WTWeyZwSj3APf6FaJOPXCU1j14scU7yolJTsZR1xkamBbk5eGqiamnD6BqQsnxDhKRVGU4UXIyC3a+xyMTNPs1/33OoH54IMPOiQvACkpKfziF79gwYIFUQ1OUQYbKSX430T6XgazItI4U3MhbaciXNch9PRYh9ilkDQwTBNLN00MhRAIBAEj1Kf923Urp6aO5dQTCVKJmoTkeL75++t58t5/c2DLIeorGgBwxDmYs2QG1/7oSqw21QtLURRF6T/vvfcet9xyC2vXru3UQ7KpqYn58+fzyCOPsHBh75ub9jqBsdvttLS0dLq/tbUVm00tllZObtL7b/A+FSkWoCUDFpAt4F+ODB8Ez08RWvLxdjPgXLqNVHs8Jd46Eqyd1z6EzcjwbYYzcYAjU/pLZkE6d/7tW+zbeICS3eVousboGQXkjs9WI2OKoihKv/vDH/7AjTfe2Cl5AfB4PNx000387ne/61MC0+vJ6RdddBFf//rX+fjjjw+XSZWsXbuWb3zjG31ahKMoQ4U0qsD/PAgb6NkgHCAsoCWBnhuZUuZ/M9ZhdkkTGmdlTsaQJj4j2GGblJJqfxOp9nhmp6iS0ycTIQTjZo3mnGsWctZVC8ibkKOSF0VRFGVAbNmyhSVLlnS7/fzzz2fDhg192nevE5gHHniA0aNHM2/ePBwOBw6HgwULFjBmzBj++Mc/9ikIRRkSgmvBbAGti54zwgLChfT/FynDAx9bD5ydMYU5KaOpC7RQ6WukJeSjMdhGqbcOl8XO9aPPxG1xxDpMRVEURTkpHVkDE+3bYFVVVdWp4f3RLBYLNTV9K+nf6ylkiYmJvPLKKxQWFrJr1y6klEyaNIkxY8b0KQBFGTLMyDoCuquqJRwgW0H6Iz1pBhm7buXb45fybuU23q/cQV2wBU1oLEyfyOLs6YxX5Y4VRVEUpf8MozLKADk5OWzbtq3bHGHr1q1kZWX1ad+9SmCam5txu91omsaYMWPaAzJNk+bm5i7nuCnKSUM7/P6WZtdJjAxEHiMG7yiGQ7dyYc4pLM6aTls4gFXTcfWieaWiKIqiKEpPXHDBBfzoRz9i6dKlOBwdz418Ph8//vGPueiii/q07x5PIXvppZeYPXs2fr+/0za/38+cOXN47bXX+hSEogwJtnmguT8diTmaDINsA/vZCNGn/rADyqLpeGwulbwcQ2OwjXcrt/Fi8ccsr9hKXaBz8RJFURRFUbr2wx/+kPr6esaNG8evfvUrXnnlFV599VV++ctfMn78eOrr6/nBD37Qp333+EzrT3/6E3fddRcuV+cKRi6Xi+9///s8+OCDXHyx6nyunJyEnoV0XAK+f4IROqoKWSuYdWAZiXAsjXWYygmSUvJm+WZeKllHY8iLIDJCn2B1clH2KXwud45aCK8oiqIox5GRkcFHH33EN7/5Te65555IKwoiBWYWL17Mww8/TEZG3/ro9TiB2b59Ow8//HC328844wx++MMf9ikIRRkqhOsaEG6k/xUwqgAThAtsCxDuGwZtHxil51ZU7+TpgyvR0ch2JqELDVOa1Afb+FfxGhwWK0uzZ8Y6TEVRFGWIGU6NLI/Iz8/njTfeoKGhgcLCQqSUjB07lqSkpBPab48TmIaGBsLh7qsrhUIhGhq6mFqjKCcRIXRwXQ6OJRDeBTIIeg7Ckhfr0JQoCJsGr5duREpJmvPTNX2a0Ei1x1Plb+KNsk2clTEZh676XimKoihKTyQlJTFnzpyo7a/Ha2AKCgpYv359t9vXr19Pfn5+VIJSlMFOaC6EbRbCPk8lLyeRA61VlPsbSLLFdbk92RZHTaCZPc0VAxyZoiiKoihH9DiBufzyy/nBD35AVVVVp22VlZX88Ic/5IorrohqcIqiKAMpYIYxTROL0LvcbhE6hjQJmKEBjkxRFEVRlCN6PIXs7rvv5pVXXmHs2LEsW7aM8ePHI4Rg165dPPPMM+Tm5nL33Xf3Z6yKoij9Kt3hwWGx0WYE8GidC5a0hQM4dRsZdk8MolMURVGGtGHWB6Y/9TiBiY+PZ/Xq1dxzzz3861//al/vkpSUxLJly/j5z39OfHx8vwWqKErsSCnZ3VzOnuZywtIgz5XKjOQCbNrgLxndGxkODzOTCviwehduiwP9qH4/hjSpD7YwK3k0eXGpMYxSURRFUYa3Xp19eDweHn74YR566CFqa2sjC13T0lRJUUU5iTUEW/nT3uXsaColaIYQh/83wpXCTWPPZVxC37roDlZX5c+nuK2WQ201uCwOHJqVgBmiLewn25XMspEL1WeeoiiKosRQny6fCiFIS0uLdiyKogwyYdPggd1vsbXxEGn2BJx6AkIIgmaYYm8Nf9zzBj+acgWpjgT2NJdTH2jFZbEzyTMCh26Ndfh9kuFM5J7Jn+Ptii2srN6N3wjh0G2clTGZpdkzyHAmxjpERVEUZShSU8ii5uSa/6EoSlRtaTjEruYyMhyeDmWDbZqFHGcKpd46/nnoI6r8TRxqqyFohNGERrrDw6W5szknY8qQHK1IdSRwzciFfD7vNNrCAVwW+5BNyBRFURTlZKMSGEVRurW1sZiwaXTZ80Q7nJi8WrqeZHs8qfZ4nA4bITNMXaCFv+1/Hykl52VNG+iwo8auW7GrxEVRFEWJBjUCEzU9LqOsKMrwEzCCxxxBaQ75CJphRjiTcR5OcqyahczD06xeLlmHLxwciFAVRVEURRkmopbA1NXV8Yc//CFau1MUZRDIdCYBElN2vsQTMEJ4jQBxFkeXSU6KLZ6aQAtbGw8NQKSKoiiKMrgJQMgo32L9omLkhKaQSSl55513ePzxx3nllVdISEjgO9/5TpRCUxQl1ualjeO1svXUBppJsyd0SFRaQj4AUuzuLp9r0XQk0Br2A1AfaOWj2r3sbCzBRDI+IZv5aePJcKieKoqiKIqi9FyfRmAOHjzIj370I/Lz87ngggtwOBy8/vrrVFZWRjs+RVFiKMPh4eqC09GEoNRXR2OwjeaQj3JvPT4jiMfqwia6XiMSNMLoCJJsbnY0lvC/W//F3/evYEN9EZvrD/JM0Sr+d8u/+KRu/wC/KkVRFEVRhrIej8AEAgFefPFF/vKXv/DRRx+xdOlSfve73/GlL32Ju+++m0mTJvVnnIqixMg5mVNJtSewvGILO5vKMKTJ6PgMzs6cws6mUlZU7cRjc6Id1fRRSkltoJksVxLZziR+uv0FavzN5LiS2x9nSkmlr4FH9/2XbGcSOa7kWL3EIacx2Mba2n1U+hqxahamJuYyyTMCi6bHOjRFURSlG0emfUV7n8NRjxOYnJwcJk2axLJly3j++edJSkoC4Etf+lK/BacoyuAwPSmf6Un5tIUDGNIk/vC6lwkJOextrqTUW4fHFodLtxE0w9QH24iz2PlS/gLW1x+g2tfUIXmBSBWzLGcSJd46Vlbv4qqCBTF8hUPHmpq9PHFgBfXBNuThtUn/KdvAZE8ut4xfTKItLsYRKoqiKEr/6nECYxgGQgiEEOi6usqnKMNRnMXe4eccVzLfn3wJzxWvZUvDIWoDLVg0ncmeEVw6YjYzk0fy652vogmtQ/JyhBACm2ZhW2MxV6ESmOPZ1VTGo4X/xW+EyHYmoR/+nfqMIJsbDvLw3ne4e/KlXf6uh5vasjrWvbmZ8sIKbE4bE08bx/RFk7A5OpcEVxRFGRCqjHLU9DiBqaio4IUXXuDxxx/ntttuY+nSpSxbtmxINqlTFCV6RrhS+O6EC6n2N1EfaMVlsZPrSmn/bOiqgtnRhABzmH4A99Z/K7fSEvJ3+P0COHUbqfZ4djSVsLu5nEmeETGMMvZWv7yOf//mVZprmxGahpSSD55bw6ipedz0my+TmpMS6xAVRVGUE9Djy3QOh4NrrrmG9957j23btjFx4kRuvfVWwuEw9913H8uXL8cwjP6MVVGUQSzd4WGCJ4e8uNQOJ9fjE7IxpNllIiOlJGCEmZw4vE+4P0tKya6mMh7b91++v+kZfrjlnzxXvJb1dfuJt3Zdttqp2wgaYXY2lcYg4sFjzyeFPHv/i/jb/GSPySJnTCYjxmaRmp3Mvk1F/OXuZzDC6rtKURRlKOtTGeXRo0fzs5/9jP/7v//j7bff5vHHH+eiiy7C7XZTV1cX7RgVRRnCFqSN583yzVT6GshyJrWffEspqfI3kWB1sjBtQpfPLfc2sLpmN3taytHQmJaYx/y08SR3U7r5ZCCl5JXST3ixZB3ecBCHbsU8nNDUB1rJciZ1+bwjU3zD5vA+Of/w+bV4m33kjMnskOjZHFbSRqSwf8tBdq3dy5TTJ8YwSiXWwqEwm9/fwcevb6CmtI6ElHjmLJ7B7MXTcbqdsQ5PUZTjOKE+MJqmsXTpUpYuXUptbS1PPvlktOJSFOUkkeZI4OtjzuHP+5ZT4q3DpkU+doJmmASrk6+MPpN8d1qn562u2cPf9r9PY7ANq2bBlJJN9UW8WbGZW8YtYaInZ6BfyoDY0niI54s/xiL0z0zFM6kPtFLmqyfVHt+p4ljINBAwrKu5hUNhdny0G7fH1eUolcNlJxwy2LvhgEpghrGgP8hff/AP1r+zBdM0sTtslOwpZ8eq3ax+eR3f+N11JKap/lRKP1BrYKKmx1PIGhoa+H//7//R3NzcaVtTUxP/+Mc/uOGGG6IanKIog4uUkqagl/pAK4Y0e/y8WSmjuHfaF/hC/jxGx2cw0p3GZblz+PG0K1mY3vlE8mBrNY8Xvoc3HCTXlUrW4TLLOa5kavzNPLT3LZqC3mi+tEHjvcrtBMwwyXZ3h5NwTWjkuJIImwZV/qYOz4mMZjWS4UhkdvLogQ550DBNiZQSoXW/NlMIMI2ev3eVk89bf32fdW9sJDEtgZzRmaTmJJM9KoPU3BR2ryvkn794OdYhKopyHD0egXnwwQfZunUr3/72tztt83g8rFy5kpaWFv7nf/4nqgEqijI4bKg7wDsVW9nbUoGUkgynh7MyJnNO5hSs2vE/SrJdSXwhfx5fyJ933Md+UL2L5pCv02J1TWhkOZMo99WzpnYvS7JnnMhL6pG2cIA9zeWETaM9ieovUkp2N5cTp9u73J5m91Dpa6Ix5AWvxGVxYEgDbzhIit3NjWPPwWkZvlW2rDYLeRNy2LV2L57UhE7bw8EwAsGIcdkxiE4ZDHxtfla99DF2lx2n29Fhm81uJTE9gW0rd1FxoIqsURkxilI5aakRmKjpcQLzwgsv8Nvf/rbb7TfddBN33HGHSmAU5ST0dvkWnj64Er8RwmN1ogmd4rZa/rZ/Bftbq7hpzLlRbaK4rbEYh27tchqQLjQEgj3N5f2awIRNg1dL17O8civ1gTZMTFy6namJeVw7ciEZzsR+Oa4AZDffSEIIEm0upibmIYRGSVstTt3KOZlTOStjMnlxqf0S01AhhGDhFfPYs24/LfWtxCd/ulbKNCXVxbVkFKQx/azJMYxSiaXKomqaaprxpHVOcAHciXGUF1ZSvKtUJTCKMoj1OIHZv38/Y8eO7Xb72LFj2b9/f1SCUhRl8KjyNfKvQx+BhFzXp+Vn3VYHbWE/K6t3MyOpgAVp46N2THmc0ssD4ZmDq3i9bCN2zUqGw4MuNFrDftbW7qXK38g9ky+LejEBIQTTkvJZUbmDZJu7UwIXMsPoQuO8rGnMTxuPIU00hCpnf5TZi6dzYNsh3nt2Fc31LTjjHBiGScAbJDUnmet/ehXOOMfxd6SclIQQILr/jGm/W/1NKcqg1uM1MLquU15e3u328vJyNE01T1OUk82a2n00h3yk2uM7bYuzOJBSsqJqZ1SPOTkxF78R6vIkw5QmEsnY+Kxe7TNghPCFgz1Kjorbanmvcjtui4M0RwIWTUcIQbzVSbYzmaLWGt6r2t6r4/fU2RlTcFns1ASaO8QaNg0qfI3kxaUxK3kUcHg0Sp1odaBpGl+881K+9YevMHvxDOJT3KTnpXLJtxZz599uZtys4btGSIHs0RmkZCfTUtfa5faW+lbiPC5GTcsf4MiU4UDI/rkNRz0egZk5cyYvv/wyp512WpfbX3rpJWbOnBm1wBRFGRyq/I0I6PZE2anbKPVGt3z6ovRJrKzeRXWgmXR7QoemmBW+BtLsCcxPG9ejfW1uOMi7FdvY2VyGlJKR7nTOzpzC/NRx3b6mDfUHaAsHOow4HWHRdBy6lZXVu7gi99SoJxATPTlcP2oRTxWtpMRbh0VomIcnleXHpXLL+CXYdWtUj3myEUIw/czJTD9TTRVTOrI5bCy6ch7//vUrtDS04U78tGKdvy1AS30Li74wn7QRqtmpogxmPU5gbrnlFq666ipGjBjBN7/5TXQ9Mt/dMAwefvhhfv/73/Pss8/2W6CKosSGQ7cdc41gSBokR/mEenR8BteNOpMnD3zQXnpZIgmZBqn2eL4x9nwSbXHH3c9b5Zt55uAqAkYQt8WJQLCtsZidTaUcbK3m6oLTu0xAWkJ+hOg+abNpFlrDAULSwCZOqBp9l87KnMK4hGw+qtnDgdZqbJqFaUl5nJoyFrdVTX9SlBNx7rIzqC6uZfVL62iqacJis2CEDHSLzoyzp3LlHZfEOkTlZKUW8UdNj795r7jiCu666y5uvfVWfvCDHzBq1CiEEOzfv5/W1lbuvPNOPv/5z/dnrMoQI6UfAh8g/e+BWQkiEeFYBPZzENqJ1diX4YMQ2goyBJZcsM5AiOFbfak/TUvM463yzfiMIE694+/YlCYBI8S81J6NhvTGmRmTGOlOZ1X1LnY3l6MLjelJ+SxIG0+64/jvn1JvHf86tAYkjHB9urjdY3PRFPTyRvlmpiTmMT2p81QRj82FlJF58l0lMX4jRIbTg1VEr3DBZ+W4krmyBxXbFEXpHd2is+x/P8/cpTNZ//ZmasrqSEiO55RzpzHl9AlYrNG/KKEoSnT16q/0vvvu49JLL+WZZ56hsLAQKSVnnHEGV199NXPnzu2vGJUhSJqtyJZfQnA9IEA4gTpk6x7wvw8JP0Tova/wIs1WZNsjEPgIpDeybzSw5IP7FoR1UpRfiTI1MY8piXlsqi8i2e4mTrcjhCBghKgONJHlTGRRRv/83vPjUskfubBPz/2oeg8th0sxf5bH5qLZW8vK6l1dJjBzkkfzcsk6GoJtnRbqh0yDkBlmUfoktf5EUYYoIQTj54xh/JwxsQ5FGUb6Y82KWgPTQ3PnzlXJinJc0vscBNeBngniqCkvMgThPcjWPyM8P+rdPqVEtj4AgQ9ASwItNVIpRgYgfADZ8gtIuA9hyY3yqzn5+I0QG+oPsLH+AD4jxAhnMvPSxjHSnd7psRZN55Zxi3m08L9sbSymIdiKQKAJjZFx6dw09twejYgMtGJv3TEXuTs0G0VtNV1uy3YlsTR7Ji+WfEylr5EkW1x7FbKmkJfxCdmcnTmlP8NXFEVRFKUbPU5gvF4vd955Jy+//DKhUIhzzz2XBx54gNTU4d13QOlMmi0Q+C+IuI7JC4CwgpYCoc3I8EGEpaDnOw7vguDHkedrR1XEEnbQc8E4hPS/hXDfGJXXMZj5wkHW1+/nYFsNGhrjE7KYnpTfo4aStf5m/rDnDfY2VyABHcE6WcjbFVu4LHcOl46Y0+mk32NzccfEiznQWsWuw00d8+JSmZaYF9X+L9Fk162YdN9x3ZAmjmP8vj6fdyoJVidvlW+m2t8c6QNjsXNe5lS+kD+fBKuzP8JWFEVRFOU4epzA/PjHP+aJJ57gmmuuweFw8I9//INvfvObPPfcc/0ZnzIUGWUgmyOJRldEPJj1YByE3iQwwQ0g/aB1MfVMaJGEKfAhMu6Gk3pqz66mMh7Zt5wKX0N7w0MdjVHxGXx7/BKynEndPldKyZ/2LWdXUxlZziRsh0/gpZTUB1t5rngtmc4kTkvt3PNJCMHo+ExGx2f2zwuLshlJ+ayq3kXIDHdK7ExpEjLDzEnpfvqIJjSWZM/g7MwpFLVWEzINspyJpHRRTlpRFEVRjkst4o+aHicwL774Io8//jhXXXUVAMuWLWPBggUYhtFekUxRIjQia1O6u/ptHt7e2/dNIPK87pITYQWCQAg4ORf0V/mbeHDPm1QHWshyJLaPfgSMEHuby/nj7je5d9rncehdv/5dzWXsbi4jzZ7QnrxAJDlJscdT6q1jecVWTk0ZM+STwNnJoxnlzmBfSyXpjoT230nQDFPlbyTLlcTp6ROOux+bZmF8QnZ/h6soiqIoSg/1uPNkSUkJCxd+uph27ty5WCyWYza3jKaGhgauvfZaPB4PHo+Ha6+9lsbGxmM+5/rrr0cI0eHWXR8bJYosBaBngdnQ9XbZCJoHLL1c+K2lAxKk0c1+20DLBE7eHhkrq3dR5W8mx5ncYeqWXbeS5UziQGsV6+sOdPv8fS2VBE2jUzWxIxKsTg60VtEc8kU99oHmtNj4zoQLmOjJoSHYRklbHSXeOmr8zeS50rht/NIum3MqJy7gC/DJW5t45aG3+M+fl7N3w/4eNRBVFEVRlJ7o8QiMYRjYbB1PeiwWC+FwOOpBdeXqq6+mtLSUt956C4Cvf/3rXHvttbz22mvHfN6SJUv429/+1v7zZ1/DYCNlMLLQXbiG7BVwIWzguDBSLcxsAJF4eLG9jCQZZgs4L0PovWwUZlsA2j/ArI4kKkf/fqQPpIlwnDdkf2898Untfuy6Ba2L12jVLJhSsq2xuNuRBSnlMZtSCiL3nyynmhnORH489fNsbyqJrPmRkgJ3GjOTR3YYgVKiZ++G/Tx577+pOFAFgDQlVoeVCXPH8NX7rsaTmhDjCBVFUZShrsff4FJKrr/+eux2e/t9fr+fb3zjG8TFfdpQ7sUXX4xuhMCuXbt46623WLt2LaeeeioAjz32GPPmzWPPnj2MHz++2+fa7XYyMwf/nH0Z2o30vxGp3IUJWhY4FoPj3KHZ38RxIRg14H8dzEO0TykTDrCfjYi7vte7FHoKxH0F2foIGMWgJQI6yBaQQbDNA8d50X0dg0xQhtFF9wOnmhAEzFC32wvcaehCw2+EcHTRfLIl5GNMQiaek2iBukXTmZFUwIykgliHctKrPFjNo3c+RX1lA+l5aVhtFqSU+Fv9bFmxk8e+/zTf/fNN6BY17VhRlGFIrYGJmh4nMNddd12n+5YtWxbVYLqzZs0aPB5Pe/ICcNppp+HxePjoo4+OmcCsWLGC9PR0EhMTWbRoEffddx/p6Z1LxR4RCAQIBALtPzc3N0fnRRyDDKxBtv4ezKbD1bV0MAqRrfsgtA3ivzvkkhghdIj7KjgWQeAjpFmN0BLBNhcsUxDHOAk/5n4d54OWhPS9GqlKJoOgZUTud16MEPbj72QIG+VOp9Rb1+U2KSWmlOTHpXX7/CmeXEa609nXXEG2K7lDMtQc8oEQnJM59aQexVL6z6qXPqa2rJ6csVloWuQ9JITAGe8kbYTGnk8K2blmL1MXToxxpIqiKMpQ1uME5uhpWAOtsrKyy6QjPT2dysrKbp+3dOlSrrzySvLz8ykqKuJ///d/Ofvss9mwYUOHkaSj3X///fzkJz+JWuzHI80WZNufwGwDPf+oaVGJkfsCK8A2HRxLBiymaBFCgGUMWMYQzdNhYZsD1tkgGyLT7bSkIZfg9dUZ6ZNYW1tIY7CNRNunI59SSqoDzXisTuanjuv2+RZN5xtjz+MPu9+gpK0Wi6ZjETp+M4hVs7A4axpnpKuTS6VvNryzBafb0Z68HM0RZydcFlYJjKIow5Y4fIv2PoejmE4Cv/fee4+bLHzyySdA13P2pZTHvFL8xS9+sf3/T5kyhdmzZ5Ofn8/rr7/O5Zdf3uVz7rnnHm6//fb2n5ubm8nN7cfGiMGPwKgGPadzdS0tDswGpP9tsC9WV8WPIoQAkRzrMAbctMQ8LsqZyWulGylpq0UTgpBpEDTDJNriWDbqDDKcicfcR15cKj+aegWravawrrYQnxEkLy6F09MmMD0pH62Po2PK8FJdXMOOj/YS8AZIy01hyukTCHiDx54eJiAYCA5ckIqiKMpJKaYJzC233NJelrk7BQUFbN26laqqqk7bampqyMjooidIN7KyssjPz2ffvn3dPsZut3c7OtMvjLLIf0U3/xSaG4xyIiWEHV0/Rhk2hBBclb+AsGny3KE1NITagEgVMk0I/EbwuIk9QKItjotyTuGinFMGImzlJBL0B3nut6+y5tUNeJu9IARCE2QWpBPncdFcVwl4Oj3PNEyQgoy87qc4Hs3X5ufg9hKMsEH26AySM7vvb6QoijIkqDUwURPTBCY1NZXU1NTjPm7evHk0NTWxbt065s6dC8DHH39MU1MT8+fP7/Hx6urqKCkpISsrq88xR5+NSGlg2XV/ExmOdJqP7T+VMohsayzmvartOC12cuNSsWkWDGlSH2zlqQMrEQiWZM+IdZjKSerfv3mV955diTvRTfboTIQmCAVCVBZVIQEjaNDW5CXO42p/jpSS2rJ6PGnxzF48/Zj7N8IGbz+xghX/Wk1DVSPSlLgSnJxy7jQuv+1CElJU6WtFUYYolcBEzZCYKzJx4kSWLFnCjTfeyNq1a1m7di033ngjF110UYcF/BMmTOCll14CoLW1lTvuuIM1a9Zw8OBBVqxYwcUXX0xqaiqXXXZZrF5KZ7YZkQRFejtvkxJkK9hORXQ3QqMMK1JKXildT2vYT7YzCbtuRQiBRdNJd3jQhOC10vV4w4Hj70xReqmiqIo1r60nPsmNJzUecXiti9VuJWtUBmbYwJOWQHN9KxVFVbTUt9JU20xZYSUWm4Uv3HHpMUdSpJT8+9ev8MLvX6OlvpWUrCTSciMXuVb86yMe/s7faGvu4rNSURRFGVaGRAID8MwzzzB16lTOP/98zj//fKZNm8ZTTz3V4TF79uyhqakJAF3X2bZtG5deeinjxo3juuuuY9y4caxZs4b4+EF0Bc8yGaynRHqbmK2RpAUiIy9GaWSBuuOC2MaoDBoVvkYKWypIsrm7nCaWbHNTG2hhe1NJDKJTTnY7Vu/B1+wjPsndaZsQ4vDoiOSq73+OkVPzMQ0TIQSnXnAKt/y/rzH/0jnH3P+hnaWsfOFj3IlxpOYkY7VbsVh1PKkJZBaksXf9fta+tqGfXp2iKEr/Ev10G46GzGX95ORknn766WM+5uhOz06nk7fffru/wzphQgiI/y6yRUBoI5i1tL8l9QyE+1sI69hYh6kMEl4jQEiauEXXC6Utmo4JeMOxXSgdNMM0BNuwa5YO1dKGk6aglzW1e9nacIiQNBjlzmBB2njy4o4/bXawCvqC7WteumKxWgj6g8w6fzrnXLMQb7MXzaLjjOvZ+r1N727D1+ojuYtpvla7Fd2qs+bVTzjnmoUn9DoURVGUoW3IJDAnM6F5IOFHkb4moc2R0sB6DthOQ2idr3QqJ6emoJf19fup9bfgsNiYkVRAniulw0hLss2NQ7PiM4LYu2hE6TeCWIVGij0275u2cIC3yjezomoHzSEfmhBMTMhhSfZMpiXlxSSmWChqreaPu9+kzFeHQKALjU31B1lesZVrRp7OOZlTYx1in6TkJCOEIBwMY7F1/vrwtvhIyvDgTnQhhCDO07vktamuGSFEt0Uo7E479VWNfQl90PO1+dn07jaKd0UKu4yens/0MydjcwyPEvGKMiyoNTBRoxKYQUIIAdZJkZsy7HxQtZNnD66mIdgKgETyYvFa5qeN5/pRZ9IU8rKnuZywNBkVn8HGugPEW50dGlFKKakNtDDSnc7EhJxujxUwQviMIHEWO1Yteh8BvnCQ3+96nS2NB7FrVuIsDgxp8En9fnY2lXLj2HNZkNZ909mThS8c5ME9b1HmrevQLFRKSU2gmScPfEi2M5mJnu7/jQaraYsmkToimZqyOjIL0jskGkF/iKAvyILPnYrV1jm57omE5HiklN1W0gv4gmQU9KyK2VByYOshHv+fZ6ksqsI0Imc4mq4xYlw2N/ziGnLHD733iqIoSn9SCYyixNim+iL+uv99QqZBljMJXWhIKWkJ+3infCubGw7iN8K0hn0A6EIjaBocbK0m2R6PU7cSNI3DzS1dXFOwEIvWeYpZubeBtys2s7Z2HwEzTJxu5/T0CSzOmk5yFEZs/lu5ja2Nh0i3ezqMDsVbnFT6G3n6wIdMT8zHbT25y4Gvr99PqbeOzMP/lkcIIUizJ1Dqq+P9qu1DMoFxxjn44l2f428//AdlhZUkJLuxWC14m734vUEmzRvHWV9a0Of9zzx7Csuf+oDWhjbikzu+J0PBMEYozGkXzTrRlzGo1Fc28Oc7n6SmpI6MvNT2ka1QIETx7jL+fMeT3P3UrbgTh+dUTEU5qUgQagQmKobMIn5FORlJKXmzfDNeI0iGw9N+wiuEIN7ixGsE2NZYQliGyXGmMMKZQoLVhUXTsGoWTGnSHPIRNg3mpo7hzkmXdDlV61BrDffveInXyzbhN0LYhIXmkI/ni9fyix0vU+tvPqHXYUiTFVU7sAi909S2IyfudcFWPqkrPKHjDAWFLVUYUmLtIokUQuDS7WxrLOmwZm8oOeWcqXz7wa8xZ8kMpCnxewMkpCVw+W0XcPMfv0Jcguv4O+lGwZQ8Flw6l5b6VurK6wkHw5iGSVNtC5VF1Yw5ZSTzL5kdxVcTex+/vpHqQ7VkjUzvMC3PareSWZBOeWElG97ZEsMIFUU5mXz44YdcfPHFZGdnI4Tg5ZdfPu5zPvjgA2bNmoXD4WDUqFE88sgj/R/ocagRGEWJobpAC3ubK0i0ujpNmWkN+/EZocMlHQTa4e1uiwOHy0qFv4ELsmdyWupYXBY7aY6ELo8hpeTJog+p8DUywpWMdjhJclsdhE2D/a1VPF+8lm+MO7/Pr8MXDtIQbMNl6boJ7JERoerAiSVKQ4HswSRnOcQvmY2bNZpxs0bTXN9C0BckITUBm71v08aOJoTgqrs/hyc1ng+eW0NNaR1SSlzxThZefipX3H5Rr9fVDHZbP9yJxWZB0ztfT7RYdYQm2L5qN4u+0POeZ4qiDFKDYA1MW1sb06dP5ytf+QpXXHHFcR9fVFTEBRdcwI033sjTTz/N6tWrufnmm0lLS+vR8/uLSmAUJYaCpoGBiUN0PvlrCnmRSDShYX7mar1F07EKCxsbivhiwbFPbA60VrGnuZwUe3x78nL0fjxWF+vq9nNloIUUe99KjNt0CxZNI2gYXW6XUiKROPSTf0HySHc6mtAIm0aXU/m8RoDZKaO6Xag+lCQkR78kvcVq4eJvLuacZWdwYOshjLBBzphMUnNSon6swSAUCKF3kbwcoekawUBoACNSFOVktnTpUpYuXdrjxz/yyCPk5eXxhz/8AYj0Zly/fj2/+c1vYprAqClkihJDyXY3CRYnbV00ngybJqaUCOiy4phV02kJ+Y57jGp/M34jhEOzUBtoYW9zOVsbDrGzqZQKXwNWTcdnBKk+gWlkNs3CnOTRtIb9XU6Nagn7cOo2ZiTm9/kYQ8XclDFkOZOo8DdgSrP9/iNFFhy6jbMypsQwwqHBFe9kyoIJTF80+aRNXgBGTskj4At0+XcjpSQcDJM/eUQMIlMUZShpbm7ucAsEotPQes2aNZx/fscZGosXL2b9+vWEQrG7uKISGEWJIYduZVH6RHxGkIDR8YPAqukY0sChWUmwODs9128EyXQmHvcYVk1HAAfaqjnUVkNL2I+Jid8IUu6tZ39LFYY0sZ1gRbLzs6aTYo+nzFdP0AgDkROwpqCXppCXeanjhnQPlJ6Ks9j51rjzyXB4KPXWU+FroMrfSIm3DgF8KX8BUxJzYx2mMkicetEsnPFOGqubOtwvpaSuvAF3kpu5S0+JUXSKokSV7KcbkJubi8fjab/df//9UQm5srKSjIyMDvdlZGQQDoepra2NyjH6Qk0hU5QYu3DELPa0VLC18RBWYcFlsRMyw/iNIDbNQqI9rtN0I78RBAQL0yced/8TPZGrtw3BNhy6tVPp5dZwAKcRJNeVfEKvI9+dxm0TlvJ44XuUeesxD6/0iNPtnJ81jWtHLhrU06Z84SDr6grZ3lRCyAxTEJfOvLRxZDg8vd7XuIRs7p32BVbX7GFTfREhM8yY+ExOT5/A2PjOTRqV4Wv09AIu+eZiXnnoTcoKK3DFuwCJt8WHM87B5797ESPGqveMoijHVlJSQkLCp2th7fau16T2xWe/u4+MGMfyO10lMIoSY3EWO7dPvIh3K7exomonjYcTjUtGzCZsGrxfvZMKXwMeqwtNCFpCfvxGkDkpo5mfOu64+7cIrb00syklOoAAJIRMA+vh7ftbq0+4tO8kzwh+MfNqtjQcotLfhE3TmZqYR5Yz6YT229/KvPX8YfcbHGqrQSIRCFbX7OE/ZRu4btSZLEyf0Ot9ptrjuXTEbC4dcXJVzVKiSwjB4q+cxYhxWax88WP2bjiAAKafNYUzrjiN8XPGxDpERVGipR8X8SckJHRIYKIlMzOTysrKDvdVV1djsVhISYnd9F6VwCjKIBBnsXPJiNlcmHMKPiOIXbNg1SxIKRmTkMnb5Vso9zUggUSrk4tzTuHiEbO7XBvzWbWBFiyaToYzkaZgG37z06lqVqGT40wmIMOUeGuj0pvEqlmYnTL6hPczUAJGiAf2vElRaxVZzuT28semlFT7m/jr/vfIdHrUyInSb4QQTDl9IlNOnzgormwqiqIcMW/ePF577bUO973zzjvMnj0bq/XEq0/2lUpgFGUQ0YWG2/Jpo0chBOdkTmVR+iTKfQ0Y0iTTkYjT0vNqXvrhEZZUezzZzkSagj7C0sCq6XiscViERqmvvsPUsuFkY30RB1tryHQmdejdoglBhsNDibeO9yq3qwRGGRAqcVGUk5c4fIv2PnujtbWVwsJPe7IVFRWxefNmkpOTycvL45577qGsrIwnn3wSgG984xs8+OCD3H777dx4442sWbOGxx9/nH/84x9RfBW9pxIYRRkCLJre5wXw6Y4EcuNS2NdcSY4rmTRHxysmTSEvcbqdiQnDs9LR3paK9iIGYdMgaIbRhIZdsyCEIM5iZ3PDIaSU6uRSURRFGdLWr1/PWWed1f7z7bffDsB1113HE088QUVFBcXFxe3bR44cyRtvvMF3v/tdHnroIbKzs3nggQdiWkIZVAKjKCc9TWgsyZrBgdZ3qAu0kGxzt5+It4UDNAXbODtzCtmuwb1Opb+YUmJIg5K2OhpCrRimCUIQp9tId3gQCIyjyiEriqIoSp8MgkaWZ555Zpdl24944oknOt23aNEiNm7c2MvA+pdKYBRlGFiQNp76YCsvlayjxFt3+F6JXbcyL3Uc1406M5bhxVSaPZ6GoBdTmuiahq5FCh60hP20tQWI022cnTlVjb4oiqIoyiChEphhTBoVEPgAGdoN6AjbNLAvRGgnVk5X6ZuwabC1sZhdTWUY0iQ3LoU5KaM7rInpKyEEl4yYzezk0Xxct48afzMui52ZSQVM9OSgDcD6F78RYkP9AXY1lRI2DfLdaZyWOpYkm7vX+5JSsrnhIB9U72RfSyVWoTMreRSLMib1eqpdU8jb3nDSJiztk5R1qeEzgrTIAKemjO11jIqiKIpyNAGIKI/ADNdLayqBGaZkYCWy9SEw6wErYCKDq8D3CsTfgbBOinWIw0q1v4kH97zFvpZKwtIAGUk6XnAk8PUx5zEtKS8qx8l2JXGZa25U9tUbZd76w5W+qjHbqyzBKyXruWHM2b2qWial5N+H1vBq2QaCZhiXbsOUkldK17OyZjffHHseM5NH9mhfITPM2tp9pDsSaAx58RnB9mIGpjTR0XDoNoJm7LoNK4qiKIrS0fAsOzTMyfABZOuDIFtBzwfLCLDkgZ4LRjmy5TdIs+n4O1KiImSGeWDPm+xsKiPJ5ibXlUpuXCqZjkRq/M08tPdtyrz1sQ6zz/yHyxTvb6kiw+EhLy6VvLhUcpzJNAbbeGTfcg611tAWDrCqejevlq7n3cpt1Adau9zfxvoiXi1bj12zkOtKIcUeT5ojgVxXCk1BL48WvktT0Nuj2NrCAVrCfpJt8YyPzybbmYRDt2LTLaQ44hmbkEWC1UldsOtYFEVRFEUZeGoEZhiS/nfBbAC9IHIZ/Aihgz4CjFIIrATnRTGLcTjZVH+QwpZKMhyeDn1dLJpOtjOZEm8dK6p2cM3IhVE9bsgMs7G+iPX1B2gJ+cl0eJifNo6x8VlRXe+xof4ARa3VZDkTsWqffuRoQiPLmUSJt46/HVhBTaCZWn8LEokEEqxOlmbN4LK8uR1KPK+o2kHIDJPhSOxwHCEEmc5Eyn31rKsr5LysaceNzaFbsQqdoBnGbXWQ7Uomm0+nUEopaQy24dKj19FYURRFGaYGwSL+k4VKYIaj0CYQzo7JyxEi0gdDhnYiVAIzIHY0lRA2zS6bUgohcOo21tUVRjWBaQp6eWDPm+xoKsGQEl1ohE2Dd6u2c37WNK4pOD1q62J2N5VhStkheTlCCIGUkg+qdpLpTCTD4cGi6ZjSpCHYxnMla7FoGp/LjUx7k1Kyr6USl971uiBdRBbgF7fV9ig2h25jbspo3q7YSqItDu0zfxNNIS9xVgen9HBKmqIoiqIo/U9NIRuWTI6/7GuYpvQxEDKNY27XhCB4nMf01t/2v8+WhoMk2+LJdaWQ7Uwi15WCTVh4vWwj71Zuj9qxwvJYsUuaQ972Bp2Ww40kNaGRYo/Hrll4s3wLrSE/EEl4dE3D5FhljUWvmnIuzp5BmiOBMl8dfiMIRNa/1AVaaA37OTtjCpnOxB7vT1EURVG6JPvpNgypBGY4sk4F6YWu6oBLA5AI6/gBD2u4ynElI6C9EtZn+Ywgo90ZUTtecVstmxoOkmRz4zhq1EcIgcfmQiD4b+U2wlFKmvLj0hCCLnup+I0QPiNIvNXZ5bS1RGscDcFWtjeVtN93StJIvOFgl3Xsg2YYXWhM9OQcNy5TmmysL+Llkk8QQNAIU9JWx6G2Gsp8DVg1ncty53J1wYLevWBFURRFUfqVSmCGIWE/F0Q8mFUdkxhpglEOWjrYz4hdgMPMvNRxJNndVPmbOp2UN4e8WITGGRkTo3a8fS0VeI1gt+WZE6wuyn0NVPmjU8jhtNSxpNriqfI1dnp9jcE2EIKUY5RSDplh6gIt7T+flTkZj81Fpb+xQ9IXNMNU+hoY6U5nRlLBMWMKmwaP73+f3+x8jZU1u2kO+XDoNoQQxFsdLCs4nV+fsowvFSzAoulIKdnfUsW6ukK2N5YQMsN9+2UoiqIow5aQ/XMbjtQamGFIWMeD+0Zk21/AOAjCAUiQQdBSEfG3qV4wAyjZ7uYro87k0cL/UuKrI063owmNtrAfXWgsyZrBnOSelxk+nuN91kW7pnyiLY4bxpzDI/uWU+Ktw6nb0ITAGw5g0XRSbe5Oa0/8RpAqfxP1gRZC0uSpAx9yoLWKS3JmM8qdwdfHnMNf979Pma8+8tYFdCEYE5/FreOXdrme6GjvV+3g3YptxFudxFud7feHTYNyXz2bGg5y8YhZQCThe7ZoFftaKgmYISxCJ8uZyKUj5nBG+kTV4FJRFEVRBphKYIYp4VgCljFI/3sQ2g7CgrDNAvtZCD071uENO/PSxpFij+e9ym1sbDiIKU1mJBVwVsZkTk0dE9WT5JFxaTg0K14jQFwXozDNIR8ZTg/pjoSoHXNWyih+6LiCD6p2sKG+iLBpcErySBZlTGJdzT7ertxKgtWFRdPxGUH2t1TiCweRQJzVjlO3saJqJ7uayvjexIs4NXUsY+OzWFO7l+K2WixCZ3LiCGYljzpu8hI2Dd6t3HZ4tMXZYZtF00mze9jXUsHu5nIcupXf7vwPdcEWkm3xpOkJBM0wFb5GHit8F0OanJ05JWq/J0VRFEVRjk8lMMOYsIxBuMfEOgzlsHEJWYxLyMKUJqaU7Qvao22UO4OJnhw21hdh06xYjzpOW9hPWBqckzGly6phJyI/LpUvj1rEl0ct6nD/CGcyha1VHGitxmWxU+tvpi0cQBcadt1CvisNt9WBxxZHqbeOZw6u4n+nXEGy3c2FOaf0Oo7GYBsVvsZOycsRDt1KXdCgqLWafS0V1ASayXOltieRdt1KljOJSl8jL5R8zLzUcTgttt7/QhRFUZRhpT+mfA3XKWRqDYyiDDKa0PoteYHIYv0bxpzN2PhMKv0NlHvrqfE3U+qtoznkY1HGJBZnT++3439WqiOBuyd/js/lzsEiNFrDfqyaTqo9njHuTNzWyCiRJgQpdjf7mispaqvu+wGFiEyTO8aHvkTSFgqwpeEQida4LkfAUuzx1Ppb2Np4qO+xKIqiKIrSa2oERlFOEo1BLwfbqpFSMtKdTqItrtvHpjs8/GDK5ayp3cua2r20hvxkOZNYkD6eU5JG9msC1ZVku5tlIxcyPj6LX+54hXSHB0cXoxou3U59sJXaQAuj+liZLcXmZkRcKvuaK9qTo6N5jQB2zUqG00PINEiwdj26YtV0JJLmkK9PcSiKoijDjGpkGTUqgVGUIc4XDvLvQ2tYdbiaFkC81cGCtPF8MX8+LkvXXeTdVgfnZU3rUcd6KSUH22pYU7OX6kATbouDWcmjmJqYF9VkJ9Eeh91iQ3az5CdohrEIHZfe9WvqCSEEi7Omsb+lkoZgG4lWV/sIS8AIURdoZfbh12bTLPiNEA69cxITMsMIIqWnFUVRFEUZOCqBUZQhLGwaPLz3bdbU7sNtcZDh8ACRhfivl22k2t/M7RMvPKH1LFJK/n1oDW+Ub6QtHEQTAlNK3q3czoykAr41bnGXIxl9MTIunVxXMkWtNeS4OlfCqw+2kuHwMC4h64SOc3raBCq8DfynfCMl3josmo4hTTRgcuIIvj72XJLtbmYmF/BB1U4SrK5OldJqAy2kOxKYlph/QrEoiqIoitI7KoFRlCFsY0MRn9TtJ82e0GEhebLdjdNiY1NDERvqizgtdWyfj/F+1Q5eKv0Ep24j15XSPlrhCwf5pG4/fz+wgm+NX3LCrwUiVcAuHTGHh/e9Q6WvkVR7PBZNJ2wa1AVb0YTg0hGzsZ1ggQEhBFfmz+OUlFF8VLOHcl8DcRY7s5JHdahkdumIOexuLqfUW0uSzY1TtxGSBnWBFhy6lS/kz+/QDFRRFEVRlP6nEhhFGcI+rt2HgdllFSynbqNOStbU7O1zAhM2Dd6p2AJA0mfW1DgtNhKli0/q9lPmre9yxKQv5qWNI2iG+XfxmkhzTyQCQbLdzWW5czgzY3JUjiOEYEx8JmPiM7t9TF5cKndNvIR/HfqIHU2lNId8WDSdUe4MLsudw6knkBgqiqIow4yUHRuIR2ufw5BKYBRlCKsPtGIV3f8ZWzWd+mBLt9uPp8rfRJmvgURr1+s84i1OSn117G0uj1oCA7AoYxJzU8awueEgTSEvCVYn05MKiOtmPU9/ynencdfkSynz1lMXaMFlsTPSnY4uVBFHRVEURYkFlcAMctKogMAHyPB+EDaEdSbY5iG07itMKcNHst1NSIa73R40w6TY4vu8f1NKpIyMgByL0Q9lUJwWG/PSxkV9v32V40qOapKmKIqiDC+qD0z0qARmEJP+d5Ftj4HZQKRlj0T63wPLSIi/G2HJi3WISozNSx3H6pq9eMOBTtXGfOEgutBOKAlIdySQbHdTH2jtcprakZLD+XGpfT6GoiiKoihKb6gEZpCSoZ3Itj+BDIKeB0emq8gQhAuRLb+CxN8ixMBPqVEGjxlJBZyaMprVNXuJM4IkWF2ApMrfRGOwjXSHhz3N5STb3YxxZ3bZkPFY7LqVszOm8MzBVZ2SpLBpUBdoZUZSAWPc3a8jibbGYBtra/dR0laHVdOZ4MnhlOSRJ7ywX4meYCDEtg93UrStGCmhYPIIpp85GZuj6546iqIoitIb6ht/kJL+t8FsAT0fjj7pFFbQcyB8AILrwL4wdkEqMWfRdL457nzSHR4+qN5Flb+RhmArATOMXVjxGyFeLd3A8sptnJ0xmWtHntHrvi1Ls2dQ1FbNx7X7qA+24tBthMwwYWkwyp3ODWPO7nVi5AsHKfHWAjDCldJtr5rPWl+3n8f3v0+tv7l90tqb5ZsZHZ/BreOXkulM7FUcSvSV7i3nL3c/Q+necgzDRIhIwYScMVl87f6ryZ+UG+sQh6RQMMT2Vbsp3HQQaZqMGJ/NzHOm4oyLTglzRVH6nzAjt2jvczhSCcwgJKWE4EYQcR2TlyOEDTAgtEslMAoO3cY1Ixdy8YjZPLznbVbX7iHPlYrncNUwKSPd4t8q30Kaw8NFOaf0av923cot4xYzN2UMK6t2UeFvxG2xsyBtAgvSxveqkWPQDPNa6Qbeq9xOQ7ANgESbi9PTJjAtKQ+rZmGEK6XLxfqHWmt4ZN9yWkN+sl3J7Yvog0aYvc3lPLDnTe6ddqUaiYmhloZWHvne3ykrrCQ9LxWbPVJiOhQIUbq3nD/f8STff/LbeFITYhzp0FJ5sJq/3P0MB7cXY4QNEAIhBJkFaVz/06sYN2t0rENUFEUZUOqbftAyiKx7Od5jFCUibBoUtlaSYotvT14gcvXbY3PhN0Msr9jCeZlT2/uc9JRVs7AgbTwL0sb3OT5DmjxW+C4rqnbg0Gwk2eKQUlLSVscjjctx6FZSbG4S7XEsSp/E53Ln4NA/nXL0ftUOGoPeDr1oAGy6hUxHEvtbqthUX6RKG8fQ+re3UF5YSdbIdHTLpyN9VruVzJHpVBZVs+7NTZx37aIYRjk0VB6sprasHqEJnvvNqxzaUUJ6bio2Z+RvIhwMU3mwmse+/zR3PXELaSNSYhyxoijHJQ/for3PYUglMIOQEAJpnQSBVUAXX0oyDAiwjBro0JQYaQ35+bhuH9sbSwiZBqPjM5ifOo6Mo6ZMFbZU0hTyku3sulJWotVFTaCFQ221J9zJvi+2NRazuno3yTY3cRYHEklxWy3NYR8C8BshrJqFtnCAF4o/psxbz60TlmI9PKKyof4ATt3W5XQ1m27BkCY7m8pUAhND21ftQmhah+TlCN2io1l0tqzYoRKYY6g4UMWLf3ydnWv2EvAG8HsDNNe2kD0mE6vj0wsPFpuFrFEZlBdWsebV9Vxy8+IYRq0oijKwVCODQUo4FoOwg1nXcYM0wSgHPQtsC2ITnDKgilqr+d+t/+LP+/7L6po9fFK3n2eKVvGDLf9kdc2e9scZ0gQJWjclj4UQSCkxZWwmzK6p2UtIGsRZInP2W0P+w31sdBwWGwJBS9hPqj2BVHsCn9TvZ0N9Ufvzw6aBdpy1NmFTjUrGUtAfQrd0/7WiWzSC/tAARjS0VJfU8v9u+QufvL0Zq91Kel4q0pSEgmEqDlRRV9HQ4fGapmFzWNn0/rYYRawoSm+IfroNRyqBGayss8H5xchoS/ggGFVgVIBRDHoqIv67CM0d6yiVfuYLB3lwz1uUtNWR6UhkhCuFHFcyua4UvOEgjxe+x/6WSiDSNT7OYqcl7OtyXy0hHwlWFyNcsZlqUu1v6tB0syHYiilNdC3yMSQEBMzIya3TYsOUktU1u9sfPzo+E68R7HLfhjQRQG6cmkYTS3kTcwgFwpF1fJ8hpSToD5E/aUQMIhsalv99BeX7q8gZnUl8Ulxk1ErXsNgsIKHqYA3hUMckXbdohFRSqCjKMKMSmEFKCIFwfQmR8BNwLAY9A/R8RNyXEZ5fIazTYh2iMgA+qd9PibeOLGdSh+phQggyHB6aQz7er9oBRBotzkguoDHoJWR2bG7pN0K0hf0sTJ+A2xqbqkWJtrgOTTcDZrjDdDAJWMWnr9GmWaj2N7f/fGbGJGyaTuPhxf/tz5OSKl8jqfZ4TksdPI0vh6O5F5yCy+OkvrKx07bG6iacbgenXTRr4AMbArwtPta/swV3Yhya/ulXs9PtACmx2i2EgiGa61o6PM/vDVAwWVV2U5QhQcr+uQ1Dag3MICaEANt0hG16rENRYmRPUzmmlFi7KH0shMBlsbGl4VD7fV8euYgafwt7WyrQhYZNsxAwgoBgVvJoLsudO4DRd3Rq6lg+qtmL3wji0G1YNR15ePXhkWltSbZPRxVDpkGi9dNiBLOSR3FRzin8p2wjJd5aXLodU0p8RpBEm4uvjTmbxF5URFOiL3/iCD53y1Je/MPrlBVWEJfgAiFoa2zD5rRx6beWMGpafqzDHJTamrwEfMFIwnKUxPQEakrqCAXDICEc+vQiQFNtMzaHjXmXzBnocBVF6Qu1iD9qVAKjKIOYyfHWqwjMoz69ku1u7pn8OVbX7GF1zR4agq2kxWeyMH0C81PH9br6WDTNSh7JjKQCNtTvJ8HqIsHios7fQtAIY0gTj9XVnoAEjBASyfy0T0dUhBBclb+AsfFZrKjaSWFLJRZN4+zkyZyVMZkCd3qsXppylPOuXUTWqAxWvrCWPZ8UAjDr/OksvOI0pi6c2OueQcNFnMeFzW4l6Aviine232932skenUHpvgrCoTD+tgCNNc20NXmx2iws+drZTJqnRh4VRRlehkwCc9999/H666+zefNmbDYbjY2Nx32OlJKf/OQnPProozQ0NHDqqafy0EMPMXny5P4PWFGiYKQ7HSEiazyO9D05ms8IMDelYw8It9XB4uzpLM4eXCN3Vs3Ct8cv4ZmDK/m4tpDWsB+LphMwQyRYXOTHpQKCpqCXppCXqYl5nJo6psM+hBDMThnN7BTV92Iwm7JgAlMWTIj0LIEuq5IpHbninZxy3jTee3YVCSnxHaaRJWcl4W31428LkJCagK4JZpw1mdMvP42ZZ09RSaGiKMPOkElggsEgV155JfPmzePxxx/v0XN+9atf8bvf/Y4nnniCcePG8bOf/YzzzjuPPXv2EB8f388RK8qJOzVlLK+UrqfS10C2M7n9REVKSX2wFYdu48yMoZOQu60Obhp7HpflzuVAazU+I8iWhoNsbSymKtAUeYzFwVkZk1g28owOfWCUoUclLr1z3rWL2PHRHsr3V5KUkYgz3kk4GKaxugmrzcLV/3M5Z199Okj1u1UUZXgbMgnMT37yEwCeeOKJHj1eSskf/vAHfvCDH3D55ZcD8Pe//52MjAyeffZZbrrppv4KVVGixmNz8Y2x5/HQnrcp8dZh0yxoQhAwQjgtNr6YP58piUNvAW+6w0O6wwPAWRmTqfU3s7+1CgmMjEvr0N9GUYaLrFEZ3PLAV3n+d6+xb8MBGmua0S0aabmpLL7+LM74/GlqtEVRhjAhI7do73M4GjIJTG8VFRVRWVnJ+eef336f3W5n0aJFfPTRR90mMIFAgEAg0P5zc3Nzl487GUkpIVwIshGEByxj1ZflIDA1MY97p13JyupdbGwoImQajI/PYmH6RCZ4cmIdXlSkOhJIdSTEOgwlBnxtflrqW3HE2UlIViPjueNz+M4jN1G6t5y68gbsLjujp+djc6jRSEVRlCNO2gSmsjLSGyMjI6PD/RkZGRw6dKirpwBw//33t4/2DCcyuAXpfRrCe0EGQdjAMhZcVyNsp8Q6vGEv05nIlfnzuDJ/XqxDUZSoaKhuYvmTK/j49Y34WvxYbDpTTp/AeV8+k5FT8mIdXkwJIcgdn0Pu+JPjAoWiKIepKmRRE9M+MPfee2+k38kxbuvXrz+hY3x2BEFKecxRhXvuuYempqb2W0lJyQkdfyiQwS3Ilp9DaCuIeNBzIv8NbUe2/AIZ3BjrEBVlQEgp2d9Sxab6Iva3VLaXd1aiq6GqkQdufow3HnsXf6sfV7wDEHz06noe+NZf2PXxvliHqCiKogxiMR2BueWWW7jqqquO+ZiCgoI+7TszMxOIjMRkZWW1319dXd1pVOZodrsdu93ep2MORVLKyMiL2Qh6fqQdOoCIA+ECoxjpfQqsMxBdVMFSYktKyZ7mcjY2FNEWCpBsd3Na6lhyXMmxDm3I2dFYwr8PrWF/axVBM4xNs1DgTuPKvHlMT1K9S6Lpjb+8S9G2YrJGpWOxRr6GnPGQkOKm4kAV//rlS/zvv7+nFqorinJSEYdv0d7ncBTTBCY1NZXU1NR+2ffIkSPJzMxk+fLlzJw5E4hUMvvggw/45S9/2S/HHJLChZFpY1rap8nLEUJE7g/vjzzGOiE2MSpd8htBHit8l49rC/Ebofb7XyvdwEU5p3BF3qlqDVMP7Wwq5fe7X6cp6CXFHo9dtxIwQuxpruCPu9/g1glLmZFUEOswTwqtjW2sf2sz7sS49uTlCCEEKdnJlBVWsuvjfUxZoD5zFEU5iagpZFEzZC6pFxcXs3nzZoqLizEMg82bN7N582ZaW1vbHzNhwgReeuklIPJF+J3vfIef//znvPTSS2zfvp3rr78el8vF1VdfHauXMfjIpsNrXhxdbxeOyHazcUDDUo7v2YOr+bB6Fy7dTq4rhby4VHJdKQC8UPIxK6p2xDjCoUFKyb8PraEp6GWEKwWXxY4uNFwWOyOcybSG/fz70Bo1nSxKGqoa8bX5ccZ3/Zljd9owwiZ15Q0DHJmiKIoyVAyZRfw/+tGP+Pvf/97+85FRlffff58zzzwTgD179tDU1NT+mLvuugufz8fNN9/c3sjynXfeGTI9YCJVwXYjAx9A+CAIF8J+KtgWIDR3dA4iEiIL9qU/Mm2sUxD+yHbNE53jKVFR629mVfVu3BYnbuunJ4JCCJLtbsp9DbxVsYWF6ROxaGoazrEcbKthf0sVyfb4TiNWQghS7PEcaquhsKWScQnZMYry5GF32dEtOuFgGFydp+seaX7pcKmqW4qinGTUCEzUDJkE5oknnjhuDxgpO/4rCiG49957uffee/svsH4SWZvyLPieB9kGwg4yjAx+BJb/QMI9CD0KJ1OWsWAZA6HtkTUvR5/ASQlmLVjHg2X8iR9LiZpdzeW0hP3kOLte65JodVHmrafM13C4w73SnZaQj6AZJlnv+qKAXbMSMg0aQ94BjuzklDYihdHT89m+ajdxHlenpLGpphlPWgIT542LUYSKoijKYDdkppANO8GV4PsnCB30AtCzwZIX+W94D7Lld0hpnPBhhBAI17LICItRDKYXpBn5r1ECmhvhWqYW8A8yhjQB2e3iPV1oSCRGFN4jJ7t4qxOrpndYR3S0gBnCqul4rK4BjuzkJIRg8VfOxpXgovJgDaFgGADTMKmvbCTgC3L2VQtUTxhFUU4+UvbPbRhSZ6WDkJQS6X8DZBi0lI6jIsIKeiaE90TKHkeBsM1ExN8N1kkgm8EojayNsY5HxH8fYZsdleMo0ZPrSsah2fAagS63t4R9eKwuMhyJAxvYEFQQl8bo+Azqgy2dRnGllNQFWsiPS2VMfGaMIjz5TJ4/nut/ehWpOcnUlNRRXlhJRVE1FqvOxTcv5oIbzz3uPtqavVQcqKKxpum4j40Wb4uP+soGgoGuk11FURRlYAyZKWTDimyJVP7qbt2JcIKsjiQxtplROaSwnQLWGZFqY2ZT5NiWcWrkZZAa5c5ggiebTfUHsWvWDutc/EYIbzjI0uyZxFmGT0nwvhJCcGXePH6/+3VKfXWk2OJx6FYCRpi6YAtxFjufz5uHPsj+Fmr8zWxqKKItHCDZ5mZW8qgO66EGSsAIUelrBCHIdiZi1Xr2tTL7/OlMOX0C2z7cSUNVE063gykLJ5KUfuz1dnUVDbz1t/dY/9Zm/G0BLFadifPGseQrZzNqWv+Uuz64o4R3n/mQrR/sJBwycCe6mHfJHM65ZiHxSVFaj6goyvAwPAdMok4lMINSbN7dQmiqVPIQIYTgK6POoiHwHw621WDTLNh1C75wEBPJKckjuWSEGjnrqSmJuXxnwgX8+9AailqrqQ+2YtUsjInP5Mq805iZPDLWIbYLmwYvFH/M2xVbaAn726cRJtvcfLFgPmdlTB6QOEJmmDfLN/Nu5TbqApFqkOmOBM7NnMb5WdN6VDzC4bIzZ0nPL8LUltfzwM2PUbyrDHeiiziPi1AgxLo3N7Fv/QG+/psvM/HUsX1+TV3ZvW4ff77zKRqrGolPcmN32Wiua+WVB99k55o93PL/vqamuymKogwwlcAMRiIB9JGRhfVdjcJIHwhLZAG+Mmxlu5L4nymX8WH1LlZV76Y57CMnPplFGZNYmD4Bh66qOPXG1MQ8JntGcKC1mqagl3irkzHxGWiDbOTl1dL1vFiy7v+3d+fxUZX34sc/58w+mSX7HhJ2CDSCgBgUBUUWvQpqlbZqtS7359ZW0Wu19letV3/2Xq3S9lbUWxW3Vmtdq7igAqLgAoIi+xJIyL6vk9nO8/sjEI0J+ySTId/363VeMuecOc93TuJkvvM8z/fBYbKS5UhE1zRCRpgafzNP7lxGnNnGSUnDejWGkBHmf3d8wPLKTVh0Mx6LAxRU+Bp5etcKyn31XDl0esTXIXrr8aUUbyklc2ha5yKXDpcdd+K+BTD/+zX+74sLIrYAZigY4u/3v0pTTRNZwzM6X0+cx0kwEGL72l28u3g5Fy04NyLtCSGOb5rq2CJ9zYFIEph+SNM0sM9BhTaBUQ9a/LfzYFQIwpVgGQOWE6Iap4i+RJuLeTmTmJczCaVUTC9cqZTiq4Y9rKzaTElrLU6zjUlJQzklZSTx1h5KfPcCXdP79VyX5qCPd8u/wmYyk2j7duiSWTeR7ohnb1stb+79kkmJQ3v1d2F9/W5WVm0h3hqHy/ztsDWH2UpT0Meyyo1MTh7O2PiciLXZVNvMl+9/jTs+rluComkaSRkJlG6vYMvnOxgzJTJVEzet3kbZjgqSMxO73U+L1YzT7eDTf63hqqCoBQAAQJhJREFU3/59Bg6XIyJtCiGOZ1JHOVIkgemvbNMgvAd8r4Gxp7OMMhhgHormuhlNkx+f+FYsJy9hZfDMrhW8X7GBgBHCplsIKYONjSV8WPENN406h5y4pGiHGXXfNJRQH2glw5HQ4/EEq4ui1ipKfXVkO3vvfq2q3kZIhbskL/t5LA4ag62srtkW0QSmvrIBf2sAT3LPw7VsThvhUJi6ioaItVlTWkc4bGB19Nyb6XA7aG1so6GqSRIYIYToQ/IJuJ/SNA2cl4P1RFT7cgjv7ljI0noy2E5D0z3RDlGIiPmoajPvln+Ny2zvUjktrAz2tNawaPt73FNw8YBflDNghFBwwIICZk3HUAb+A5SEjpRyXwM23XLA42bNRKWvIaJt2uPsmMw6QX8QWw8JRTgURiOyC2DaHFZQCiNsoJu63/NQMIzJrB8wwRFCiO+SIWSRIwlMP6ZpGlgK0CwF0Q5FiF6jlOKD8g2gVMdciu8waTqpdg9FLVVsbNzLCQm9U2UqVqTavVh1E75QAIe5+4fmtrAfh8lKsq13v+DwWBwEjdABj4eMMJ4Ir5uTOiiZISfksXFVzwtg1lc1Ep/qJT+CC2DmF47AleiisaaZhLSu8xGVUjTVNHHCtDEkpsdHrE0hhBCH1r9mpwohBpzGYBulvjrclp6H4NhNVsLKoKilqo8j639GejIY7EqlJtCE8b01a0JGmKagj8nJw/Fae3fRzZNThqPo6BH6Pn84iK7pTEoaGtE2NU1j9pX7F8CsIrhvLZZwKExtWT1Bf4gZl51GnDdy86US0uI57cKT8TX7aKhuwjA67nkoGKJyTzVOj4MZl50e08M3hRB9SPXSNgBJAiOEiCptXyHgA70HK6VQxHaBgkjRNZ3Lh5xOis3D3rZa6vwttITaqW5votRXx3B3BhfknNTrcZycNJyRnkwqfPU0B30dPyOlaAq2UdneyNj4HCYkDYl4u2OmjOTKe39MSk4y1aV1lO6ooGJ3NTanlQt+cTazfjY94m3OvXE2M6+YBkpRvrOCsp0VVBXXkpAWz+W/mx+xggFCCCEOnwwhEyLK6gMtbGgowR8OkmL3MNabM6DmengsDoa40tjQUNxtCBmALxzAqlsY4c6IQnT9z3B3BrePmce7Zev5vHYngXAQj8XOnMxxzMkaR4K19xdWdJit3DzqHJ7cuYwNDXvY62sFBU6zjdNSR3H5kGlYD3NByyN14owCxp46im8+3tKxAKbbzthTRuFJ6p21WCxWC/Nvm8cZP5nKhpWbaW/1k5gezwnT8mXivhDiCEkVskiRBEaIKNm/IOHSiq9pDPrQ6Jjzke1M4mdDp5HvzY52iH1C0zRmpP+ALU2l1PlbSLDGdfa2BIwQ1f4mxiXkMcqTGeVI+49BcclcM3wGlw4+DV84QJzZhs104En1vSHR5uLW/HPZ01rDrpZKNDSGu9PJciYe8bVqSmtprm/FnRBHctahq6dZ7VZOnNG3cwNTspM448en9mmbQggheiYJjBBR8o89q3lt7xf7FiRMQNd0/OEge1qrWbhlCb/Kn8tQd1q0w+wTJycPp9xXz+t711DSVotZ1wkrhQaM9mZx3fCzZAhZDxxma4+T+ftSblwyuXHJR/Xc3RtLeOvxpWz+dDtBfxCLzUJ+4QjOvmYGeWMiV4JZCCH6BWPfFulrDkCSwAgRBVXtjbxfsQGnydZlQUKbyUKWI5GSthreKV/PDe5ZUYyy72iaxgWDJjM+cTCrqreyt60Op9nKiYlDmJA4BHsf9y6I3rfr6z385ZdPUltWT3yKhziPA78vwOdvr2PnV7u54Y9XMqRgYFedE0IcX6SMcuRIAiNEFHxVv4fmUDtZju7DbTRNw2Nx8mXdLlqC7bgs3RcLPF4NdqUy2JUa7TBEL1NK8cof36KuvIHs4RloekfvmtVhxRUfR+mOcl7541vc8tfrpOdNCCFEN1KFTIgoaAsH0AD9AB/OLLqJkGHQHg70bWBC9IGSrWXsXL+bhHRvZ/Kyn6ZrJKTHs+ur3ezdVhalCIUQQvRn0gMjDkqF9qL8H0BwHagwWMai2c9EMw+LdmgxLdnmRqNjIn9PFcfaQgE8FvsB10Y5UmFlsLWpjFp/Mw6TlTHenKjPnRC9ryHQRo2/CatuJtuZiK71j++s6isbCLQHDrgApCPOTmN1E/WVjeSMzOrb4IQQQvR7ksCIA1KBz1HND4NRB5oN0CC0FeVfCnHXoNkHxvyM3jA+IY9ku4cqfxMZ9vguw2SCRhhfOMDZWeMjUlnqm4YSni9ayZ7WGoIqhI5Oit3DedkTOCu9QIboHIdq/M28WvwZn9buwBcKYNJ18uJSODdrAiclR//LB6fbgdliJuAPYnfauh0PtAcxW8w4PVKmWBzazq92s/qNNexYX4Ru0vnB1NEUnjuR9DwZjir6GaU6tkhfcwCSBEb0SIWrUc1/BKMJTINg/ze3SoFRiWr9XzANQbMMj26gMcpptnFp3lQe2/4+e9tqibfGYdFNtIb8tIbaGeHJZE7m+GNuZ1tTGX/csoTGYBvJNjd2k5WgEaYu0MzincsxlGJ25rhjf0Gi36gPtPDgpn+xvbkcj8VBgjWO0L4euN2t1VwZns70tDFRjXFIQS6ZQ9Mo2VpGxpDulfbqKxsYNDqLwWMHRSG641tVSQ1fvr+BppomXPFxnDB9DFnDYneNpQ+eX8krf3yLtuY27A4bhqEo+rqYj1/+jJ/d+yPGnjo62iEKIXqBJDCiZ/4VYNR0TV4ANA30NAjvRvk/kATmGBSmjCDObOPN0i/Z2lS2bz0PO2emj+W87InEW53H3MYbe9dQH2glx5nU2dNi0U2k2eOpam/kjb1rmJo6mjhz92/BRWx6u3Q925vLyXIkdg5PtAFxZhsVvgZe3L2KSYlDo1ocwmQ2cfa/n8VTd/6dit1VJGUkYLFZCPqD1JbXY3VYOfuaszCZB86Crr1NKcVbj7/Pu4uX0dLQikbH91Fv/e/7TL1wMhfdcl7M3e9ta3fyysI3UQqyhmV0vscpQ1G+u4rFd73I/31xAd5kT5QjFaKDVCGLHElgYpRSflBB0OJ6ZQiQCm0F9K7Jy36aBpoDghsi3u7xIKwMdLTD+rkUJOTyg/hBVPubaA8HSbK5I5ZM1LQ38U3jXuKtPf+OJFpdVLQ38HX9HgpTRkSkTRFd/nCQj6u3EGe29Ti3KtnmpqK9gbV1uzg9LT8KEX5r0qxxGKEwrz/yLlV7qjHCBrpJJy03hfNumM3EmSdENb7jzUcvreb1v7yD1W4hc2g6uq6hlKKptoWlz6wgzuPk3Otia1jwqte/oK3F1yV5gY5CEOm5KZTtqmTNu19x5iVToxilEKI3SAITY1Twa5TvbQh+CRhgygH7LLCdiaZF8sepAQdL6xVSxO5bISPMJ9VbWVa5kb1tdVh1EycnD+eM9LFkOw++srimaaTavRGPqSXUTsgI47T0nBDt/4DbEmqPeNsiOlpC7bSF/NhNPRdo2P8zrwu09GVYBzT5nAmMP/MHbP5sO811LbgTXYyePByrXQpMRFIwEOT95z5C0+hSOEHTNLzJbkKBEMv/sYozfnIqcd646AV6hLat3YUjzt7jFzS6SUfTYNeGPZyJJDCiv1Ac/LPV0V5z4JEEJoao9g9RLX8B1QK6B9AhuLWjtyS4GVw3RiyJ0SxjUf4VHZXHtO99k6sUqHawnBiRtmJdyAjz6PalfFy9BQU4TTZaQkHe2LuWVdXb+MWoOeR7s/s8rnhrHFbdTHs40ONCkAEjhK5pJFpdPTxb9ActoXb2tFSjgEFxyXgOUZXOabJh0c0EwqEe390NpVDQr4YMWu1WTjg9unNyjnclW8qoKq7Bm9LzUCpvioeq4mq2f1nEuOlj+zi6o9fRi3Tg40qBySRftAlxPJL/s2OECtd0TJwnAKZc0BNBjwdzNmheaF8KgY8j16DtNDBlQnhvRxLTGYgBRinoiWj2MyLXXgxbVrmRlVVb8FriyHIkkmCNI9nmIceZRF2ghce3v097ONjnccVb45iUNJTGYBthZXQ5ppSipr2JdHsCP0iQidL9jT8c5MXdq7h17bPc+80r3PvNy9z65bM8V7QSX+jAawM5zFYmJQ2lJdSO0cMnu4ZAK26znRMTBvdm+KKfCfqDGIZxwDkuJrOOEVaEguEej/dXY04Zha+1HdXD73ooGEbTNIafOCQKkQnRM83one1IPfLIIwwePBi73c6ECRNYuXLlAc9dvnw5mqZ127Zs2XIMd+LYSQITKwIrO8oZ6+kdc1C+S3cDBqr9/Yg1p+nxaO5bwZQB4RIIFUOoBMLFoHnRXL9AM+dGrL1YpZTig4pv0DSt27famqaRZvdS7qtnXV1RVOKbmz2JbGcie9tqaQy0ETBCtITa2eurxW628pO8U7Dq0hHbn4SMMI9tf59/Fn9KW9hPss1Nis2LPxzktZIv+J9t7xA0Qgd8/uzMcaTZPZT6amkL+VFKETLC1Pib8IUDzM44gWS7TGoeSFJzU3C6HbQ2tvV4vLWxDYfLTnpeSh9HdmxOmXcS3iQ3lXtqMIxvk5hwKEzF7ioyhqRx4lkFUYxQiP7nxRdf5KabbuLOO+9k3bp1TJ06lTlz5lBcXHzQ523dupXy8vLObfjw6BZxkgQmRqhQacc/DrQQnRYHoV09fhN1tDTLGLT4h9BcN4DtFLBORou7qmOfbUrE2ollrSE/le2NuMw9V3Sy6GYUsLettm8D2yfTmcBt+XM5PTUfA4M6fzPt4QBjvTncNOrsfrEmiOhqQ0Mxq2u2kWhzk2zzYNHNWHQTSTY3KXYPa2p3saZ21wGfPygumZtGn8NITybNIR97fbVUtDfgMNmYn1vIBYMm9+GrEf1BQqqXE88qoLmuhWCga/IbDoVpqGpk1ORhZA2PrXLKg0ZlcdldFxPndVK2s4LyXZWU7qygoqgjebn695cQ5zn2ao5CHE8eeughrrrqKq6++mpGjx7NwoULycnJYdGiRQd9XmpqKunp6Z2byRTdqoXy1WuM0DTbIaZphUDzRLwimaYngOM8NMd5Eb3u8cKk6eiahqF67sNVSqGUwhLFXo4sZyK/GDWHmvYm6gItOM02shyJsoBlP/VZzXZCKtzjPBWHyYpCsbpm20Erxw13Z3BPwcVsbSqnqr0Ru8nCGG9OVEsni+iad+Mc9m4tY8e63VjtFuxxNgK+AO1tfrJHZjL/tnkx+Z4wceYJ5I3J5vO311O0YQ8mi4nRJw1nwswTcMXHTkECMUD04hz+pqamLrttNhs2W9e/I4FAgLVr13L77bd32T9z5kxWrVp10GbGjx9Pe3s7+fn5/OY3v2H69OnHHvsxkAQmVljHQfvroHwdJYy/Sxmg2sAqSUZfc5itjI3PYVXVVrwWZ7cPAG1hPzaThXxvVpQi/Fay3SNDh2JAjb8Z8/cLZ3yHVTdT3d58yOvoms5obxaj+8Hvnog+b7KHXzxyDR+/8hmfvPY5zXUteFO9zD53Iqf98GQS0uKjHeJRS85K4uyrz4x2GEJEVU5OTpfHd911F3fffXeXfTU1NYTDYdLSui4gnJaWRkVFRY/XzcjI4PHHH2fChAn4/X6effZZzjzzTJYvX85pp50W0ddwJCSBiRWW8WD5AQTWgp4KmrNjLowKQLgcTKlo9hnRjnJAmpVxAl/V7aGyvZEUuwfTvmF+bSE/tf4WTkoexnB3bA3N+L6gEaIp6MOmW+Rb/F6WYHMRUgeeTB0wQiTZpHKcOHLuBBdzrjqT2VeeQdAfxGKzxGSvixAxSykOWjrvaK8JlJSU4PF8+yXl93tfvuv7/98rpQ74XjBy5EhGjhzZ+biwsJCSkhIefPBBSWDEoWmaGdz/gWp+GIJfgVGz/wiYctDcP0czSzWpaMj3ZnPVsDN4tugjynx1ne9NVt3MhMQh/J9hM2L2Q0JryM975V+xvHIjDYE2TJpOQUIuczLHMdKTGe3wjkuTk4axsmoLbSE/zu8NI2sPB9HQZOFRcUw0TZO1doQ4zng8ni4JTE+Sk5MxmUzdeluqqqq69coczMknn8xzzz13VHFGiiQwMUTTE8HzOwhthOAGUCEwDwLryWiafCt+LDqKHwSBo/tGcmrqKMbGZ/NZzQ4qfA1YTWYK4nMZ7c3q7JGJNa0hPw9tfpOv6/dgM1lwmm2EjDAfV23h64Y9XD98JhOThkY7zOPOuIQ8JiUOYXXNdlzhIF5rxyTkpqCP5qCPExMHMzExMqVhQ0aYrxuK2dtWi1kzMdqbRV5cSswm3EII0a/1Yg/M4bBarUyYMIGlS5dy/vnnd+5funQpc+fOPezrrFu3joyM6I4skQQmxmia3jGUzPKDaIdyXFBGK/iXdpSgNqpBc6Js09Dss9BM6Ud0rQSri9mZ43on0ChYWv41XzfsIdXuxfadhTC9FiflvnoW71rBGG8ODrN8kxtJZt3E9SNmkWRz83H1Fsp99QC4LQ5mZRbw49xTu/w8jtbO5goe3/EBxa01hJWBQmE3WRmfkMc1w87EfYhFM4UQQsSeBQsWcNlllzFx4kQKCwt5/PHHKS4u5tprrwXgjjvuoLS0lGeeeQaAhQsXkpeXx5gxYwgEAjz33HO8/PLLvPzyy9F8GZLAiIFLGS2o5vsgsA40c8e8IqMe2p5H+VeC50408/Gx4F/ACLGurojNjaUEjRDZcUmcnDycBGvPcylCRpjllRux6pZuH5Y1TSPF7qWqvYEv64s4JWVkj9c4FiEjzLbmchoDbbgtDkZ5MjHr0S3Z2JccZitXDJ3GvJxJ7GyuRKHIc6WSbHNH5PqV7Y0s3LKEivYGUm0dCapSitaQn1XV2wgYIf4j/7yY7T0UQoh+qRerkB2u+fPnU1tbyz333EN5eTljx45lyZIl5OZ2rO1XXl7eZU2YQCDArbfeSmlpKQ6HgzFjxvDWW29x9tlnR/JVHDFJYMSApdpe6iiKYMoE7TtzDVQYwiWolkfA+98xP5ym0tfAn7a+w86WCkKGgQYoDV4rWcOVQ6cxObn7YlTNIR8NgTbiTD1PArToJhRQ1d4Y8XjX1O7kH3tWs7etloARxqKbyHYmctGgwgG3bk28NY4JSZFfSXx5xUbKfQ1kOxPR9yUpmqbhstjRNY2v6/ewsWEvBQkyr04IISJFUx1bpK95pK6//nquv/76Ho8tXry4y+PbbruN22677Sgi612SwIgBSRktEPiwYwFQ7Xsf0jUT6CkQ2gahzWDJj06QERA0Qvx52ztsbSoj7TtDwQxlUNneyGM73ifZ5maou+twOatuwaTrB6yGpZRCobDpxz6U6bu+rCviL9vepS3kJ8nmwaabCRghiltreWTbu6DBSUkDK4npDatrtmE3WTqTl+9ymm3U+Jv5qmG3JDBCCCH6JRkfIAYmowqMJtAPMCRHc4LyQ7ikb+OKsPX1e9jRVNEleYGONULS7fE0BXx8WLmx2/PizDbGJeTSFPTtK3DQVVPQh9Nki+gHXEMZvFz8Ka0hP5mOROymjoIKNpOFTEcCvnCAV4o/I2QcuMSwODSlFG3hwEHXmtGA9lCw74ISQogBQfXSNvBIAiMGKDOgdwwX69H+N4TI9jD0tS1NpYSU0eOkb03TcJptfFlX1GOSMjtzHF6rkzJfPUEjBHR8+G0MtNEUauOUlJFkO5MiFmtRSxV7WmtItLq6DdvTNI0km5uStlp2NPe82JY4PJqmke1MwhcO9HjcUAoFpDm8fRuYEEIIcZgkgREDkykbzLkdk/Z7ohpA98R8tbewYRz0uEnTCBlhVA/f4Ax3Z3DjiFmkO7xU+ZvY21bL3rZawirMzIwCfjrk9IjG2hxqJ2iED1hhy6pbCBphWkLtEW13IJqWlg9ax2Kr31frb8ZjcXByD3OjhBBCHIP9ZZQjvQ1AMgdGDEiapoN9Lir0MISrQE8GTd/3ZtDUMbzMcQGaKSXaoR6T7LgkNE0jrIweK0q1hvycmDikx7kQAOMTBzPam826uiIq2xux7VvfJsuZGPFY4y1OrCYz7eEAcebu6xq1hwNYdTPx1riItz3QFCYPZ11dEZ9Ub6Up6MNlsWMog6agD5vJwo/yppBqlx4YIYQQ/ZMkMGLgsk1DU/Wothcg/G3JQDQH2GejxV0RtdAiZXLSMF4p/oyK9gYy7QldhmY1Btow6yampx28SIHdZOmTld9z41IY7k7n64ZinCZbl1iVUtT6mxntzWao69vVgg1lsLWpnHJfPRbdzBhvNom2nktDi29ZdDPXj5jJcHcGH1Z+Q3V7E7qmMS4hj5kZBf1qgdJQMMTGT7ay+bPtBP1B0genMnHWOBJSJcESQsSYflBG+XghCYwYsDRNA8cFYJ0CgVUQrgE9DiwngXlYzJdPho7FD/99+Awe2fYeJW21OExWdE3Dt28S99lZ4/tNVS9N05ifO4W9rbWUtNWSaHVhM1nwG0Hq/C3EW538KG9K58+lqKWKJ3cuY1dLJcF9E/vdFgfTUvP5Ud4ULLq8vR2MRTdzdtZ4ZmYU0BBoxayb8Fqc/er3vr6ygf+97Tm2f7mLUDAEGmhoLPnrB/zoV/OYfPaJ0Q5RCCFEFMhfeDHgaab0jkTmODUuIY/fjL2A5ZUb+aJ2JyFl8IP4HE5PG8PExCH96gPrSE8mt+afyz+LP2NLUynNIR8W3cS4hDwuHDSZ0d4sAMp99Ty0+U3KfQ2k2DzYTRYUioZAG2+UriVghLhq2BlRfjWxwaybSLZ7oh1GN+FwmL/e8TybPttGanYSNmdHuXMjbFC9t5bn7nmJpIwEho0/PhabFUIc/zRAi/Cclf7zF7xvSQIjxAAwKC6Znw45PeIT73vDCE8md4yZR5mvnsZgG26zg2xnYpdE6/3yDd0XYkQj0ebCFND5qGozZ2UUMCguOVovQxyjLZ/tYPvaXaRkJXYmLwC6SSd1UDKl28tZ8dIqSWCEELFDhpBFjFQhE0L0O5qmkeVMJN+bTc6+QgT7hYwwq2q24TRbeyw+4LE4aAv7+bKuqC9DFhG2bc1OQoEQ9rjuBR00TSPOG8eGlZs7hpYJIYQYUGImgbnvvvuYMmUKTqeT+Pj4w3rOFVdcgaZpXbaTTz65dwMVQvSqgBHCHw5iPcAcF03T0NBoC3cvESz6RnFrDc/sWsEv1zzF9Z//lYc2v8na2l09rjd0IOFQ+KBjI3STjjIURvjgpcKFEKLfkDLKERMzQ8gCgQAXXXQRhYWFPPHEE4f9vNmzZ/PUU091PrZarb0RnhCij9hNFrxWJ5W+RjwWZ7fjhjJQQKJVqpFFw7q6Ih7Z9h71gdbOohGf1mxjbd0uzsk8kR/nnXJY864yh6WjaRqhQAiztfufqtbGVkZOGobFFtuLzQohhDhyMZPA/O53vwNg8eLFR/Q8m81Genp6L0QkhIgGXdOZljaG53Z9RMAIYdXNGMqgMdhGfaCVlmA7dpMFp9l2wPVvRO9oCvr43x0f0BRsI8f53aF/bhoDbbxZ+iXDPRlMOowyzePPGEtKTjJVJTVkDE5D079NeloaWtFNOlMvPLlfFaEQQoiDk0kwkXLc/2Vfvnw5qampjBgxgmuuuYaqqqqDnu/3+2lqauqyCSH6lzPTx5Ifn02Fr56q9ka2NZezo7mCqvYm2o0gBopHt73Ho9uXEjRkjkRf+axmO9X+ZtIdCd0SC6/VSUiFWV658bCu5XA5uPx384lP8VK6o5yasjrqKxsp21lBS0Mb0y6ewklnj++NlyGEEKKfO64TmDlz5vD888/z4Ycf8oc//IEvvviCM844A7//wGPj77//frxeb+eWk5PThxELIQ6Hy2znltHnMjdnEo2BNhoCrSjAabKS50xhpDsTl8XBispNvFW6LtrhDhglbbUopQ7Y6+U02djeXHHYc2FGTx7OLU9cx9nXzMCb5MHqsFBwWj7//t+X8qM7zsdkMkUyfCGE6F1GL20DUFSHkN19992dQ8MO5IsvvmDixIlHdf358+d3/nvs2LFMnDiR3Nxc3nrrLS64oOd1P+644w4WLFjQ+bipqUmSGCGOkC8UYEtTKQEjRKrdS15cSpdv5MPKoMLXQFgZpNq92E1HPo/BY3GQ78nCF/ajo6OhEQiHKGuvx2cEyXYm0qb7WVK2jiGuVLwWJzlxST1WLhORcajhegYK8xHe/8yh6Vx0y3lcdMt5KKVkyJgQQojoJjA33ngjP/rRjw56Tl5eXsTay8jIIDc3l+3btx/wHJvNhs1mO+Bx0Z0yWiC8F9DBnIemSaGEgcpQBkvK1vN26Tpq/M2EMXCYrIz2ZHHp4KnkOJNYXrWJ98q+Yq+vDqUU8dY4pqeN4ZysE48okalqb+SPW9+mLRzAabJh0nWUUoSUQY2/iUA4CMCe1hp+t+GfOM028uJSOC974mHNwRBHbrQni7f1dQTCIaymrn9elFL4wn5OSx111EmIJC9CCCEgyglMcnIyycl9t9BcbW0tJSUlZGRk9FmbxzNltKF8/wD/+2A0AhroaeA4B+z/hqbFTI0IESGvlnzOS8WfYtZMpNq9mDWd1rCfL+t2UdHewLj4XJZWbEAphdcah65pNARaeWHPKopaqvjFqDkHLI/8fR9WfEOtvwWzpnd+869pGhbNhAoravzNmPSOnhmvxYlFN7O1qYz/2foO1ww7k1NTR/XmrRiQxifmMcSVxramMtIdCZ0/S0MZVLY34rY4mJ42NspRCiFElPRG2eMBWkY5ZsZSFBcXs379eoqLiwmHw6xfv57169fT0tLSec6oUaN49dVXAWhpaeHWW29l9erV7N69m+XLl3PuueeSnJzM+eefH62XcdxQKoBqfgDa/g5GK+hJoMeDUYlqeRzV+sQRrfkgYl9NexNvla7DpltItXux6CY0TcNltpPtTGJPSzWvlHyOTbeQ6UwkzmzDYbKSaveSbHPzRe1OVldvO6y2lFJ8XL0Vt9mOWTcTUuEux0MqjIGBUgqHyYLb4iDObCPLkUjACPHCnk/whQK9cRuiqj0c4OOqLTxXtJLniz7m89odfVrEwKKb+cXIOYzwZFLd3kRxWw3FrTWU+urwWJz8n2EzGOpO67N4hBBCHJ9i5ivy3/72tzz99NOdj8eP76g+s2zZMqZNmwbA1q1baWxsBMBkMrFhwwaeeeYZGhoayMjIYPr06bz44ou43e4+j/+4418Jgc/AlAaa49v9JgcYDdD+NthOB4t8yz1QrK0rojnkI8uR1O2YrukYKBqDbQx1df8A6zB1DDtcUbWJ09PyD9lWWBm0hwM4zTbiDSc1/mZ0TUfXtM5hZAAKRZLN3aWHJtnmobK9gfX1uylMGXEsL7lf2d5czqJt77G3rQ61r6ymCZ3BrlRuHDmbLGdin8SR7ojnrh/8kHX1u9nUUEJQhclxJlOYMpwEWZtHCDGQSQ9MxMRMArN48eJDrgHz3W/8HQ4H7777bi9HNXAp/4eA6pq87Kd5wdiD8n+CJgnMgNEc8qGjoR9gnoJSHdXqDRQ91Y6ymyxU+BoOqy2zbiLV7mFXSzXZziSCKkxT0LevoW8Xs3SbHaTZvV2ea9E7Wq8PtB7eC4sBNe1N/HHLEirbm0i3x3e+Rn84yPbmCv64ZQl3FVxEnLlv5vfZTBZOTh7OycnD+6Q9IYQQA0vMDCET/Uy4EjR7z8c0DdDBqOzTkER0xVvjMOjoHemJoQw0DlypKmiEcVt6SIgPYFraGAxlEFIGQ11pDHalEm+Jw2m2oaNj1c0Mc6d3qzq2Pz6X5QC/vzHo4+qtVPgayXIkdCYv0JFIZDgS2N1azRe1O6MYoRBCiM51LCO9DUCSwIijo8cDB5tDYOw7RwwUExOHEG9xUudv6XYsZITRNQ232UH7vupg3z8eMEJMSRl52O2dljqa8QmDqW5vpNbfgkO3kubw4rHY8VgcuM32HgsC1PlbiLfGcUJ87pG9wH5sTe1OrLq5xxLR+xOar+p393FUQgghRO+QBEYcFc02DVQYVA9JjNEKmhXNenKfxyWiJ94axwWDTsLAoMxXT3s4QMgI0xBopdRXxyhPJlNSR1Djb6Ix0IZSCqUUrSE/Zb468uJSOD119GG3ZzdZuWnU2VycW4jH6qAl1I4/HGSUJ4trh59FblwKe321+EKBjnkxRpiq9kZCKsx5WRPwWp29eDf6lt8IHXDoHoCORqAPJ/MLIYTowf45MJHeBqCYmQMj+hnb6R3lk4ObQE8EzQMoUA1gNO2bwH9CtKMUfWx2xjicJhtvlq6lzFdPeF8VsGlp+czPnUKc2c4zu1bwWe0O9vpqAbDpFk5IyOOqoWcQb407ovYcZisX5RZybvYEavzNWPaVb9Y0jTHx2TxT9BFFLVXUBELoaCTb3Pxb9gRmZ4zrhVcfPUNdqexuqerx2P6iBrlxKX0clRBCCNE7JIERR0XT3eC+E9X6GAS+BGMPHevAeMAxF815BZrW01RtcTzTNI3T0/I5JWUkRa1VBMIhUu1eUuyeznOuGzGT830nsbmplLAyGORMZrg7/ZgWKbSbrGQ7u1Y/G+HJ5J6Ci9nWVE6Nvxm7ycIYbw4O8/G30OqpqaP5uHor9YFWEr6TBCrVsR6Ox+LglCMYnieEEKIXSBWyiJEERhw1zZSC5vkNKrQHwkWADuZRaKbUaIcmosysmxjuPvCCsemOeNId8b0eh67pjPJm9Xo70TbGm8152RN5fe8X7G2rJc5s7xieF27HYbLy47xT+qyMshBCiAOQBCZiJIERx0wz54L5+JkQLUSs0TSNiwadTJ4rhWUVG9neXI6m6ZyaOIoz03/A2PicaIcohBBCRIwkMEIIcRzQNI2TkoZxUtIwQkYY6OgJO1L+cJB19bspaa3BpOmM9mYzypN5TEP8hBBCID0wESQJjBBCHGeOJnEB2NJYyuM73qe0rR6FQgFW3cwYbzbXjTiLBKsrsoEKIYQQR0HKKAshhKDcV8+ftr7N3rY6Uuwesp1JZDsScZvtrK3bxZ+3vtPZsyOEEOJoyEqWkSI9MEKIiNjZXMnKqs1sbSpD1zTGJeQxNXV0n0zWF8duWcVGqtqbyHYmda4po2kaTrONNM3L5sZSvm4o5sTEwVGOVAghxEAnCYwQ4pgtLf+a53d/TEuwHZvJglKKrU3lfFDxDdeNmMkJCVLkob/7vHYHdpOlxwUx7SYrQaOJDZLACCHE0TP2bZG+5gAkQ8iEEMdke3M5zxetJGSEyXEmkWb3ku6IJ8eZRH2glUe3L6U+0BLtMMUhtIeDmA+xdlMgHOzVGGr9zays2swHFRvY1LgXQw3Qv8xCCCEOSnpghBDHZHnlJlrDfrIdSV0qVWmaRoYjnlJfHaurt3N21vgoRikOJTcumXX1u0mk+0R9Qyk0IN2R0CttB4wQL+xexYqqTTQFfWiARTcx2JXKz4ZMZ6g7rVfaFdETDoXZuGor33yyhfaWdtJyU5g4axxpuSnRDk2IXtQbc1ZkDowQQhyxzY2l2HVrj2V2dU1HQ2NHc0UUIhNH4vS0fL5qKKYl2I7LYu/cr5Si2t+E1+qkMHl4xNtVSvH0rhW8V/4VLrOdLEcCuqbjCwXY2ljGw1ve5NdjLiDT2TvJk+h7TbXN/O+vnmPL59sJBUJouo4yFO8+tYy5N87hzEumRjtEIXqHlFGOGBlCJoQ4JhrsK7h7kHNkDZF+76SkYUxPy6cp1EZZWx1NwTYaAq3s9dVi1nQuGTyVZLsn4u0Wt9XycdUWPGYnCVYXutbxZ8lhtpLlTKTC18D7FV9HvF0RHUopnr77RTas3Ex8ipfsEZlkDUsna1g6oWCIfz70BuuXfRPtMIUQ/ZwkMEKIY3JCQi7t4SCqh2+BwspAAaM8mX0fmDgiZt3EVUPP4N+HzWCYO71j2JimUZg8gltGn8v0tDG90u66uiLaQn48Fke3Y7qm4zTbWV2zXUo4Hyd2f1PMplVbScyIxx5n69yv6RpJmYkEfEGWvfBxj+8nQsQ8qaIcMTKETAhxTE5PzWdF1WYq2htIt8d39raElUGZr44MewIn98LQIxF5Zt3EGeljmZ42htaQH5Om4zBbe7VNXziApmkH7KWz6ib84SB+I3TUC3SK/mP7l0X42wIkZSb2eNyd6GLXV3torm/Bk+ju4+iEELFCEhghxDHJdaVw9dAzeHLnMkraOoYbGSiUUqQ7Erhx5GzcPXy7LvovTdO6zIPpTYlWFwqFoYzO4WPf1RYKkOGIx2Gy9Ek8oneFgmHQDjysVNM1DKUIh6QCnTgOKaNji/Q1ByBJYIQQx6wwZQRDXKl8Ur2V7c0VmDSdsfE5nJw8gnirM9rhiX7spOSh/LP4U2r8zaTavV2OBcIhgirE6Wn5PSY3IvZkj8jAZDbh9wWwObr37rU0tJIzMhNPUvdqeEIIsZ8kMEKIiEhzxHPBoMnRDkPEmASri4tzC3l61wr2ttUSb43DrOm0hPy0hfyMjc/hjPSx0Q5TREh+4QhyRmZS9E0JmUPS0E3fJqatTW0oQzH1wkJMJhkuKI5DUoUsYiSBEUIIEVVnZRTgsThYUrqOotYqDKVwme3MyijgvOyJuMx9M5xN9D6zxczlv5vPogVPU7azEpvDislior21HU3XKZw7iakXyhchQoiDkwRGCCEGOKUUjcE2QMNrcUSl7PXk5OGclDSMcl8DQSNEst1DnNl26CeKmJObn8OtT17P6te/4It319Pe0s6ICUOYMncSJ84owGSW3hdxHBuYHSYRJwmMEEIMUEopPq7ewvvlGyhuqwFgUFwyM9J/wKkpo/o8kdE0TRasHCCSMxM597pZnHvdrGiHIkTfkSFkESMJjBBCDEBKKV7Y8wlv7F2LoQw8lo5iC1say9jWVE5pWx3zc6fIIqRCCCH6HUlghBBiANrcVMqS0vU4TFbirXGd+90WBw2BVt4qW8e4hDxGebOiGKUQQhxHpAcmYqQupRBCDECfVG/FFw7gtXQvc+21OPGFAnxSvTUKkQkhhBAHJz0wQggxAJW01mLVzT0OEdM0DatupqStNgqRCSHEcUp6YCJGemCEEGIAcpqthFX4gMdDKozT1H2hQSGEECLaJIERQogBaELiEBQQMronMUEjjAImJA3p87iEEOK4pfi2FyZiW7RfVHRIAiOEEANQYfIIBrtSKfPV4QsHOvf7QgHKffUMdaVxcvKIKEYohBBC9EwSGCGEGIBcFjs3jzqHMfE5NAbaKGmroaStlsZQG2Pis7l51NmykKQQQkRSxHtfemFOTYyQSfxCCDFApTviuesHP2RTYyk7WyoBGOpKI9+bha7J91tCCBFRMok/YiSBEUKIAUzXdMbG5zA2PifaoQghhBCHRRIYIYQQQggheplSChXhHpNIXy9WyBgBIYQQQgghRMyQHhghhBBCCCF6m8yBiRjpgRFCCCGEEELEDOmBEUIIIYQQordJD0zESA+MEEIIIYQQImZID4wQQgghhBC9TXpgIkZ6YIQQQgghhBAxQ3pghBBCCCGE6GXKUCgjwuvARPh6sUISGCGEEEIIIXqd2rdF+poDjwwhE0IIIYQQQsQMSWCEEEIIIYTobYbqne0IPfLIIwwePBi73c6ECRNYuXLlQc9fsWIFEyZMwG63M2TIEB599NGjvQMRIwmMEEIIIYQQA8CLL77ITTfdxJ133sm6deuYOnUqc+bMobi4uMfzi4qKOPvss5k6dSrr1q3j17/+Nb/4xS94+eWX+zjyriSBEUIIIYQQotepXtoO30MPPcRVV13F1VdfzejRo1m4cCE5OTksWrSox/MfffRRBg0axMKFCxk9ejRXX301V155JQ8++OARvvbIkkn8h6D21dduamqKciRCCCGEEKIn+z+nqX68Loo/5O+1a37/c6rNZsNms3XZFwgEWLt2LbfffnuX/TNnzmTVqlU9Xn/16tXMnDmzy75Zs2bxxBNPEAwGsVgsx/oSjookMIfQ3NwMQE5OTpQjEUIIIYQQB9Pc3IzX6412GF1YrVbS09P50/u/75Xru1yubp9T77rrLu6+++4u+2pqagiHw6SlpXXZn5aWRkVFRY/Xrqio6PH8UChETU0NGRkZx/4CjoIkMIeQmZlJSUkJbrcbTdNoamoiJyeHkpISPB5PtMOLKXLvjp7cu6Mn9+7oyb07enLvjp7cu6M3kO+dUorm5mYyMzOjHUo3drudoqIiAoFAr1xfKYWmaV32fb/35bu+f25Pzz/U+T3t70uSwByCrutkZ2d32+/xeAbcm0OkyL07enLvjp7cu6Mn9+7oyb07enLvjt5AvXf9reflu+x2O3a7PaoxJCcnYzKZuvW2VFVVdetl2S89Pb3H881mM0lJSb0W66HIJH4hhBBCCCGOc1arlQkTJrB06dIu+5cuXcqUKVN6fE5hYWG389977z0mTpwYtfkvIAmMEEIIIYQQA8KCBQv461//ypNPPsnmzZu5+eabKS4u5tprrwXgjjvu4Kc//Wnn+ddeey179uxhwYIFbN68mSeffJInnniCW2+9NVovAZAhZEfMZrNx1113HXRsoeiZ3LujJ/fu6Mm9O3py746e3LujJ/fu6Mm9E4cyf/58amtrueeeeygvL2fs2LEsWbKE3NxcAMrLy7usCTN48GCWLFnCzTffzF/+8hcyMzP505/+xIUXXhitlwCApvpzvTkhhBBCCCGE+A4ZQiaEEEIIIYSIGZLACCGEEEIIIWKGJDBCCCGEEEKImCEJjBBCCCGEECJmSAJzDM477zwGDRqE3W4nIyODyy67jLKysmiH1e/t3r2bq666isGDB+NwOBg6dCh33XVXr61Qe7y57777mDJlCk6nk/j4+GiH06898sgjDB48GLvdzoQJE1i5cmW0Q4oJH330Eeeeey6ZmZlomsZrr70W7ZBiwv3338+kSZNwu92kpqYyb948tm7dGu2wYsaiRYsoKCjoXISxsLCQt99+O9phxZz7778fTdO46aaboh2KEL1GEphjMH36dP7xj3+wdetWXn75ZXbu3MkPf/jDaIfV723ZsgXDMHjsscfYuHEjDz/8MI8++ii//vWvox1aTAgEAlx00UVcd9110Q6lX3vxxRe56aabuPPOO1m3bh1Tp05lzpw5XcpDip61trZywgkn8D//8z/RDiWmrFixghtuuIFPP/2UpUuXEgqFmDlzJq2trdEOLSZkZ2fz+9//njVr1rBmzRrOOOMM5s6dy8aNG6MdWsz44osvePzxxykoKIh2KEL0KimjHEFvvPEG8+bNw+/3R3V10lj0wAMPsGjRInbt2hXtUGLG4sWLuemmm2hoaIh2KP3S5MmTOfHEE1m0aFHnvtGjRzNv3jzuv//+KEYWWzRN49VXX2XevHnRDiXmVFdXk5qayooVKzjttNOiHU5MSkxM5IEHHuCqq66Kdij9XktLCyeeeCKPPPII9957L+PGjWPhwoXRDkuIXiE9MBFSV1fH888/z5QpUyR5OQqNjY0kJiZGOwxxnAgEAqxdu5aZM2d22T9z5kxWrVoVpajEQNPY2Agg721HIRwO88ILL9Da2kphYWG0w4kJN9xwA+eccw4zZsyIdihC9DpJYI7Rr371K+Li4khKSqK4uJjXX3892iHFnJ07d/LnP/+Za6+9NtqhiONETU0N4XCYtLS0LvvT0tKoqKiIUlRiIFFKsWDBAk499VTGjh0b7XBixoYNG3C5XNhsNq699lpeffVV8vPzox1Wv/fCCy+wdu1a6V0WA4YkMN9z9913o2naQbc1a9Z0nv8f//EfrFu3jvfeew+TycRPf/pTBuqovCO9dwBlZWXMnj2biy66iKuvvjpKkUff0dw7cWiapnV5rJTqtk+I3nDjjTfy9ddf8/e//z3aocSUkSNHsn79ej799FOuu+46Lr/8cjZt2hTtsPq1kpISfvnLX/L8889jt9ujHY4QfULmwHxPTU0NNTU1Bz0nLy+vxzeJvXv3kpOTw6pVqwZkl/eR3ruysjKmT5/O5MmTWbx4Mbo+cPPpo/m9kzkwBxYIBHA6nbz00kucf/75nft/+ctfsn79elasWBHF6GKLzIE5cj//+c957bXX+Oijjxg8eHC0w4lpM2bMYOjQoTz22GPRDqXfeu211zj//PMxmUyd+8LhMJqmoes6fr+/yzEhjgfmaAfQ3yQnJ5OcnHxUz92fC/r9/kiGFDOO5N6VlpYyffp0JkyYwFNPPTWgkxc4tt870Z3VamXChAksXbq0SwKzdOlS5s6dG8XIxPFMKcXPf/5zXn31VZYvXy7JSwQopQbs39TDdeaZZ7Jhw4Yu+372s58xatQofvWrX0nyIo5LksAcpc8//5zPP/+cU089lYSEBHbt2sVvf/tbhg4dOiB7X45EWVkZ06ZNY9CgQTz44INUV1d3HktPT49iZLGhuLiYuro6iouLCYfDrF+/HoBhw4bhcrmiG1w/smDBAi677DImTpxIYWEhjz/+OMXFxTLX6jC0tLSwY8eOzsdFRUWsX7+exMREBg0aFMXI+rcbbriBv/3tb7z++uu43e7O+VZerxeHwxHl6Pq/X//618yZM4ecnByam5t54YUXWL58Oe+88060Q+vX3G53t3lW++fmyvwrcbySBOYoORwOXnnlFe666y5aW1vJyMhg9uzZvPDCC9hstmiH16+999577Nixgx07dpCdnd3lmIxoPLTf/va3PP30052Px48fD8CyZcuYNm1alKLqf+bPn09tbS333HMP5eXljB07liVLlpCbmxvt0Pq9NWvWMH369M7HCxYsAODyyy9n8eLFUYqq/9tfsvv7/x8+9dRTXHHFFX0fUIyprKzksssuo7y8HK/XS0FBAe+88w5nnXVWtEMTQvQzMgdGCCGEEEIIETMG9sQDIYQQQgghREyRBEYIIYQQQggRMySBEUIIIYQQQsQMSWCEEEIIIYQQMUMSGCGEEEIIIUTMkARGCCGEEEIIETMkgRFCCCGEEELEDElghBBCCCGEEDFDEhghhBBCCCFEzJAERggxoF1xxRVomoamaVgsFoYMGcKtt95Ka2trl/Nefvllpk2bhtfrxeVyUVBQwD333ENdXV2X83w+HwkJCSQmJuLz+Q4rhqamJu68805GjRqF3W4nPT2dGTNm8Morr6CUithrjXV3330348aNO+R5Gzdu5MILLyQvLw9N01i4cGGvxyaEEKLvSAIjhBjwZs+eTXl5Obt27eLee+/lkUce4dZbb+08fueddzJ//nwmTZrE22+/zTfffMMf/vAHvvrqK5599tku13r55ZcZO3Ys+fn5vPLKK4dsu6GhgSlTpvDMM89wxx138OWXX/LRRx8xf/58brvtNhobGyP+eo93bW1tDBkyhN///vekp6dHOxwhhBCRpoQQYgC7/PLL1dy5c7vsu/rqq1V6erpSSqnPPvtMAWrhwoU9Pr++vr7L42nTpqlHH31ULVq0SE2fPv2Q7V933XUqLi5OlZaWdjvW3NysgsGgUkqpuro6ddlll6n4+HjlcDjU7Nmz1bZt2zrPfeqpp5TX61X/+te/1IgRI5TD4VAXXnihamlpUYsXL1a5ubkqPj5e3XjjjSoUCnU+Lzc3V91zzz3qxz/+sYqLi1MZGRnqT3/6U5c49uzZo8477zwVFxen3G63uuiii1RFRUXn8bvuukudcMIJ6plnnlG5ubnK4/Go+fPnq6amps5zDMNQ//Vf/6UGDx6s7Ha7KigoUC+99FLn8WXLlilAvf/++2rChAnK4XCowsJCtWXLls7XB3TZnnrqqUPe39zcXPXwww8f8jwhhBCxQ3pghBDiexwOB8FgEIDnn38el8vF9ddf3+O58fHxnf/euXMnq1ev5uKLL+biiy9m1apV7Nq164DtGIbBCy+8wCWXXEJmZma34y6XC7PZDHQMdVuzZg1vvPEGq1evRinF2Wef3RkndPQ8/OlPf+KFF17gnXfeYfny5VxwwQUsWbKEJUuW8Oyzz/L444/zz3/+s0s7DzzwAAUFBXz55Zfccccd3HzzzSxduhQApRTz5s2jrq6OFStWsHTpUnbu3Mn8+fO7XGPnzp289tprvPnmm7z55pusWLGC3//+953Hf/Ob3/DUU0+xaNEiNm7cyM0338yll17KihUrulznzjvv5A9/+ANr1qzBbDZz5ZVXAjB//nxuueUWxowZQ3l5OeXl5d1iEEIIMTCYox2AEEL0J59//jl/+9vfOPPMMwHYvn07Q4YMwWKxHPK5Tz75JHPmzCEhIQHoGJr25JNPcu+99/Z4fk1NDfX19YwaNeqg192+fTtvvPEGn3zyCVOmTAE6EqucnBxee+01LrroIgCCwSCLFi1i6NChAPzwhz/k2WefpbKyEpfLRX5+PtOnT2fZsmVdPvyfcsop3H777QCMGDGCTz75hIcffpizzjqL999/n6+//pqioiJycnIAePbZZxkzZgxffPEFkyZNAjqSscWLF+N2uwG47LLL+OCDD7jvvvtobW3loYce4sMPP6SwsBCAIUOG8PHHH/PYY49x+umnd8Zy3333dT6+/fbbOeecc2hvb8fhcHQmdDIsTAghBjbpgRFCDHhvvvkmLpcLu91OYWEhp512Gn/+85+Bjh4ITdMOeY1wOMzTTz/NpZde2rnv0ksv5emnnyYcDvf4HLVvgv6hrr9582bMZjOTJ0/u3JeUlMTIkSPZvHlz5z6n09mZvACkpaWRl5eHy+Xqsq+qqqrL9fcnFd99vP+6mzdvJicnpzN5AcjPzyc+Pr5L23l5eZ3JC0BGRkZnO5s2baK9vZ2zzjoLl8vVuT3zzDPs3LmzS9sFBQVdrgF0i1cIIcTAJj0wQogBb/r06SxatAiLxUJmZmaX3pYRI0bw8ccfEwwGD9oL8+6771JaWtptWFM4HOa9995jzpw53Z6TkpJCQkJCl0SgJ+oAlci+n1x9P779ldW+v88wjIO2t/+8nto4krb3t7P/v2+99RZZWVldzrPZbF0ef/c6+69/OPEKIYQYOKQHRggx4MXFxTFs2DByc3O7fRD/yU9+QktLC4888kiPz21oaADgiSee4Ec/+hHr16/vsl1yySU88cQTPT5X13Xmz5/P888/T1lZWbfjra2thEIh8vPzCYVCfPbZZ53Hamtr2bZtG6NHjz7KV/2tTz/9tNvj/cPa8vPzKS4upqSkpPP4pk2baGxsPOy28/PzsdlsFBcXM2zYsC7bd3t2DsVqtR6wN0sIIcTAIT0wQghxEJMnT+a2227jlltuobS0lPPPP5/MzEx27NjBo48+yqmnnspPfvIT/vWvf/HGG28wduzYLs+//PLLOeecc6iuriYlJaXb9f/f//t/LF++nMmTJ3PfffcxceJELBYLK1eu5P777+eLL75g+PDhzJ07l2uuuYbHHnsMt9vN7bffTlZWFnPnzj3m1/jJJ5/w3//938ybN4+lS5fy0ksv8dZbbwEwY8YMCgoKuOSSS1i4cCGhUIjrr7+e008/nYkTJx7W9d1uN7feeis333wzhmFw6qmn0tTUxKpVq3C5XFx++eWHdZ28vDyKiopYv3492dnZuN3ubj04AIFAgE2bNnX+u7S0lPXr1+NyuRg2bNhh3hUhhBD9lfTACCHEIfzXf/0Xf/vb3/jss8+YNWsWY8aMYcGCBRQUFHD55ZfzzDPPEBcX1znx/7umT5+O2+3utl7MfgkJCXz66adceuml3HvvvYwfP56pU6fy97//nQceeACv1wvAU089xYQJE/i3f/s3CgsLUUqxZMmSwyoucCi33HILa9euZfz48fznf/4nf/jDH5g1axbQMYzrtddeIyEhgdNOO40ZM2YwZMgQXnzxxSNq4z//8z/57W9/y/3338/o0aOZNWsW//rXvxg8ePBhX+PCCy9k9uzZTJ8+nZSUFP7+97/3eF5ZWRnjx49n/PjxlJeX8+CDDzJ+/HiuvvrqI4pZCCFE/6SpAw2uFkIIcdzLy8vjpptu4qabbop2KEIIIcRhkR4YIYQQQgghRMyQBEYIIYQQQggRM2QImRBCCCGEECJmSA+MEEIIIYQQImZIAiOEEEIIIYSIGZLACCGEEEIIIWKGJDBCCCGEEEKImCEJjBBCCCGEECJmSAIjhBBCCCGEiBmSwAghhBBCCCFihiQwQgghhBBCiJjx/wFryziYWEw3AwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Apply K-Means Clustering\n",
    "k = 4 \n",
    "kmeans = KMeans(n_clusters=k, random_state=42, n_init=10)\n",
    "customer_data[\"Cluster\"] = kmeans.fit_predict(X_scaled)\n",
    "\n",
    "dbi_score = davies_bouldin_score(X_scaled, customer_data[\"Cluster\"])\n",
    "print(f\"Davies-Bouldin Index: {dbi_score:.4f}\")\n",
    "\n",
    "pca = PCA(n_components=2)\n",
    "reduced_data = pca.fit_transform(X_scaled)\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(reduced_data[:, 0], reduced_data[:, 1], c=customer_data[\"Cluster\"], cmap='viridis', alpha=0.7)\n",
    "plt.xlabel(\"PCA Component 1\")\n",
    "plt.ylabel(\"PCA Component 2\")\n",
    "plt.title(f\"Customer Clusters (DBI: {dbi_score:.4f})\")\n",
    "plt.colorbar(label=\"Cluster\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}