Quantium_Task1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "96655876-fcba-42cd-bb4b-33b8e8fd2f61",
   "metadata": {},
   "source": [
    "## Quantium Task 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1e9a58e9-0cd1-4c08-8fa1-441a0fda4e6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Importng Necessary Libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f912a9e4-5217-45b6-863e-ecd00a1673f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LYLTY_CARD_NBR</th>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000</td>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>OLDER SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   LYLTY_CARD_NBR               LIFESTAGE PREMIUM_CUSTOMER\n",
       "0            1000   YOUNG SINGLES/COUPLES          Premium\n",
       "1            1002   YOUNG SINGLES/COUPLES       Mainstream\n",
       "2            1003          YOUNG FAMILIES           Budget\n",
       "3            1004   OLDER SINGLES/COUPLES       Mainstream\n",
       "4            1005  MIDAGE SINGLES/COUPLES       Mainstream"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#load the dataset\n",
    "customer = pd.read_csv(r\"C:\\Users\\user\\Downloads\\Quantium\\QVI_purchase_behaviour.csv\")\n",
    "customer.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "33885d57-c12e-4840-99e5-bdbebdbb6dd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>STORE_NBR</th>\n",
       "      <th>LYLTY_CARD_NBR</th>\n",
       "      <th>TXN_ID</th>\n",
       "      <th>PROD_NBR</th>\n",
       "      <th>PROD_NAME</th>\n",
       "      <th>PROD_QTY</th>\n",
       "      <th>TOT_SALES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-10-17</td>\n",
       "      <td>1</td>\n",
       "      <td>1000</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Natural Chip        Compny SeaSalt175g</td>\n",
       "      <td>2</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-05-14</td>\n",
       "      <td>1</td>\n",
       "      <td>1307</td>\n",
       "      <td>348</td>\n",
       "      <td>66</td>\n",
       "      <td>CCs Nacho Cheese    175g</td>\n",
       "      <td>3</td>\n",
       "      <td>6.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-05-20</td>\n",
       "      <td>1</td>\n",
       "      <td>1343</td>\n",
       "      <td>383</td>\n",
       "      <td>61</td>\n",
       "      <td>Smiths Crinkle Cut  Chips Chicken 170g</td>\n",
       "      <td>2</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-08-17</td>\n",
       "      <td>2</td>\n",
       "      <td>2373</td>\n",
       "      <td>974</td>\n",
       "      <td>69</td>\n",
       "      <td>Smiths Chip Thinly  S/Cream&amp;Onion 175g</td>\n",
       "      <td>5</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-08-18</td>\n",
       "      <td>2</td>\n",
       "      <td>2426</td>\n",
       "      <td>1038</td>\n",
       "      <td>108</td>\n",
       "      <td>Kettle Tortilla ChpsHny&amp;Jlpno Chili 150g</td>\n",
       "      <td>3</td>\n",
       "      <td>13.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE  STORE_NBR  LYLTY_CARD_NBR  TXN_ID  PROD_NBR  \\\n",
       "0 2018-10-17          1            1000       1         5   \n",
       "1 2019-05-14          1            1307     348        66   \n",
       "2 2019-05-20          1            1343     383        61   \n",
       "3 2018-08-17          2            2373     974        69   \n",
       "4 2018-08-18          2            2426    1038       108   \n",
       "\n",
       "                                  PROD_NAME  PROD_QTY  TOT_SALES  \n",
       "0    Natural Chip        Compny SeaSalt175g         2        6.0  \n",
       "1                  CCs Nacho Cheese    175g         3        6.3  \n",
       "2    Smiths Crinkle Cut  Chips Chicken 170g         2        2.9  \n",
       "3    Smiths Chip Thinly  S/Cream&Onion 175g         5       15.0  \n",
       "4  Kettle Tortilla ChpsHny&Jlpno Chili 150g         3       13.8  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#load the dataset\n",
    "transaction = pd.read_excel(r\"C:\\Users\\user\\Downloads\\Quantium\\QVI_transaction_data.xlsx\")\n",
    "transaction.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38cfcf48-65da-4fa9-a36a-30ad133d44a3",
   "metadata": {},
   "source": [
    "## Checking Data Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6f4a65be-33cf-4ad4-b899-be1f884843af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 264836 entries, 0 to 264835\n",
      "Data columns (total 8 columns):\n",
      " #   Column          Non-Null Count   Dtype         \n",
      "---  ------          --------------   -----         \n",
      " 0   DATE            264836 non-null  datetime64[ns]\n",
      " 1   STORE_NBR       264836 non-null  int64         \n",
      " 2   LYLTY_CARD_NBR  264836 non-null  int64         \n",
      " 3   TXN_ID          264836 non-null  int64         \n",
      " 4   PROD_NBR        264836 non-null  int64         \n",
      " 5   PROD_NAME       264836 non-null  object        \n",
      " 6   PROD_QTY        264836 non-null  int64         \n",
      " 7   TOT_SALES       264836 non-null  float64       \n",
      "dtypes: datetime64[ns](1), float64(1), int64(5), object(1)\n",
      "memory usage: 16.2+ MB\n"
     ]
    }
   ],
   "source": [
    "transaction.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a3d0eb20-8984-437e-b2f7-58eeecb1e76a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 72637 entries, 0 to 72636\n",
      "Data columns (total 3 columns):\n",
      " #   Column            Non-Null Count  Dtype \n",
      "---  ------            --------------  ----- \n",
      " 0   LYLTY_CARD_NBR    72637 non-null  int64 \n",
      " 1   LIFESTAGE         72637 non-null  object\n",
      " 2   PREMIUM_CUSTOMER  72637 non-null  object\n",
      "dtypes: int64(1), object(2)\n",
      "memory usage: 1.7+ MB\n"
     ]
    }
   ],
   "source": [
    "customer.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17f99672-e16c-4dcf-847e-5c7cdb7f2ac2",
   "metadata": {},
   "source": [
    "## Summarization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1e7cf2c9-7bc9-4667-8f2a-9e3c7a4b274f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>STORE_NBR</th>\n",
       "      <th>LYLTY_CARD_NBR</th>\n",
       "      <th>TXN_ID</th>\n",
       "      <th>PROD_NBR</th>\n",
       "      <th>PROD_QTY</th>\n",
       "      <th>TOT_SALES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>264836</td>\n",
       "      <td>264836.00000</td>\n",
       "      <td>2.648360e+05</td>\n",
       "      <td>2.648360e+05</td>\n",
       "      <td>264836.000000</td>\n",
       "      <td>264836.000000</td>\n",
       "      <td>264836.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2018-12-30 00:52:12.879215616</td>\n",
       "      <td>135.08011</td>\n",
       "      <td>1.355495e+05</td>\n",
       "      <td>1.351583e+05</td>\n",
       "      <td>56.583157</td>\n",
       "      <td>1.907309</td>\n",
       "      <td>7.304200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2018-07-01 00:00:00</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2018-09-30 00:00:00</td>\n",
       "      <td>70.00000</td>\n",
       "      <td>7.002100e+04</td>\n",
       "      <td>6.760150e+04</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>5.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2018-12-30 00:00:00</td>\n",
       "      <td>130.00000</td>\n",
       "      <td>1.303575e+05</td>\n",
       "      <td>1.351375e+05</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>7.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2019-03-31 00:00:00</td>\n",
       "      <td>203.00000</td>\n",
       "      <td>2.030942e+05</td>\n",
       "      <td>2.027012e+05</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2019-06-30 00:00:00</td>\n",
       "      <td>272.00000</td>\n",
       "      <td>2.373711e+06</td>\n",
       "      <td>2.415841e+06</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>650.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>76.78418</td>\n",
       "      <td>8.057998e+04</td>\n",
       "      <td>7.813303e+04</td>\n",
       "      <td>32.826638</td>\n",
       "      <td>0.643654</td>\n",
       "      <td>3.083226</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                DATE     STORE_NBR  LYLTY_CARD_NBR  \\\n",
       "count                         264836  264836.00000    2.648360e+05   \n",
       "mean   2018-12-30 00:52:12.879215616     135.08011    1.355495e+05   \n",
       "min              2018-07-01 00:00:00       1.00000    1.000000e+03   \n",
       "25%              2018-09-30 00:00:00      70.00000    7.002100e+04   \n",
       "50%              2018-12-30 00:00:00     130.00000    1.303575e+05   \n",
       "75%              2019-03-31 00:00:00     203.00000    2.030942e+05   \n",
       "max              2019-06-30 00:00:00     272.00000    2.373711e+06   \n",
       "std                              NaN      76.78418    8.057998e+04   \n",
       "\n",
       "             TXN_ID       PROD_NBR       PROD_QTY      TOT_SALES  \n",
       "count  2.648360e+05  264836.000000  264836.000000  264836.000000  \n",
       "mean   1.351583e+05      56.583157       1.907309       7.304200  \n",
       "min    1.000000e+00       1.000000       1.000000       1.500000  \n",
       "25%    6.760150e+04      28.000000       2.000000       5.400000  \n",
       "50%    1.351375e+05      56.000000       2.000000       7.400000  \n",
       "75%    2.027012e+05      85.000000       2.000000       9.200000  \n",
       "max    2.415841e+06     114.000000     200.000000     650.000000  \n",
       "std    7.813303e+04      32.826638       0.643654       3.083226  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transaction.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "04be26d9-069d-4f7e-97de-83157ec13d7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DATE              0\n",
       "STORE_NBR         0\n",
       "LYLTY_CARD_NBR    0\n",
       "TXN_ID            0\n",
       "PROD_NBR          0\n",
       "PROD_NAME         0\n",
       "PROD_QTY          0\n",
       "TOT_SALES         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking null values\n",
    "transaction.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16ba0e72-26eb-4fb2-87a0-bd66f6d6fc75",
   "metadata": {},
   "source": [
    "## Finding and Treating Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8049efa1-41d7-4f78-ab7f-1bd4e2a24b9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ss89sxw4fPqzY2Fh17txZUVFRSk5OtjvXYrFoyZIlioyMVFhYmOLi4nTixImavgUAAFBHOD38fPTRR3r11Vc1dOhQffLJJ+rTp4+ef/55ffPNN8rNzdWoUaPUqlUrpaamKj4+XosXL1Zqaqrt/GXLliklJUWzZs3SunXrZDKZNGbMGBUXFzvxrgAAQG1lslqtVmd9udVqVa9evfTwww9r8uTJtvannnpK9913nyTpww8/1I4dO+Tm5iZJWrBggT7//HNt2bJFxcXFioiI0Isvvqhhw4ZJkvLy8hQZGak5c+aob9++laqrtNSiCxeu3ObdAQCAmuLv31Curo6N6Th15Of48eM6deqU+vXrZ9eenJyssWPHav/+/QoPD7cFH0mKiIhQZmamcnJylJGRoStXrigiIsJ23NfXV6Ghodq3b1+N3QcAAKg73H69S/X56aefJElXr17VU089pfT0dLVs2VLjxo1TdHS0srKy1K5dO7tzAgMDJUmnT59WVlaWJKl58+Zl+pw5c+a2anNzc/qMIAAAqAZODT/5+fmSpMmTJ+u5557TpEmT9Pe//13PPPOMVq1apcLCQrm7u9ud4+HhIUkqKipSQUGBJJXb59KlS5Wuy8XFJD+/hpU+HwAA1F5ODT8NGjSQdH2Nz4ABAyRJHTp0UHp6ulatWiVPT88yC5eLiookSd7e3vL09JQkFRcX236+0cfLy6vSdVksVuXlXa30+QAAoGb5+no5vObHqeEnODhYkspMbbVt21ZffvmlWrRooezsbLtjNz4HBQWppKTE1hYSEmLXx2w231ZtJSWW2zofAADUTk5d2BIaGqqGDRvq4MGDdu1HjhxRSEiIwsPDdeDAAZWWltqO7dmzR61bt1ZAQIDMZrN8fHy0d+9e2/G8vDylp6era9euNXYfAACg7nDqyI+np6dGjx6tt956S0FBQerUqZM+/fRT7d69W++//77atm2r9957T1OmTNHo0aN16NAhrV69WjNnzpR0fa1PbGysEhMT5e/vrxYtWmjevHkKDg5WTEyMM28NAADUUk7d5+eGVatW6YMPPtDZs2fVpk0bxcfH66GHHpIkHTp0SLNnz1Z6erqaNWumuLg4xcbG2s4tLS3VggULlJaWpsLCQoWHh2v69Olq2bJlpethnx8AAOqWiuzzUyvCT21D+AEAoG6pM5scAgAA1DTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBTCDwAAMBSnh59Tp06pffv2Zf5s2LBBknT48GHFxsaqc+fOioqKUnJyst35FotFS5YsUWRkpMLCwhQXF6cTJ04441YAAEAd4ObsAn744Qd5eHho27ZtMplMtvZGjRopNzdXo0aN0kMPPaSZM2fq22+/1cyZM9WkSRMNGjRIkrRs2TKlpKRo7ty5CgoK0rx58zRmzBh98skncnd3d9ZtAQCAWsrp4efIkSNq3bq1AgMDyxxbvXq13N3dlZCQIDc3N7Vp00YnTpzQihUrNGjQIBUXF2vlypV68cUX1bNnT0nSwoULFRkZqa1bt6pv3741fTsAAKCWc/q01w8//KC2bduWe2z//v0KDw+Xm9v/ZbSIiAhlZmYqJydHGRkZunLliiIiImzHfX19FRoaqn379lV77QAAoO5xevg5cuSIcnJy9Pjjj+v+++/XsGHD9D//8z+SpKysLAUHB9v1vzFCdPr0aWVlZUmSmjdvXqbPmTNnaqB6AABQ1zh12qu4uFg//fSTvLy89NJLL8nb21sff/yxxowZo1WrVqmwsLDMuh0PDw9JUlFRkQoKCiSp3D6XLl26rdrc3JyeCwEAQDVwavhxd3fXvn375ObmZgswHTt21LFjx5ScnCxPT08VFxfbnVNUVCRJ8vb2lqenp6TrIerGzzf6eHl5VbouFxeT/PwaVvp8AABQezl9wbO3t3eZtnbt2mnXrl0KDg5Wdna23bEbn4OCglRSUmJrCwkJsetjNpsrXZPFYlVe3tVKnw8AAGqWr6+XXF0dm7VxavjJyMjQsGHDtGLFCnXt2tXW/t1336lt27bq0KGDUlJSVFpaKldXV0nSnj171Lp1awUEBKhRo0by8fHR3r17beEnLy9P6enpio2Nva3aSkost3U+AAConZy6sKVdu3a6++67NXPmTO3fv1/Hjh3T3Llz9e233+rpp5/WoEGDlJ+frylTpujo0aNKS0vT6tWrNXbsWEnXp81iY2OVmJio7du3KyMjQxMnTlRwcLBiYmKceWsAAKCWMlmtVqszC7hw4YISExP1j3/8Q3l5eQoNDdWkSZNsI0GHDh3S7NmzlZ6ermbNmikuLs5uVKe0tFQLFixQWlqaCgsLFR4erunTp6tly5aVrqm01KILF67c9r0BAICa4e/f0OFpL6eHn9qI8AMAQN1SkfDD89wAAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQCD8AAMBQqiT8HD16VFu2bNGxY8eq4nIAAADVpkLhZ9u2berXr5/WrFlja3vzzTfVr18/TZgwQY8++qhee+21Ki8SAACgqjgcfvbu3av4+Hi5u7urbdu2kqTdu3dr1apV6tq1qzZv3qz58+dr8+bNSk1NrVQxmZmZ6tKli9LS0mxthw8fVmxsrDp37qyoqCglJyfbnWOxWLRkyRJFRkYqLCxMcXFxOnHiRKW+HwAA1H8Oh59Vq1apR48e2rBhg7p37y5JSklJkclk0pw5c2Q2m9WnTx+NGDFC69evr3Ah165d06RJk3T16lVbW25urkaNGqVWrVopNTVV8fHxWrx4sV24WrZsmVJSUjRr1iytW7dOJpNJY8aMUXFxcYVrAAAA9Z/D4efgwYMaMmSIXFyun2KxWLRnzx61bdtWv/nNb2z97rvvPv34448VLmTp0qVq2LChXdv69evl7u6uhIQEtWnTRoMGDdLIkSO1YsUKSVJxcbFWrlyp+Ph49ezZU2azWQsXLtTZs2e1devWCtcAAADqP4fDz+XLl+Xv72/7/MMPPyg/P1/dunWzv6CLiywWS4WK2Ldvn9atW6c333zTrn3//v0KDw+Xm5ubrS0iIkKZmZnKyclRRkaGrly5ooiICNtxX19fhYaGat++fRWqAQAAGIPD4adp06Y6ffq07fOePXtkMpnsgod0fY1Os2bNHC4gLy9PL730kqZOnarmzZvbHcvKylJwcLBdW2BgoCTp9OnTysrKkqQy5wUGBurMmTMO1wAAAIzD7de7XPfAAw9o9erV6tWrlywWi9atWycfHx9FRkba+ly8eFH//d//rfvvv9/hAhISEtS5c2f169evzLHCwkK5u7vbtXl4eEiSioqKVFBQIEnl9rl06ZLDNZTHzY0tkAAAqI8cDj/PPvus/vjHP+qBBx6QyWRSQUGBZsyYYQsjSUlJSk1NVV5ensaOHevQNTdv3qz9+/frr3/9a7nHPT09yyxcLioqkiR5e3vL09NT0vW1Pzd+vtHHy8vL0Vsrw8XFJD+/hr/eEQAA1DkOh5877rhDmzdv1rp165STk6OoqCg9+OCDtuNpaWkKDg5WUlKS3QLoW0lNTbVd6+dmzJih5ORk3XHHHcrOzrY7duNzUFCQSkpKbG0hISF2fcxms6O3VobFYlVe3tVf7wgAAGoFX18vubo6NmvjcPiRrq/7efbZZ8s9tm3bNtuTYI5KTExUYWGhXVvv3r01fvx49enTR59++qlSUlJUWloqV1dXSdfXGrVu3VoBAQFq1KiRfHx8tHfvXlv4ycvLU3p6umJjYytUyy+VlFRs0TYAAKgbKhR+buVG8CkoKNDx48d1zz33/Oo5QUFB5bYHBASoRYsWGjRokN577z1NmTJFo0eP1qFDh7R69WrNnDlT0vW1PrGxsUpMTJS/v79atGihefPmKTg4WDExMVV1awAAoB5xeKime/fuSk9Pt2tbvny5zp8/b9d25MgRDR48uEqKCwgI0HvvvafMzEwNGDBASUlJeumllzRgwABbn/Hjx2vw4MGaOnWqhg0bJldXVyUnJ5dZBA0AACBJJqvVanWko9ls1vr169WpUydJUmlpqTp27KiNGzfajfIcPHhQjz32mA4fPlw9FdeA0lKLLly44uwyAACAg/z9Gzq85ue2nud2MDcBAADUGmxmAwAADIXwAwAADIXwAwAADOW2w4/JZKqKOgAAAGpEhZ72atasmd0j5KdOnVJgYKAaNGhgaysuLtb58+d52gsAANSYijzt5fAmhz/fWwcAAKCucnjkx0gY+QEAoG6psX1+ynPs2DFt3ry5qi8LAABQJao8/OzatUuvvPJKVV8WAACgSvCoOwAAMBTCDwAAMBTCDwAAMBTCDwAAMBSH9/lJSkpyqN+3335b2VoAAACqXZWHHwAAgNqMTQ7LwSaHAADULU7d5DAzM1NvvvlmVV8WAACgSlTJyE9JSYm2bt2qlJQUff3115LEi00BAECNqZYXm5bn1KlTWr9+vVJTU5WTkyNfX1899thjvAQVAADUWhUOP1arVV988YVSUlK0e/duWa1WWa1WTZo0ScOHD5e7u3t11AkAAFAlHA4/2dnZ2rBhgzZu3KgzZ87orrvu0sSJExUdHa0+ffqoU6dOBB8AAFDrORx+oqOj5efnp969e6tfv37q3LmzJOny5cvVVRsAAECVc/hprwYNGqi0tFT5+fnKyspScXFxddYFAABQLRwe+dm9e7c+/fRTpaamasKECfL19dWjjz6qmJiY6qwPAACgSlXqUffjx49r48aN+vjjj3X+/HmZTCY99thjGjFihFq1alUNZdYsHnUHAKBuqcij7re1z09paam+/PJLpaWlaefOnSotLVWHDh3Uv39/jRw5srKXdTrCDwAAdUuNhZ+fu3DhgjZt2qS0tDQdP36cTQ4BAECNcUr4+blDhw6pU6dOVX3ZGkP4AQCgbqnWHZ6/++47+fr6KiQkRJKUm5urFStW6NixY2rfvr1GjhxZp4MPAACo3xx+1L24uFjPPvushgwZoi1btkiSioqK9Pjjj2vVqlU6e/asNm7cqCFDhujChQvVVjAAAMDtcDj8rFmzRrt27dIrr7yiwYMHS5I++OADZWZm6r/+67+0efNmbd26VT4+Plq+fHm1FQwAAHA7HA4/n376qeLi4vTkk0/K399fkrRlyxZ5eXlp1KhRkqSGDRtq+PDh2rFjR/VUCwAAcJscDj8//fSTunbtavucn5+v77//Xl26dJGHh4etvVWrVjp79mzVVgkAAFBFHA4/VqtVJpPJ9vmbb76RxWJRt27d7PpdvnxZXl5eVVchAABAFXI4/LRu3Vrfffed7fMXX3whk8mkHj162PXbuXNnvdjlGQAA1E8OP+rev39/JSUlyc/PT1arVWlpaerQoYPuueceW5/PPvtMqampmjhxYrUUCwAAcLscDj/Dhw/XDz/8oOnTp8tqtap58+b685//bDv+yCOP2NYFDR8+vFqKBQAAuF0V3uH5zJkzOn/+vMxmsxo0aGBrf/PNN3XXXXfpD3/4g117XcQOzwAA1C1Of73FDVarVa+++qri4+N1xx13VNfXVDnCDwAAdUtFwo/DC54rw2KxaPPmzcrNzb1pn5ycHL344ouKiIhQly5d9Kc//UlHjx61HT98+LBiY2PVuXNnRUVFKTk5ucx3LFmyRJGRkQoLC1NcXJxOnDhRbfcEAADqtmoNP9L10Z9bGTdunE6ePKkVK1Zo48aN8vT01MiRI1VQUKDc3FyNGjVKrVq1UmpqquLj47V48WKlpqbazl+2bJlSUlI0a9YsrVu3TiaTSWPGjFFxcXF13xoAAKiDKvxi06qUm5urli1baty4cbr77rslSc8884z+8z//Uz/++KP27Nkjd3d3JSQkyM3NTW3atNGJEye0YsUKDRo0SMXFxVq5cqVefPFF9ezZU5K0cOFCRUZGauvWrerbt68zbw8AANRC1T7ycyt+fn5asGCBLficP39eycnJCg4OVtu2bbV//36Fh4fLze3/MlpERIQyMzOVk5OjjIwMXblyRREREbbjvr6+Cg0N1b59+2r8fgAAQO3n1JGfn5s2bZrWr18vd3d3vf322/L29lZWVpbatWtn1y8wMFCSdPr0aWVlZUmSmjdvXqbPmTNnaqZwAABQp9Sa8DNixAgNHTpUf/nLX/Tss89q7dq1KiwslLu7u12/G+8RKyoqUkFBgSSV2+fSpUu3VY+bm1MHxQAAQDWpNeGnbdu2kqTXX39d3377rT744AN5enqWWbhcVFQkSfL29panp6ckqbi42PbzjT63834xFxeT/PwaVvp8AABQezk1/OTk5GjPnj165JFH5OrqKklycXFRmzZtlJ2dreDgYGVnZ9udc+NzUFCQSkpKbG0hISF2fcxmc6Xrslisysu7WunzAQBAzfL19XJ4nx+nhp/s7Gy98MILCggIUPfu3SVJ165dU3p6uqKjo9W0aVOlpKSotLTUFo727Nmj1q1bKyAgQI0aNZKPj4/27t1rCz95eXlKT09XbGzsbdVWUmK5vZsDAAC1ksMLW5588kkdO3asQhd3dXXV9u3byyxavsFsNqtHjx6aOXOm9u/fryNHjmjy5MnKy8vTyJEjNWjQIOXn52vKlCk6evSo0tLStHr1ao0dO1bS9bU+sbGxSkxM1Pbt25WRkaGJEycqODhYMTExFaoVAAAYg8OvtzCbzVq/fr06depUpQVcvnxZ8+fP17Zt23T58mV17dpVL7/8su3x90OHDmn27NlKT09Xs2bNFBcXZzeqU1paqgULFigtLU2FhYUKDw/X9OnT1bJly0rXxOstAACoW6rl3V7VFX5qI8IPAAB1S615txcAAEBtU6GRn9DQUPn4+Pz6RU0mrV69+raLcxZGfgAAqFsqMvJT4ae9HMlKDuYpAACAGleh8JOQkGCINT8AAKD+Ys0PAAAwFMIPAAAwFIfDT3h4uBo25H1XAACgbnP4aa/yXL58WVarVb6+vlVZk9PxtBcAAHVLtT7tdezYMa1YsULbt29Xfn6+pOtvWH/ooYcUFxen9u3bV/SSAAAANaZCIz9/+9vf9Morr8jFxUX333+/QkJC5ObmppMnT2r37t0qKirSnDlz9Oijj1ZnzdWOkR8AAOqWanm9xbFjxzRw4ED17NlTr732mpo0aWJ3PD8/XzNmzND27duVmpqqNm3aVLjw2oLwAwBA3VItr7d4//331bZtWy1cuLBM8JEkHx8fzZs3T2azuU7v7gwAAOo3h8PPnj179Pjjj8vV1fXmF3Nx0WOPPaavvvqqSooDAACoag6Hn+zsbN15552/2q9ly5Y6d+7cbRUFAABQXRwOP76+vsrOzv7VfufOnZO/v/9tFQUAAFBdHA4/9957r9LS0n6136ZNm3TvvffeVlEAAADVxeHwM2LECO3evVtJSUk37bNw4ULt3r1bI0aMqJLiAAAAqlqF9vl59913tWDBAt111136j//4D7Vs2VJubm46deqUtm7dquPHj2vy5MkaOXJkNZZc/XjUHQCAuqVa9vm54YsvvlBSUpK+//57u/bOnTvrueeeU48ePSpyuVqJ8AMAQN1SLeGnV69eeuutt2Q2myVJubm5OnXqlKxWq1q0aFGvFjkTfgAAqFuq5d1ep06dUnFxse2zn5+f/Pz8Kl4dAACAEzm84BkAAKA+IPwAAABDcXjNj9lsVrNmzeTu7v7rFzWZtG3bttsuzllY8wMAQN1SLWt+JCk0NLReLWwGAADGU6Hw8+yzz6pTp07VVQsAAEC1Y80PAAAwFMIPAAAwFIfDz4ABA9jXBwAA1HkVfr2FEfC0FwAAdUtFnvZi2gsAABgK4QcAABgK4QcAABgK4QcAABgK4QcAABgK4QcAABgK4QcAABgK4QcAABgK4QcAABgK4QcAABiK08PPxYsXNX36dD344IO69957NWzYMO3fv992/PDhw4qNjVXnzp0VFRWl5ORku/MtFouWLFmiyMhIhYWFKS4uTidOnKjp2wAAAHWE08PP888/r4MHD2rBggXauHGj7rnnHj311FM6duyYcnNzNWrUKLVq1UqpqamKj4/X4sWLlZqaajt/2bJlSklJ0axZs7Ru3TqZTCaNGTNGxcXFTrwrAABQWzn1xaYnTpxQ79699Ze//EX33nuvJMlqterhhx9W37595enpqQ8//FA7duyQm5ubJGnBggX6/PPPtWXLFhUXFysiIkIvvviihg0bJknKy8tTZGSk5syZo759+1aqLl5sCgBA3VJnXmzq5+end999Vx07drS1mUwmWa1WXbp0Sfv371d4eLgt+EhSRESEMjMzlZOTo4yMDF25ckURERG2476+vgoNDdW+fftq9F4AAEDd4PbrXaqPr6+vevbsadf22Wef6V//+pd69OihhQsXql27dnbHAwMDJUmnT59WVlaWJKl58+Zl+pw5c+a2anNzc/qMIAAAqAZODT+/dODAAb366qvq1auXoqOjNXfuXLm7u9v18fDwkCQVFRWpoKBAksrtc+nSpUrX4eJikp9fw0qfDwAAaq9aE362bdumSZMmKSwsTAsWLJAkeXp6llm4XFRUJEny9vaWp6enJKm4uNj2840+Xl5ela7FYrEqL+9qpc8HAAA1y9fXy+E1P7Ui/HzwwQeaPXu2YmJilJiYaBvJCQ4OVnZ2tl3fG5+DgoJUUlJiawsJCbHrYzabb6umkhLLbZ0PAABqJ6cvbFm7dq1ef/11PfHEE1q0aJHdFFZ4eLgOHDig0tJSW9uePXvUunVrBQQEyGw2y8fHR3v37rUdz8vLU3p6urp27Vqj9wEAAOoGp4afzMxMzZkzRzExMRo7dqxycnJ07tw5nTt3TpcvX9agQYOUn5+vKVOm6OjRo0pLS9Pq1as1duxYSdfX+sTGxioxMVHbt29XRkaGJk6cqODgYMXExDjz1gAAQC3l1H1+li9froULF5Z7bMCAAXrjjTd06NAhzZ49W+np6WrWrJni4uIUGxtr61daWqoFCxYoLS1NhYWFCg8P1/Tp09WyZctK18U+PwAA1C0V2efHqeGntiL8AABQt9SZTQ4BAABqGuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYCuEHAAAYSq0KP8uWLdPw4cPt2g4fPqzY2Fh17txZUVFRSk5OtjtusVi0ZMkSRUZGKiwsTHFxcTpx4kRNlg0AAOqQWhN+3n//fS1ZssSuLTc3V6NGjVKrVq2Umpqq+Ph4LV68WKmpqbY+y5YtU0pKimbNmqV169bJZDJpzJgxKi4urulbAAAAdYCbsws4e/aspkyZogMHDqh169Z2x9avXy93d3clJCTIzc1Nbdq00YkTJ7RixQoNGjRIxcXFWrlypV588UX17NlTkrRw4UJFRkZq69at6tu3rzNuCQAA1GJOH/n5/vvv1bhxY3388ccKCwuzO7Z//36Fh4fLze3/MlpERIQyMzOVk5OjjIwMXblyRREREbbjvr6+Cg0N1b59+2rsHgAAQN3h9JGf6OhoRUdHl3ssKytL7dq1s2sLDAyUJJ0+fVpZWVmSpObNm5fpc+bMmduqy83N6bkQAABUA6eHn1spLCyUu7u7XZuHh4ckqaioSAUFBZJUbp9Lly5V+ntdXEzy82tY6fMBAEDtVavDj6enZ5mFy0VFRZIkb29veXp6SpKKi4ttP9/o4+XlVenvtVisysu7WunzAQBAzfL19ZKrq2OzNrU6/AQHBys7O9uu7cbnoKAglZSU2NpCQkLs+pjN5tv67pISy22dDwAAaqdavbAlPDxcBw4cUGlpqa1tz549at26tQICAmQ2m+Xj46O9e/fajufl5Sk9PV1du3Z1RskAAKCWq9XhZ9CgQcrPz9eUKVN09OhRpaWlafXq1Ro7dqyk62t9YmNjlZiYqO3btysjI0MTJ05UcHCwYmJinFw9AACojWr1tFdAQIDee+89zZ49WwMGDFCzZs300ksvacCAAbY+48ePV0lJiaZOnarCwkKFh4crOTm5zCJoAAAASTJZrVars4uobUpLLbpw4YqzywAAAA7y92/o8ILnWj3tBQAAUNUIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFAIPwAAwFDcnF0AANSEI0eO6I03EmyfX345Qe3atXNeQQCcxmS1Wq3OLqK2KS216MKFK84uA0AViYt7/KbHVq5cW4OVAKgu/v4N5erq2IQW014A6rVbBR9HjgOofwg/AOqtI0eOVGk/APUD017lYNoLqB8qMqrD9BdQtzHtBQAAcBOEHwAAYCiEHwAAYCiEHwAAYCiEHwAAYCiEHwAAYCi83gKoAdnZZ1VQcNXZZeAWTpzIdHYJhuTl5a3AwCBnlwGDYZ+fcrDPD6rS5ct5mjBhnPhXDSjLxcVFCxcuU6NGvs4uBXVcRfb5IfyUg/CDqsbIj3PMnDnF4b4zZsyuxkpwM4z8oKpUJPzUi2kvi8WipKQkbdiwQXl5efrd736nGTNm6M4773R2aU6Vk3Ne+fmXnV0GANxUQcFVphxrCR+fRgoIaOrsMmpEvRj5SUpK0tq1azV37lwFBQVp3rx5OnnypD755BO5u7tX+Hr1YeQnJ+e8XnnlBZWUXHN2KQCAOsDNrYHmzp1fZwOQoV5vUVxcrJUrVyo+Pl49e/aU2WzWwoULdfbsWW3dutXZ5TlNfv5lgg8AwGElJdcMM1tQ58NPRkaGrly5ooiICFubr6+vQkNDtW/fPidW5lw+Po3k5tbA2WUAAOoIN7cG8vFp5OwyakSdX/OTlZUlSWrevLlde2BgoM6cOeOMkmqFgICmmjt3vmFSfG2Xm3tBhYUFzi7D8M6fP6e0tA0aOHCImjZt5uxyIMnT00t+fv7OLgMy1pqfOh9+Cgqu/4Xyy7U9Hh4eunTpUqWv6+ZW5wfFFBQUqKCgQGeXYXiXL+fptdem8qh7LZKWtsHZJeD/c3Fx0dKly3nUHTWqzocfT09PSdfX/tz4WZKKiork5eVVqWu6uJjk59ewSuoD/Pwa6t1331V+fr6zSwFqHR8fHwUHBzu7DBhMnQ8/N6a7srOzFRISYmvPzs6W2Wyu1DUtFqvy8tiTBVXHw6ORPDyMMZcOVFRubt1+uha1g6+vl3H2+TGbzfLx8dHevXtt4ScvL0/p6emKjY2t9HVLSixVVSIAAKhF6nz4cXd3V2xsrBITE+Xv768WLVpo3rx5Cg4OVkxMjLPLAwAAtUydDz+SNH78eJWUlGjq1KkqLCxUeHi4kpOTK7XBIQAAqN/qxQ7PVa0+7PAMAICRGGqHZwAAgIog/AAAAEMh/AAAAEMh/AAAAEMh/AAAAEMh/AAAAEMh/AAAAEMh/AAAAEMh/AAAAENhh+dyWK1WWSz8WgAAqCtcXEwymUwO9SX8AAAAQ2HaCwAAGArhBwAAGArhBwAAGArhBwAAGArhBwAAGArhBwAAGArhBwAAGArhBwAAGArhBwAAGMr/Ay315UhS/KQJAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ploting a boxplot to detect outliers in sales\n",
    "sns.set(style = 'darkgrid')\n",
    "sns.boxplot(transaction['TOT_SALES'])\n",
    "plt.title('Detecting Outliers')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ba54ba82-cce7-4579-98d4-8c58199c0a59",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "first Quartile: 5.4\n",
      "second Quartile: 9.2\n",
      "inter Quartile Range: 3.799999999999999\n"
     ]
    }
   ],
   "source": [
    "# Use IQR Methodd to treat outliers\n",
    "q1,q3 = np.percentile((transaction['TOT_SALES']),[25,75])\n",
    "iqr = q3-q1\n",
    "print(f\"first Quartile: {q1}\")\n",
    "print(f\"second Quartile: {q3}\")\n",
    "print(f\"inter Quartile Range: {iqr}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a90a53cf-2796-4eca-b528-d740ffa7dd2d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "upper_bound: 14.899999999999999, lower_bound: -0.29999999999999805\n"
     ]
    }
   ],
   "source": [
    "# Calculating upper and lower bound so that any datapoints higher than upper bound and lower than lower bound will be callled as outliers\n",
    "upper_bound = q3 + (iqr * 1.5)\n",
    "lower_bound = q1 - (iqr * 1.5)\n",
    "print(f\"upper_bound: {upper_bound}, lower_bound: {lower_bound}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "64efcbb6-879e-48e8-bdb8-6b7fda39399d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# capping outliers\n",
    "transaction['TOT_SALES'] = transaction['TOT_SALES'].apply(lambda x: np.where(x > upper_bound, upper_bound,x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8944ea4f-556c-4af6-a087-8c3535b39c21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>STORE_NBR</th>\n",
       "      <th>LYLTY_CARD_NBR</th>\n",
       "      <th>TXN_ID</th>\n",
       "      <th>PROD_NBR</th>\n",
       "      <th>PROD_NAME</th>\n",
       "      <th>PROD_QTY</th>\n",
       "      <th>TOT_SALES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-10-17</td>\n",
       "      <td>1</td>\n",
       "      <td>1000</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Natural Chip        Compny SeaSalt175g</td>\n",
       "      <td>2</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-05-14</td>\n",
       "      <td>1</td>\n",
       "      <td>1307</td>\n",
       "      <td>348</td>\n",
       "      <td>66</td>\n",
       "      <td>CCs Nacho Cheese    175g</td>\n",
       "      <td>3</td>\n",
       "      <td>6.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-05-20</td>\n",
       "      <td>1</td>\n",
       "      <td>1343</td>\n",
       "      <td>383</td>\n",
       "      <td>61</td>\n",
       "      <td>Smiths Crinkle Cut  Chips Chicken 170g</td>\n",
       "      <td>2</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-08-17</td>\n",
       "      <td>2</td>\n",
       "      <td>2373</td>\n",
       "      <td>974</td>\n",
       "      <td>69</td>\n",
       "      <td>Smiths Chip Thinly  S/Cream&amp;Onion 175g</td>\n",
       "      <td>5</td>\n",
       "      <td>14.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-08-18</td>\n",
       "      <td>2</td>\n",
       "      <td>2426</td>\n",
       "      <td>1038</td>\n",
       "      <td>108</td>\n",
       "      <td>Kettle Tortilla ChpsHny&amp;Jlpno Chili 150g</td>\n",
       "      <td>3</td>\n",
       "      <td>13.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE  STORE_NBR  LYLTY_CARD_NBR  TXN_ID  PROD_NBR  \\\n",
       "0 2018-10-17          1            1000       1         5   \n",
       "1 2019-05-14          1            1307     348        66   \n",
       "2 2019-05-20          1            1343     383        61   \n",
       "3 2018-08-17          2            2373     974        69   \n",
       "4 2018-08-18          2            2426    1038       108   \n",
       "\n",
       "                                  PROD_NAME  PROD_QTY  TOT_SALES  \n",
       "0    Natural Chip        Compny SeaSalt175g         2        6.0  \n",
       "1                  CCs Nacho Cheese    175g         3        6.3  \n",
       "2    Smiths Crinkle Cut  Chips Chicken 170g         2        2.9  \n",
       "3    Smiths Chip Thinly  S/Cream&Onion 175g         5       14.9  \n",
       "4  Kettle Tortilla ChpsHny&Jlpno Chili 150g         3       13.8  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transaction.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "da20c5a9-be23-4944-ab3b-0c2ab56d1a83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# final outplot\n",
    "sns.set(style = 'darkgrid')\n",
    "sns.boxplot(x= transaction['TOT_SALES'],showmeans= True, linewidth= 2, meanprops= {'marker': 'o', 'markeredgecolor' : 'y'})\n",
    "plt.title('Box plot after capping the outliers')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cac0eaa3-abf5-48b5-a02f-4d4fe0673044",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2., 3., 5., 1., 4.])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transaction['PROD_QTY'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "86694892-c6f9-4a59-9ae1-ee98807fc060",
   "metadata": {},
   "outputs": [],
   "source": [
    "median_qty = transaction['PROD_QTY'].median()\n",
    "transaction['PROD_QTY'] = transaction['PROD_QTY'].apply(lambda x: x if x<=5 else median_qty)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b3bd4102-edc5-4ea5-84db-f85fd7a99b2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>STORE_NBR</th>\n",
       "      <th>LYLTY_CARD_NBR</th>\n",
       "      <th>TXN_ID</th>\n",
       "      <th>PROD_NBR</th>\n",
       "      <th>PROD_NAME</th>\n",
       "      <th>PROD_QTY</th>\n",
       "      <th>TOT_SALES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-10-17</td>\n",
       "      <td>1</td>\n",
       "      <td>1000</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Natural Chip        Compny SeaSalt175g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-05-14</td>\n",
       "      <td>1</td>\n",
       "      <td>1307</td>\n",
       "      <td>348</td>\n",
       "      <td>66</td>\n",
       "      <td>CCs Nacho Cheese    175g</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-05-20</td>\n",
       "      <td>1</td>\n",
       "      <td>1343</td>\n",
       "      <td>383</td>\n",
       "      <td>61</td>\n",
       "      <td>Smiths Crinkle Cut  Chips Chicken 170g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-08-17</td>\n",
       "      <td>2</td>\n",
       "      <td>2373</td>\n",
       "      <td>974</td>\n",
       "      <td>69</td>\n",
       "      <td>Smiths Chip Thinly  S/Cream&amp;Onion 175g</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-08-18</td>\n",
       "      <td>2</td>\n",
       "      <td>2426</td>\n",
       "      <td>1038</td>\n",
       "      <td>108</td>\n",
       "      <td>Kettle Tortilla ChpsHny&amp;Jlpno Chili 150g</td>\n",
       "      <td>3.0</td>\n",
       "      <td>13.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264831</th>\n",
       "      <td>2019-03-09</td>\n",
       "      <td>272</td>\n",
       "      <td>272319</td>\n",
       "      <td>270088</td>\n",
       "      <td>89</td>\n",
       "      <td>Kettle Sweet Chilli And Sour Cream 175g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264832</th>\n",
       "      <td>2018-08-13</td>\n",
       "      <td>272</td>\n",
       "      <td>272358</td>\n",
       "      <td>270154</td>\n",
       "      <td>74</td>\n",
       "      <td>Tostitos Splash Of  Lime 175g</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264833</th>\n",
       "      <td>2018-11-06</td>\n",
       "      <td>272</td>\n",
       "      <td>272379</td>\n",
       "      <td>270187</td>\n",
       "      <td>51</td>\n",
       "      <td>Doritos Mexicana    170g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264834</th>\n",
       "      <td>2018-12-27</td>\n",
       "      <td>272</td>\n",
       "      <td>272379</td>\n",
       "      <td>270188</td>\n",
       "      <td>42</td>\n",
       "      <td>Doritos Corn Chip Mexican Jalapeno 150g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264835</th>\n",
       "      <td>2018-09-22</td>\n",
       "      <td>272</td>\n",
       "      <td>272380</td>\n",
       "      <td>270189</td>\n",
       "      <td>74</td>\n",
       "      <td>Tostitos Splash Of  Lime 175g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>264836 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             DATE  STORE_NBR  LYLTY_CARD_NBR  TXN_ID  PROD_NBR  \\\n",
       "0      2018-10-17          1            1000       1         5   \n",
       "1      2019-05-14          1            1307     348        66   \n",
       "2      2019-05-20          1            1343     383        61   \n",
       "3      2018-08-17          2            2373     974        69   \n",
       "4      2018-08-18          2            2426    1038       108   \n",
       "...           ...        ...             ...     ...       ...   \n",
       "264831 2019-03-09        272          272319  270088        89   \n",
       "264832 2018-08-13        272          272358  270154        74   \n",
       "264833 2018-11-06        272          272379  270187        51   \n",
       "264834 2018-12-27        272          272379  270188        42   \n",
       "264835 2018-09-22        272          272380  270189        74   \n",
       "\n",
       "                                       PROD_NAME  PROD_QTY  TOT_SALES  \n",
       "0         Natural Chip        Compny SeaSalt175g       2.0        6.0  \n",
       "1                       CCs Nacho Cheese    175g       3.0        6.3  \n",
       "2         Smiths Crinkle Cut  Chips Chicken 170g       2.0        2.9  \n",
       "3         Smiths Chip Thinly  S/Cream&Onion 175g       5.0       14.9  \n",
       "4       Kettle Tortilla ChpsHny&Jlpno Chili 150g       3.0       13.8  \n",
       "...                                          ...       ...        ...  \n",
       "264831   Kettle Sweet Chilli And Sour Cream 175g       2.0       10.8  \n",
       "264832             Tostitos Splash Of  Lime 175g       1.0        4.4  \n",
       "264833                  Doritos Mexicana    170g       2.0        8.8  \n",
       "264834   Doritos Corn Chip Mexican Jalapeno 150g       2.0        7.8  \n",
       "264835             Tostitos Splash Of  Lime 175g       2.0        8.8  \n",
       "\n",
       "[264836 rows x 8 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transaction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b87ee58-94ad-4466-a6c8-7abea1330421",
   "metadata": {},
   "source": [
    "* Now, we are able to treat outliers successfully and can see there is no outliers in Sales column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3f9f7537-7c87-4871-809d-c4c1806b0f12",
   "metadata": {},
   "outputs": [],
   "source": [
    "# separate pack size from product name\n",
    "transaction['PACK_SIZE'] = transaction['PROD_NAME'].str.extract('(\\d+)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1c8f12d1-1bd2-4d72-a392-114400fd3a0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['175', '170', '150', '300', '330', '210', '270', '220', '125',\n",
       "       '110', '134', '380', '180', '165', '135', '250', '200', '160',\n",
       "       '190', '90', '70'], dtype=object)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transaction['PACK_SIZE'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e5b6d31-48f3-4593-bba9-89ff0a48190f",
   "metadata": {},
   "source": [
    "## Merging two tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9ddbab87-47d1-4ec5-850d-502265cac245",
   "metadata": {},
   "outputs": [],
   "source": [
    "New_dataset = pd.merge(transaction, customer, on = 'LYLTY_CARD_NBR').sort_values(by = 'TXN_ID', ascending = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e9196925-be27-4f0e-b793-5184f161e455",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>STORE_NBR</th>\n",
       "      <th>LYLTY_CARD_NBR</th>\n",
       "      <th>TXN_ID</th>\n",
       "      <th>PROD_NBR</th>\n",
       "      <th>PROD_NAME</th>\n",
       "      <th>PROD_QTY</th>\n",
       "      <th>TOT_SALES</th>\n",
       "      <th>PACK_SIZE</th>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-10-17</td>\n",
       "      <td>1</td>\n",
       "      <td>1000</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Natural Chip        Compny SeaSalt175g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>175</td>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240665</th>\n",
       "      <td>2018-09-16</td>\n",
       "      <td>1</td>\n",
       "      <td>1002</td>\n",
       "      <td>2</td>\n",
       "      <td>58</td>\n",
       "      <td>Red Rock Deli Chikn&amp;Garlic Aioli 150g</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>150</td>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188932</th>\n",
       "      <td>2019-03-07</td>\n",
       "      <td>1</td>\n",
       "      <td>1003</td>\n",
       "      <td>3</td>\n",
       "      <td>52</td>\n",
       "      <td>Grain Waves Sour    Cream&amp;Chives 210G</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>210</td>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188933</th>\n",
       "      <td>2019-03-08</td>\n",
       "      <td>1</td>\n",
       "      <td>1003</td>\n",
       "      <td>4</td>\n",
       "      <td>106</td>\n",
       "      <td>Natural ChipCo      Hony Soy Chckn175g</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>175</td>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102787</th>\n",
       "      <td>2018-11-02</td>\n",
       "      <td>1</td>\n",
       "      <td>1004</td>\n",
       "      <td>5</td>\n",
       "      <td>96</td>\n",
       "      <td>WW Original Stacked Chips 160g</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>160</td>\n",
       "      <td>OLDER SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             DATE  STORE_NBR  LYLTY_CARD_NBR  TXN_ID  PROD_NBR  \\\n",
       "0      2018-10-17          1            1000       1         5   \n",
       "240665 2018-09-16          1            1002       2        58   \n",
       "188932 2019-03-07          1            1003       3        52   \n",
       "188933 2019-03-08          1            1003       4       106   \n",
       "102787 2018-11-02          1            1004       5        96   \n",
       "\n",
       "                                     PROD_NAME  PROD_QTY  TOT_SALES PACK_SIZE  \\\n",
       "0       Natural Chip        Compny SeaSalt175g       2.0        6.0       175   \n",
       "240665   Red Rock Deli Chikn&Garlic Aioli 150g       1.0        2.7       150   \n",
       "188932   Grain Waves Sour    Cream&Chives 210G       1.0        3.6       210   \n",
       "188933  Natural ChipCo      Hony Soy Chckn175g       1.0        3.0       175   \n",
       "102787          WW Original Stacked Chips 160g       1.0        1.9       160   \n",
       "\n",
       "                    LIFESTAGE PREMIUM_CUSTOMER  \n",
       "0       YOUNG SINGLES/COUPLES          Premium  \n",
       "240665  YOUNG SINGLES/COUPLES       Mainstream  \n",
       "188932         YOUNG FAMILIES           Budget  \n",
       "188933         YOUNG FAMILIES           Budget  \n",
       "102787  OLDER SINGLES/COUPLES       Mainstream  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "New_dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edc27894-ba66-4dae-ba6e-289ab32e44b0",
   "metadata": {},
   "source": [
    "## Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4a5c928-bed9-4886-9c3d-06cf0b5e7cec",
   "metadata": {},
   "source": [
    "* Customer Segmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "246466ab-63d4-474e-99e8-9e0bb5c77ea1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PREMIUM_CUSTOMER\n",
       "Mainstream    101988\n",
       "Budget         93157\n",
       "Premium        69691\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Total customers in each spending pattern group\n",
    "segmentation= New_dataset['PREMIUM_CUSTOMER'].value_counts()\n",
    "segmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "96542401-ad0f-48cf-93cc-39c9daf72668",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create plot\n",
    "plt.pie(segmentation, labels= segmentation.index, shadow= True, explode= [0.1,0.0,0.0], autopct='%1.02f%%')\n",
    "plt.legend(loc= 'best')\n",
    "plt.title('Customer Segmentation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b00ebe41-d11b-448e-885a-d8e0827ea728",
   "metadata": {},
   "source": [
    "*  Average Spend per customers by LIFESTAGE and PREMIUM_CUSTOMER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a918e91d-35b8-4f00-a9cc-142f2f0d17ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "      <th>TOT_SALES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>35473.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>90640.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>58348.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NEW FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>21906.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NEW FAMILIES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>16999.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NEW FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>11480.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>OLDER FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>168048.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>OLDER FAMILIES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>103264.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>OLDER FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>80569.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>OLDER SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>136544.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>OLDER SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>133184.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>OLDER SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>132045.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>RETIREES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>112967.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>RETIREES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>155525.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>RETIREES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>97491.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>139133.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>92661.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>83911.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>61101.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>157448.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>41624.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 LIFESTAGE PREMIUM_CUSTOMER  TOT_SALES\n",
       "0   MIDAGE SINGLES/COUPLES           Budget   35473.10\n",
       "1   MIDAGE SINGLES/COUPLES       Mainstream   90640.10\n",
       "2   MIDAGE SINGLES/COUPLES          Premium   58348.85\n",
       "3             NEW FAMILIES           Budget   21906.95\n",
       "4             NEW FAMILIES       Mainstream   16999.95\n",
       "5             NEW FAMILIES          Premium   11480.30\n",
       "6           OLDER FAMILIES           Budget  168048.35\n",
       "7           OLDER FAMILIES       Mainstream  103264.80\n",
       "8           OLDER FAMILIES          Premium   80569.10\n",
       "9    OLDER SINGLES/COUPLES           Budget  136544.30\n",
       "10   OLDER SINGLES/COUPLES       Mainstream  133184.50\n",
       "11   OLDER SINGLES/COUPLES          Premium  132045.25\n",
       "12                RETIREES           Budget  112967.00\n",
       "13                RETIREES       Mainstream  155525.15\n",
       "14                RETIREES          Premium   97491.00\n",
       "15          YOUNG FAMILIES           Budget  139133.20\n",
       "16          YOUNG FAMILIES       Mainstream   92661.35\n",
       "17          YOUNG FAMILIES          Premium   83911.50\n",
       "18   YOUNG SINGLES/COUPLES           Budget   61101.50\n",
       "19   YOUNG SINGLES/COUPLES       Mainstream  157448.20\n",
       "20   YOUNG SINGLES/COUPLES          Premium   41624.70"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Total_sales = New_dataset.groupby(['LIFESTAGE', 'PREMIUM_CUSTOMER'])['TOT_SALES'].sum().reset_index()\n",
    "Total_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "6101babf-397d-4e5e-b53a-1f4254d7544e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create plot\n",
    "sns.set(style= 'darkgrid')\n",
    "plt.figure(figsize= [8,6])\n",
    "sns.barplot(x= 'LIFESTAGE', y= 'TOT_SALES', hue= 'PREMIUM_CUSTOMER', data= Total_sales, palette= 'winter')\n",
    "plt.title('Average spend per customers by Lifestage and Premium_Customers')\n",
    "plt.ylabel('Avg Spend')\n",
    "plt.xticks(rotation= 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6b43d0b-a82c-4bbf-87f3-27da3d58500d",
   "metadata": {},
   "source": [
    "*  Total number of units bought per customers by LIFESTAGE and PREMIUM_CUSTOMER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c49ac0b2-ccd8-4afd-9855-504613452612",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "      <th>PROD_QTY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>9496.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>22699.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>15526.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NEW FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>5571.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NEW FAMILIES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>4319.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NEW FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>2957.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>OLDER FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>45065.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>OLDER FAMILIES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>27756.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>OLDER FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>21775.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>OLDER SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>35220.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>OLDER SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>34997.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>OLDER SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>33986.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>RETIREES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>28764.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>RETIREES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>40518.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>RETIREES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>24884.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>37111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>25044.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>22406.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>16671.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>38632.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>11331.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 LIFESTAGE PREMIUM_CUSTOMER  PROD_QTY\n",
       "0   MIDAGE SINGLES/COUPLES           Budget    9496.0\n",
       "1   MIDAGE SINGLES/COUPLES       Mainstream   22699.0\n",
       "2   MIDAGE SINGLES/COUPLES          Premium   15526.0\n",
       "3             NEW FAMILIES           Budget    5571.0\n",
       "4             NEW FAMILIES       Mainstream    4319.0\n",
       "5             NEW FAMILIES          Premium    2957.0\n",
       "6           OLDER FAMILIES           Budget   45065.0\n",
       "7           OLDER FAMILIES       Mainstream   27756.0\n",
       "8           OLDER FAMILIES          Premium   21775.0\n",
       "9    OLDER SINGLES/COUPLES           Budget   35220.0\n",
       "10   OLDER SINGLES/COUPLES       Mainstream   34997.0\n",
       "11   OLDER SINGLES/COUPLES          Premium   33986.0\n",
       "12                RETIREES           Budget   28764.0\n",
       "13                RETIREES       Mainstream   40518.0\n",
       "14                RETIREES          Premium   24884.0\n",
       "15          YOUNG FAMILIES           Budget   37111.0\n",
       "16          YOUNG FAMILIES       Mainstream   25044.0\n",
       "17          YOUNG FAMILIES          Premium   22406.0\n",
       "18   YOUNG SINGLES/COUPLES           Budget   16671.0\n",
       "19   YOUNG SINGLES/COUPLES       Mainstream   38632.0\n",
       "20   YOUNG SINGLES/COUPLES          Premium   11331.0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Total_units = New_dataset.groupby(['LIFESTAGE', 'PREMIUM_CUSTOMER'])['PROD_QTY'].sum().reset_index()\n",
    "Total_units"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1b0ba295-5afe-4970-9ff2-05719b0071b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ly5ejWLFi2Lx5MyQSCQDAzc0Nnp6eWL16NVatWoWKFSsCSP7HUalSJQDAu3fvMGDAAIwYMULoq2jRoujYsSPu3r2LwoULq1xD+fLlFeaTP3jwQGnFVYVMJsPQoUOF3TdRUVEYN24c+vbti/79+wMAChYsiE6dOuHRo0cK0yxGjBiBwYMHAwAaNmyIN2/eYM2aNXBzc8Nff/2Fq1evYuXKlcKHRYMGDRAbG4tly5ahdevWwtYdW1tbTJkyJc0tOjKZDEuXLkW9evWwcuVKYXnNmjXh5eWFLVu2YOLEiQpjro7dsElJSfDz8xP+McXExGDy5Ml4+vSp0haw4sWLK01ROnjwIAoUKIBBgwYJ3+AtLS3x8OFDyOVyhXmbP+rYsaNw8GKDBg0QEhKCtWvXonPnzrh69Sr++usvLF26FG3btgWQ/I8uJaj17dtXabd4Wnx9fWFqaorNmzcL/6BLly6d6hbM5s2bY+rUqQCAunXr4s8//xQOqilbtmyGu95TfP36FevXrxemBlWrVg1NmzbFtm3bMHnyZGzfvh0RERHw9/dHkSJFACS/v7y8vODt7Q0fHx+hr2bNmqFz585pPldUVBS2bt2K3r17Y9KkSQCSx+rLly+pfsFIy40bN1CkSBH07NkTYrEYLi4uMDY2Rnh4OIDkebcGBgawtrYWXv+aNWugr6+PHTt2CLtk3d3d0bp1ayxduhQHDhwQ+m/QoAF++eUXAMljefLkSdjY2AhbquvXr49Tp07h7t27aNmyZbbWr19//TXd15Ke9Nb51q1bY9GiRTh69ChGjx4NADh27BgMDQ3RrFkzlcc6M6ZPn66wOx1I3ur2456UdevWpfll6/Lly8L/td9++w0ymQxnz57F+fPnASSv2x4eHujfv3+WppkdOnQIpUuXFt4XnTt3xr59+3Dq1Cl06NABQPKUucjISJQsWVLp8T9+QRCJRMLnDpA8JzitL7tLlixJc4PG8+fPUbFiRXh7ewvrbr169XD9+nXcunULQ4cOFdqm93kjl8uxbt06NG/eHDNmzACQ/HkYHR2NvXv3pjc0qb7G6OhoPHz4EAsXLkSRIkXQqFEjhbapvdbChQtj1KhRwnvze98ffPu9unXrKn3J0NPTQ9OmTXHmzBmMHDkSABAbG4tLly5h7dq1mfqfkVleXl7YvXs3Hj16JHy+BAQEoEmTJlnaqhoeHo74+HiNHvvUqFEj/Prrr1ixYgWWLFkCIHkPRN26ddG9e3e4ubllus/3799nuIehRIkSAJL3iqTkKyB5b0nx4sVx+vRp4fPl9u3biIiIQNOmTXHo0CGlvoKCgtJcf8aMGaMwBSmttiVLlsSsWbPQo0ePjF/gdxi+M+Hbt294+PAhRowYofAP0NzcHI0bN8bly5fTfGzKbvyvX7/izZs3ePPmDa5fvw4ASkexZ+THgGNvb4/Y2NhM9ZGiRo0awu8FCxZU6j9lV01UVJTC41q2bKlwu2nTpli9ejViYmJw/fp1iEQiNGrUSOEfq4eHB44dO4b//vtPCMtlypRJd1fq69ev8enTJ6VdZ8WLF0eNGjU0dmaQ7wMlANjZ2QGAyuPs7OyMlStXok2bNmjZsiUaNmwINzc3pQ+T1Py4dcvT0xPnz5/Hq1evcPPmTUgkEqU2bdu2hbe3N27cuKFy+P7777/RqFEjhS0jNWrUEELv936cR1esWLEsfRgVLlxYYU6+ra0tatSoIfR1/fp1VKxYEXZ2dsJ7RywWo2HDhkpzE1Obw/e9+/fvIzExUekD+McpNRlxdXXFvn370LFjR+EAojZt2qT7BermzZto3LixwlxIPT09tGrVCmvXrkVMTIyw/Pt1MOUAJCcnJ2GZSCSChYUFvn79CgDZWr+y8lpSpLfOm5mZoVmzZjh27JgQvo8cOYIWLVpo7MC/kSNHKh1wmdrr6Nq1a5q7wL/f0mxmZgYfHx+8f/8ely9fxo0bN3Djxg1s27YN+/fvh5+fH2rWrKlyfeHh4bh48SIGDx4s/P8sWbIkSpUqhb179wrhO7WtsEDygZo/fnEpUqQILl68KNyuXLmycMDnj4oVK5ZmbW5ubnBzc0NiYiJev36NN2/e4N9//8WXL1+Uds+n93nz6tUrhIWFCVMtU7Rs2VKl8J1WoHFycsLcuXOVttoePHgQQPLGkB07duDGjRuYPn06mjZtmmr/69evT/WAy7S29np5eeHQoUPCvPxLly7B2NgYderUUVv4Tu09WqtWLdjZ2eHUqVOoUqWKMM986dKlWXqOlHU+tT1BmakrIz179kTHjh1x7do1XL9+HTdv3sS5c+dw7tw59O/fP9P/a+VyearTrr6Xkr1S2zLdsmVLHD58GNOnT4dYLMbJkyfh7u6e5t+7UKFCWL9+far3pXzmp9Y2PDwcvr6+ePv2LRYsWIBatWpl+Np+xPCdCV+/foVcLhdC6vcKFiwofDim5u3bt/j111/x999/Q09PD6VLlxbmDGf2/MA//kMSi8VZPsdwam9KVb5p//gPzcbGBnK5HNHR0YiIiIBcLk/zgyo0NFQIB6mN5fciIiLSbFewYEGlrVzqktoYA2l/UP6oRo0a2LhxI7Zt2wY/Pz9s2LABhQoVwqBBgzLcHZfa2AL/20JmZWWV6pHYANJ9D/7oy5cvqe7mTu3DSl3vue/PLpHCxsYGjx8/BpD89w4MDExza8T3X35Ufe98f7BPVnh5eUEmk2HPnj1Ys2YNvL29UaRIEYwfPz7N3ZmRkZFpvmdT1pMUqa2Dae0qBpCt9SsrryVFeuu8iYkJOnfujGPHjuH27dswMDDAixcv0gyG6lCkSBFhbnB6bG1tVWqXomjRoujZsyd69uwJmUyG8+fPY+rUqZg3b16mTvd29OhRJCYmYu3atVi7dq3S/c+ePYOjoyOsrKxgbGysNL/ZwcFBCJtA8gGhKafHS2FiYpKp15YiZRrJ7t278e3bNzg4OKBatWqpzrNNb92PjIwEoLyOpXWGkR/9GH4MDAxgb28PCwuLVNt//1pdXFwwcOBA/PLLL9i6dWuqB9qXL18+U1t/XV1dYWVlhVOnTmHkyJEICAhAixYtFDa2pcfY2BgJCQmp3peyPLV1WyQSoUWLFjh9+jQmTpyIq1evQiwWo379+grTn1RlaWkJExOTdKe0fvv2DQkJCcKXLSMjozRrT6k/tXnTRkZG8PT0FDZyBAYGYvr06di6dSs6duyY4UaS7xUpUiTDef4pp0hMbbaAl5cXfH19cfv2bdSqVQtnz57F7Nmz0+zLwMBA5fXnx7bOzs7o2rUrBg8ejAMHDqB06dIq9ZOC4TsTzMzMIBKJlA42AZIPSEtrQr9MJsPgwYOhr6+P/fv3o1KlStDT08OLFy+yfKRxRn78xptycJy6REZGKoT0z58/QyKRwMLCAmZmZjA2Nk7z3Jcpu41UkTKmaY25lZWVyn2lfLPX9NikaNCggTAd4O+//8aOHTuwYMECVK9eXWHL5o9SPtBSpLx2GxsbWFhYIDw8HElJSQoBPOVAzu/HI6PXaW9vj7CwMKXnDwsLQ6lSpVR8lZmTEoi/9/nzZ+FLgJmZGVxcXIRpIj9S5VSfKczNzQEkf8n4/h/jx48fERgYiFq1akEkEqn0fmjdujVat26Nr1+/4tq1a9i0aRMmTpyI2rVrK20hAQALC4s037NA8t8pq6cQy+76ldnXkiK9dR5IDkMpu3319fVRokSJVE/7lROdOXMGs2bNgr+/v8J7XywWo1mzZrh165Zw3IWqDh8+DCcnJ6XjPOLi4jBs2DD4+/sLX06aNGmCixcvIjo6Wvgy9uOHvToPGEvZMDB79mw0b95c2EOT3jSu1KT8v/nx/0hq63lqMhN+fiQWi7FgwQJ4eXlh6tSpOHnyZKpfHjJDT08PzZo1w+nTp9GvXz9cuXIlU6dRLViwYJrrdUqITmujgZeXF7Zv346HDx8iICAAzZo1y9Y8czc3N9y4cQPx8fGpjsvhw4cxf/587NmzBzVq1EDBggURERGBhISEVP/PBgcHC3tVpVIpPD090b59e2FPV4oSJUpg+vTpaN++PV68eJGp8O3h4YEtW7bg48ePac77PnPmDBwcHBSmnKRwdHREqVKlcPr0aSQmJiI+Pj7V05Gqg5GRERYsWICuXbti2rRp8Pf3z9TeAx5wmQnGxsaoUqUKAgICFD6wv379ij/++EPY9fDjt+Tw8HC8fv0anTt3RrVq1YTQdOXKFQCqb01VlampqdIBknfv3lXrc1y9elX4PeWgBicnJxgaGsLFxQXfvn2DXC5H1apVhZ///vsPa9euVZrHmJ5SpUqhUKFCShcsevfuHe7fv5+p3cApH2rfj01iYiIePHigch9p+XHqzOLFi9G5c2fI5XIYGRmhcePGwjzu7y8ekZrvxxZIPuDPwcEBJUqUgIuLC6RSqdKZLVK+xKW8B1V5Dzg7O+PKlSuIj48Xlj19+jRLF1NR9SwMb9++VTgfekhICO7fv4+6desCSA5wr1+/RqlSpRTeO8eOHcOBAwdU3gIFJM8n19fXx4ULFxSWb9++HWPGjIFIJIKJiYkwPzLFj+P0yy+/CHNAzczM0LJlSwwfPhxSqVT4oP3x9Ts7O+PSpUsKeyKkUilOnjyJqlWrZupLxI+ys36p8lrSkt46DyR/ue3YsSPOnz+P8+fPC9MqcoNy5cohIiIC27dvT/X+N2/eZCpEPHz4EP/++y86duyIOnXqKPw0atQIbm5uOH78uDD9aMiQIZBKpZg2bVqqWx/j4uKULoqSHXfu3EHZsmXRuXNnIXiHhITg+fPnmfo8KlmyJBwcHJSOObp06ZLaak2Pg4MDhg0bhnfv3mHjxo1q6dPLywv//fcfNm/ejIIFCypMC8uIi4sLrl27luoZRE6fPp3unorq1aujSJEiOH78OC5evJjls5ykGDBgACIiIhSOlUoRFhaGzZs3o0SJEsK0IhcXFyQmJgrHO3zvn3/+QXBwsHDQsUQiga2tLQ4dOpTq8SIpB8xmZp0Bks+cZWpqiqlTpyr8T06xZ88e3LhxA0OGDEnzM8fLywvnzp3DyZMn4enpme0vZOmpWrUqunbtinv37uH333/P1GO55TuTxo8fj4EDB+Lnn39Gr169kJiYiI0bNyIhIUHhQw1InptZpkwZODk5oUiRIti9ezfs7e1hbm6Oa9euCf/oszpfOy2NGzfGxYsXMX/+fDRt2hR37txROgtCdq1atQpSqRQODg7w9/fH69evsXXrVgDJB2I4Oztj+PDhGD58OMqUKYMHDx5g9erVcHNzy9Q0ALFYjHHjxmHq1KkYO3Ys2rdvj/DwcKxZswYWFhbCgaGqsLCwQI0aNbBr1y6UKFECVlZW2LlzJ+Li4rI9L9Xc3ByfP3/G5cuXUbFiRdStWxdbt27FlClT0LZtWyQmJmLz5s2wtLTM8KwJO3fuhImJCSpVqoSTJ0/i6tWrWLJkiXC6qzp16mDWrFkIDQ1FpUqVcPPmTWzatAkdOnQQtkyo8h4YOnQoAgIC8PPPP2PAgAGIioqCt7c3RCJRpuf/mZub4969e7h+/ToqVaqU5m5juVwunO9YIpFgzZo1MDc3F05H169fPxw9ehT9+vXDgAEDYGVlhYCAAOzfv1844FNV1tbW6NOnD7Zv3w4DAwO4urri4cOH2LVrF8aNGwc9PT00btwYO3fuxLRp09ClSxf8999/2LJli0LId3V1xaxZs7B48WI0bNgQUVFRWLNmDUqWLAlHR0fh9T958gQ3b95EtWrVMHLkSFy5cgV9+vTB4MGDYWBggF27duHdu3fYvHlzpl7Hj7KzfqnyWtKS3jqfomPHjli9ejXkcrnKR//fv38/1a2Lbm5uKh+/kJ7g4GDcv38/1fsMDQ3h6OiI0qVLY/DgwfD19cWHDx/Qtm1bYc/Q0aNHcf36daXXmp5Dhw5BX18fzZs3T/X+9u3b4/Llyzh+/Di6d++OcuXKYfny5Zg8eTLat2+Prl27okKFCkhKSsK9e/dw8OBBfP78GT///LNCP9HR0Wm+NgCoUqVKqnNoU64CvHHjRlSvXh2BgYHw9fVFQkJCpj6PRCIRJkyYgPHjx2PGjBlo0aIF7t+/D39/f5X7yK5+/frh4MGD2LRpE9q3b68w1/3p06ep7oECkqctpDYNzsXFBYUKFcLmzZvRr1+/TP0vHDp0KM6ePYsePXqgf//+KF68OL5+/YqLFy/i4MGDmDVrVrphsEWLFtixYwcsLS2zfdGu6tWrY8yYMVi1ahVevnyJDh06wMrKSvgfFxMTg40bNwqvr3bt2vDw8MDUqVPx8uVL1K5dG2KxGE+ePMHmzZtRq1YthWONZsyYgd69e6Njx47o06cPKlasCJlMhlu3bmHbtm3o3r17ptdfW1tbeHt7Y/To0UK/pUuXRmRkJE6dOoWTJ0+iZ8+e6R7c6OXlhbVr1+LYsWMZntUqISEh3fWnfPnyGWaDX375BadOncLy5cvh6empcJxPehi+MyklVPn4+GDcuHEwMDBA7dq1sXjxYpQrVw5A8lbH/v37Y9++ffjjjz/w559/Yt26dZg/fz6mTJkCAwMDlC1bFuvXr8eCBQtw+/ZttZ4Lt1OnTnj79i1+//137Nu3Dy4uLvD29s700bjpmT9/PpYsWYLAwECUL18emzZtEv5ZiMVibNy4Ed7e3vD19UVYWBjs7OzQr18/hbO9qKpjx44wMTGBr68vRowYAVNTUzRo0ADjxo1TeW5hikWLFuG3337DzJkzYWpqis6dO6NGjRoKZ5/Iio4dO+Ly5csYMWIERo8ejcGDB2PZsmXYsmULRo4cCZFIhFq1agn/WNMzd+5cbNmyBatWrUKxYsWwYsUKYSuISCSCr68vfHx8sGPHDnz58gVFixbF2LFjFb6IqPIeKFGiBPz8/LBkyRKMHj0aNjY2GDJkCNavXw8TE5NMvf6ePXvi0aNHGDRoEBYuXIg2bdqk2q5w4cLo378/FixYgNjYWNSrVw/r168XxsTOzg579+7F8uXLMXv2bMTHx6NkyZKYP39+pneJA8DEiRNRsGBB+Pv7Y8uWLShatCimTZuGn376CUDymUQmT56MnTt34uzZs6hcuTLWrFmjcMaX7t27IzExEXv37sWePXtgaGiIunXrYuLEicJu4QEDBmDBggUYOHAgtm7ditq1a2PPnj1YsWIFpk2bBpFIhGrVqmHHjh3ZnoqRnfVLldeSlvTW+RR2dnbCPOb0Thf2vWvXrqV62eiFCxeqJXwfPHhQYe7098qVK4cTJ04AAMaNG4eKFSviwIEDmDdvHqKjo2Fubo7atWvj4MGDGX45SREfH4+TJ0+ifv36aU6La9q0KczNzbF3717hvda0aVMcO3YM/v7+OHjwIIKCgiCXy1GsWDF4eXmhe/fuSmdEefLkCbp165ZmLdevX0/1y9iQIUMQHh6OHTt2YO3atXBwcEC7du2E/y+RkZFpfoH+UevWrSEWi7Fu3TocPXoU5cuXx9y5c1M9v7QmGBgYYNq0aRgyZAgWLlyoELhSNoilZtKkSRg4cKDS8pRT/+3atSvTW5+LFSuGQ4cOYf369fDx8cHnz59hamoKR0dHbNiwIcMD7r28vODn54eWLVuq5Zzuw4YNQ6VKlbB7924sXLgQERERsLe3R8OGDTF06FCledM+Pj7YunUrTp48ia1bt0Imk6FIkSL46aef8PPPPytslKhSpQqOHDkCX19f7Nq1C58+fYJEIkHZsmUxbdq0LP2/BpI3EBw5cgTbtm0TpqCYm5ujatWq2LRpk8KVpVNTtmxZlC9fHp8+fUK9evXSbZtylc60HDx4MMNpUVZWVhgzZgzmzp0LHx8fpTMwpUUkz+qRekSUq12/fh36+voKYTAyMhL169fHpEmT0KdPH7U+35QpU3Dz5k2FszVQ3hISEgIPDw+sWLEiza2+RET5Hbd8E+VTjx8/FvbgVK5cGeHh4diyZQvMzMwULmFNlJGnT5/iwoULOHPmDIoWLZrmqd+IKOtkMplKc/IzOl0f6R7/QkT51IABA5CQkAB/f398/PgRxsbGcHFxweLFi7N9ej7KX+Lj47F161bY2dlh1apVmTowlohUM23aNJUO7Ltw4YJGL7BD2cdpJ0REREQ53Pv371W6Gm2FChWydUYl0jyGbyIiIiIiLeF5vomIiIiItIThm4iIiIhISxi+iYiIiIi0hGc70RC5XA6ZjNPpiYiIiHIisTjzV3RWB4ZvDZHJ5PjyJUbXZRARERFRKqytTSCRaD98c9oJEREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRlvBsJzomk8kglSbpugwirZNI9CAW8/s/ERHlLwzfOiKXyxEV9QWxsdG6LoVIZ4yMTGFubq2T86wSERHpAsO3jqQEb1NTKxgYFGD4oHxFLpcjISEe0dHhAAALCxsdV0RERKQdDN86IJNJheBtamqu63KIdMLAoAAAIDo6HGZmVpyCQkRE+QI/7XRAKpUC+F/4IMqvUtYBHvdARET5BcO3DnGqCeV3XAeIiCi/YfgmIiIiItISzvnOgUaOHIz79+8qLNPT04O1tQ3q12+IQYOGwdzcHPPnz8apUycU2olEIhgaGqFIkaJo1aotunTpLtzn5+eLrVs3pfvcZ89egbGxsdDWwMAAx4+fhYmJqVLbI0cOYtmyRbC3d8DBg8cBAAEBx7FgwRwcOHAMDg6F8fHjB3Tp0hbTps2Cl1cbpT7u3r2N0aOHwsdnA2rWrC20B4CJE6ehXbuOSo+Jjo5G27bNkJCQIDwus27fvonDhw/gyZNH+Po1Cra2dqhXrwF69uwDa+v/Hfw3cuRgAMCaNRtT7adz5zaoUaMWpk+fLSx79eoFtm/3w717dxEVFQkLCws4OdVEr159Ub68IwDV/hYAcO3abeH3ly9fYM+eHbh79zYiIsJhZWWNqlWd0LXrT6hcuYrC41LeQ1WqVMOGDVtS7XvWrKm4cOEcWrZsLdSf2nvvexUqVISf384024pEIhgbG6N48ZLo1u0nNG3aPMPXSERElJ8wfOdQ5ctXwLhxU4TbSUmJ+Pffp/D1XYf//vsX69f7AQBsbGwwf/6y7x4pR1hYGI4ePQxv72XQ19dH+/adFPresGFrms9raGiocDspKQnXrl1B8+ZeSm3Pnz+bhVemGrFYjIsXz6cavq9cuYSEhIQs971hwxrs3r0djRs3xZgx42FhYYmXL19g9+7tuHz5Itas2Qh7e4cs9f3q1UsMGTIAlSpVxpgxE2BtbY1Pn0Jx8OA+DB06AD4+vqhSpSratGmPOnXqCY87ceIITpw4mubf5syZACxcOBflylXAoEHD4OBQGJ8+heLEiaMYPnwghg0bhe7deyk8RiwW4/HjhwgJCYadnb3CfXFxcfjrr2upPteP773vGRsbpdtWJpMiNDQE+/btwezZ02FqagZX13o/dkNERJRvMXznUMbGJqhSparCsurVayI2NhabN2/A48ePAAD6+gZK7QCgfv0G6Nq1HU6ePKoUvlNrn5aqVZ1w8eI5pfD9+fMnPHhwH+XKlcfXr19V7i8zz3v//h2Eh4fDyspK4b7z58+iXLny+O+/55nu98KFs9i1axtGjx6Hrl1/EpbXrFkb9eq5oX//nli5cgkWL16Zpbr37dsNc3NzLF++Gnp6/1u9GjRwR8+enbF9+2YsXeoNW1s72NraCfffuPEXgNT/Ns+fP8PChXPRrFlLTJ48AxKJRLivWbOW8PZejrVrvVGmTDk4O9cR7itf3hGvX7/EpUvnlYL5tWuXUaBAAZiamik9X2rvvbSk1bZu3fpo06YZTp48xvBNRET0Hc75zmUqVKgIAAgJ+ZhuOz09PaWt2Fnh4eGJW7duIDpa8WJAFy+eR/HiJVC2bPlsP0dqGjZ0h0gkwuXLFxSWR0ZG4M6dm1mezrBz5zaULFkaXbr0ULqvSJGiGD58NKpVqw6ZTJal/r98CQOQfB7r7xkZGWHUqLHw8PDMdJ87dmyFkZExxo6dpBC8UwwfPhq2tnbYtm2zwnJDQ0PUreuGixfPKz3mwoVzcHdvmmp/6mBgUAB6evoa6ZuIiCg3Y/jOZd69CwSQHBRTJCUlCT8JCQkIDg7GunXeePs2EC1atFLq4/v23/+kFjgbN24CqVSKq1f/UFh+4cJZjc7nNTMzh4uLq1JwvHTpAuzs7FGxYuVM9xkW9hkvXjxHvXpuaZ5lo337TujZs2+Wzzldr14DhIQEY8iQ/jh0aD/evHktBPHGjZuiZcvWmepPJpPh1q2/UauWM4yMjFJto6+vj4YNG+PBg/uIjIxQuK9JE088efIIwcHBwrKYmGjcuPEXPD3T/vul9R758UvFj23j4+Px/v07LFr0G759i0l1uhIREVF+xmknOVhS0v/Offz1axTu3buL7dv9ULlyVWELeHDwR7i7uyo9tmjR4hg/forSlBMAqbYHgNat22HKlJkKy6ytbVC9ek1cunRBCI7BwR/x5MkjzJgxBzt2pH4wnzp4eHhi4cK5CA//AisrawDZC/2fPoUCAAoXLqy2Gn/UoUNnhIV9xp49O7Fy5RIAgKWlJVxc6qJTp25KB0ZmJCoqCjExMRnWXLRoUcjlcoSEBMPCwlJYXq+eG4yMjHHp0nn06JE89eTKlT9gaWmFatWqp9rX/ft303yPzJw5VyFQp9ZWJBKhdOmy+O23RXBza6jCqyQiIso/GL5zqNRCjVgsRq1azpg8eYaw5dbGpiAWL14BAIiIiMDOnVsRFPQe06b9mma42rx5R6rLLS2tUl3u4eGJVauWIjo6Gqampjh//gwqVKiIYsWKZ/g6VD2Pc2rtGjRohCVLJPjjj4vo0KEzPn/+jH/+uYexYyciIiJCpX4VnyN5a7ZUqvqUEpFIlOrW3h/bfO/nn4eia9efcOPGX7hz5xbu3r2Ns2dP4dy50xg1ahy6dlWe8pKWlOeWSNJfVVOmj/xYaoEChqhfvwEuXjwnhO/z58+iSZNmaf5typd3xKRJ01K9r3DhImm2DQ0NxebN65GUlIQ5cxagZMlS6b84IiKifIjhO4dSDEAiGBgYwN7eHsbGJgrt9PX14ehYSbhdvXpNDB7cFxMnjsGmTdtRvHhJpb6/b68Kd3cPrFixGFev/oGWLVvj4sVz8PRsqdJjDQ2Tp0qkdXaSxMREAEh1SoWJiSnq1KmHixfPoUOHzrh06TxKliyF0qXL4u7d20rtM2JnZw+RSJTufPmvX79CIpHA2NhYqCsyMjLN9omJCanOrTc3N4enZwt4erYAkHzQ5G+//YoNG1ajefOWClun02NpaQkjIyMEB6c/x//DhyAAUDqrCZA89WTq1An4+PEDjI2Ncfv2DQwaNCzNvoyNjVV+j3zf1tGxEqpWrYZ+/Xpg3LiR8PPbpXSwbFokEhH09JSn+shkcshk6X/5ISIiyk045zuHSgk1yT8VUbp0GaXgnRpDQ0NMmzYLsbGxWLhwboZbbVVhYWGJWrVccOnSebx79xb//fccTZqoduCgmZkZDAwMEBb2OdX7P30KAQCFc2t/r0kTT/zzzz18+RKGixezN8/c0tISFSpUxN9//5XmuGzf7gcvLw+EhAQLdX3+/CnVtgkJCYiIiBBq//QpFO3atcCJE0eU2pYv74hBg4YjISEBQUHvVa5ZJBKhXr0GuHHjOmJjY1NtI5VKceXKH6ha1QmWlpZK99epUw+mpqa4dOkCLl++BAeHInB0rKhyDRnVp6cnFn4KFSqICROmIDQ0BKtXL1e4L7UfiUQEsVgMCwtjWFmZKP1YWhpDLOZVMImIKO9g+M6DHB0roW3bDnj48IHSRXiyqkmT5LOeHD9+BE5ONRROk5ceiUSCqlWr48qVSwpz2FNcunQRRYsWT7O/+vUbwsDAAAcP7sOjRw/RpEmzbL2OHj1649Wrlzh4cJ/SfW/fvsGJE0dQo0YtYQtyjRq1EBISjCdPHim1v3r1D0ilUtSq5QwgOahLJBIcPnwA8fHxqfZvYFAARYtmPF3ne336DEBcXCyWLVuY6kGxvr5r8f79O/TpMyDVxxsYGMDNrREuX774/3st1HugbOiXaASFRAo/5SvVRo2aLjh79jTOnL+scN+PPyFh0YiIisXKHZcxzTtA4Wet/5+QSMQM30RElKdw2kkeNWjQMFy4cA4bNqxBw4aNYWr6vytUPnr0MM3HFS9eHObmFkrLGzZsjGXLFmL//j345ZcJmaxlKEaPTv7p2LELChWyQ0REOM6dO4U7d25iwYJlaT7WyMgIdeu6Yc+eHahYsbLCWV6yokkTT9y+fQPe3svw5MkjuLs3gbGxMZ49e4K9e3fB1NQM06bN+q59M+zf74+JE8egV6/+qFDBETKZDI8ePcDu3TvQpEkzVK3qBCD5i8aECVMxdep4/Pxzb3Tq1BUlSpRCXFwcbt36G4cO7ReuTpoZZcqUxbRps7BgwVwEBb1H+/ad4OBQGJ8/f0ZAwHHcuvU3hg0bhbp166f7uidNGguxWIxffpmY7vN9+xaT7nvE0bGiwjnMExOliE+UKrTp2XcYHjy4i80bvbFgqW/apzSUS5EklSEoJApfvmb9wklERES5BcN3HmVhYYmffx6KlSuXwM/PF2PGjBfuGzq0f5qP++23RWjcuKnScjMzMzg7u+LGjb/g7q58f3qqVKmG9eu3YNeubVi9eiWioiJhZmaOSpUqY/VqXyG8pqVJE09cunQeTZtmb6t3ismTZ6BGjdo4fvx3LFu2EDExMXBwcECrVm3x0099FaZu6OnpYc2ajdixYwtOnDgCP79giMUSFC1aFIMHD0enTl0V+q5Xzw0bN27Hnj07sGPHVkREhENfXx/lyzti7tyFaNTII0s1N23aHGXKlMP+/Xvg5+eLsLDPwhlL1q3zy/CiOM7OrjA1NYOdnX2GB0I+f/5vuu+REyfOpzq95XuFixRDC68OOHnsAM6eOoKWrZXPukNERJQfieTqmBRMSqRSGb58iUn1vsTEBISFfYSNjQP09Q20XBmR+ujpiREUEqm05Vtl8iRER33GgUtvlLZ8lyxihQVjvBAeHoOkpKxd9IiIiCgt1tYmkEi0PwObW74p15NKpSodWPr9VAkiIiIiXWAaoVxvzJhhuH//bobtrl3L/OkJiYiIiNSJ4ZtyvUmTpuHbt2+6LoOIiIgoQwzflOuldiEhIiIiopyI5/kmIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEp7thAAAYrEIYrFIJ88tk8khk/FCq0RERJT3MXwTxGIRLC2NdXKJVQCQSmWIiPiWqQDeuXMbBAd/FG7r6+vDzs4Bbdu2x08/9clyLR8/fkCXLm3h47MBNWvWznI/30tKSsKhQ/vQrVtPtfRHREREuRfDN0EsFkEiEWOt/58ICo3U6nMXsbXAiB71IRaLMr31u3v3XujRoxcAID4+Ho8fP8TixfNQoIAhOnXqqolys+TcudNYvXolwzcRERExfNP/BIVG4k1QuK7LUJmRkRFsbAoKtwsXLoK7d+8gIOB4jgrfcjmn1BAREVEyhm/KU4yMDIXfR44cDAeHwpg+fbawbP782fj48QPWrNkIAHj16gVWrVqGJ08eoWBBW/Tq1Vepz/37/XHggD/CwsJQtaoTqlevgZMnj+HgweMAgE+fQrFmzUrcuHEdEokEVapUw8iRY1GsWHEEBBzHggVzAABubrXVOp2FiIiIch+e7YTyjCdPHuHs2dNo27aDSu2jo6MxZsxwmJiYYOPG7Rg/fhK2bdus0ObQof3w9V2Dvn0HYtu2PahZsxa2bt0k3B8bG4tRo4ZAKpVh9eqNWL3aFxYWlhg8uB8+fQpFkyaeGD16PADg6NHTqFrVSX0vmIiIiHIdbvmmXGvnzq3Yu3cXACAxMRFJSUmoVKkKmjRpptLjz58/g7i4OEyfPgempqYoXboMRo8ej2nTJght/P13okuXHmjduh0AoG/fgXj+/Bn+/fcZAODChTOIiIjA7NnzoaeXvDpNmTIT9+7dwbFjv2PgwCEwNTUFAIUpMkRERJQ/MXxTrtW+fSd07twdQPIZRd6/fwtf37UYMeJnbN68M8PHv3r1AsWKFRPCMQBUrVpN+D0yMgLBwR9RpUpVhcc5OdUQwve///6Lb99i0LJlY4U2CQkJCAx8k9WXRkRERHkUwzflWmZm5ihatJhwu2TJUjAzs8CIET/j1q0bAJQPdkxKSlK4/eP9Eome0u/pnYVFLpehePESWLRohdJ9RkZGKr4SIiIiyi8455vyJJlMBn19fcTERCssf//+nfB7+fIV8PZtICIiIoRlz549EX43NTWFvb0DHj9+qNDH48ePhN9LlSqD4OCPMDExRdGixVC0aDHY2ztgw4bVuH//LgBAJNLNxYuIiIgo52H4plwrNjYWYWGfERb2GZ8/f8Y//9yHj89yFCxYCLVru6BqVSfcunUD165dQVDQe/j5+eLVqxfC45s0aQ5raxvMnj0N//33HPfu3YGPz3KF5+jVqy8OHdqHU6dO4P37d9i3bzcuXTovBOrmzb1gbm6B6dMn4tGjhwgMfIOFC+fg+vU/UapUGQD/2wL+7NlTxMfHaWl0iIiIKCfitBMSFLG1yFXPuXfvLuGAS7FYDAsLS1Sr5oRZs36DoaEhunfviQ8fgvDbbzMhEong4eGJrl1/wsOH/wBIDsU+PhuwYsViDB8+EGZm5hg0aBjmz58tPEf79p0RFRWFjRvXITIyAtWr10LLlq3x4MF9AMlbx9es2Yi1a1dhwoRRkEplKFeuPFasWIPSpZPDd82azqhUqQqGDRuAmTN/g4dH0yy/ZiIiIsrdRHJeAUQjpFIZvnyJSfW+xMQEhIV9hI2NA/T1DbRcmbLceHl5bfn7779QqlRp2NnZC8sWL56PDx/ew9t7vQ4ryxn09MQIColEfKI0ax3IkxAd9RkHLr3Bl68JCneVLGKFBWO8EB4eg6QkmRqqJSIi+h9raxOdZB9u+SbIZHJERHyDWKybuckymTxHBm8AOHMmAG/evML48VNRsGBB3Lt3B2fPBmD8+Cm6Lo2IiIhyIYZvApCzA7AujR07EatXr8S0aRMQHf0VhQsXxejR4+Hl1UbXpREREVEuxPBNlI7kgyln67oMIiIiyiN4thMiIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItISnmqQACRf5ZIX2SEiIiLSLIZvglgsgpWVEcRiiU6eXyaTIjw8NlMBvHPnNggO/oiRI39B9+69lO5funQBjh49jP79B2HgwCEq9deyZWuV2qriwYP7kMsBJ6fqaumPiIiI8gaGb/r/rd4SvD6xCbFhH7X63EY2DijVehDEYlGmt37r6enh0qULSuE7KSkJly9fhEik+pb8TZt2oECBApl6/vQMH/4zpk2bxfBNREREChi+SRAb9hGxIW91XYbKatd2wY0b1xESEgw7O3th+d27t2FoaIQCBQxV7svKykoTJRIREREpYPimXKtixcoIDHyDS5fOK2z9vnDhLDw8PHHx4jlh2cmTx3Dw4F4EBgZCLBbB0bESRo0ahwoVHAEoTjvx8/PFvXt3ULdufRw8uA+RkRGoUqUaJkyYguLFSwIArl//E5s3b8CbN69gZGSMunXrY9SocTA3N4ebW20AwIIFc3Dv3h0MGDAYXbq0xc8/D8XhwwdgYGCArVv3QCQSYe1ab1y9egmJiYmoUKEihg8fDUfHSgAAuVwOf/+dOHnyGD58CIKBgQGcnGrgl18monDhIgAAN7famDVrHo4fP4JHjx6iUKFCGDVqHABg7dpV+PQpFE5ONTFz5lxYWlpq+k9CREREGeDZTihXa9y4KS5duiDcTkxMxJUrf6Bp02bCssuXL2HZsoXo2vUn7NlzEN7eGxAfH49Fi+am2e/jxw9x//5dLFmyCqtWrUNw8EcsX74YABAREYHp0yeiVau22L37IBYsWIr79+9h3TpvAMDRo6cBAKNHj8eYMROEPs+ePQVv7/WYN28xTE1NMXHiaLx//xaLF6/Cxo3bUblyVQwbNhDPnz8DAOzfvwc7dmzFsGGj4e9/GAsXLsfbt4FYvXqlQq3e3svQsWMX7Ny5D6VKlcacOTOwfbsffv31NyxZsgpPnjzCrl3bsjfQREREpBbc8k25moeHJ/z9dwpTT27e/BuWlpYoX95RaGNhYYHJk2egRYtWAAB7ewe0adMey5YtTLPfpKQkzJw5F+bmFgCAzp27Y/16HwDAp08hSEhIgJ2dPeztHWBv74DFi1dAKpUCAGxsCgIATE1NYWpqiq9fowAAHTp0QalSpQEAt2/fxMOHD3D8+DlhysuQISPw8OE/OHBgL6ZPn40iRYphxozZcHNrKNTduHFTXLhwVqHWFi1aw929CQCgXbuOuHbtCgYPHo6KFSsDAFxc6uDVq5dZHWIiIiJSI4ZvytUcHSuicOEiwtSTixfPomnT5gptqleviTdvXmPbts14//4d3r4NxIsXzyGTydLs19raWgjeQHKQTkxMBACUK1cBTZs2x+TJY2Frawdn5zqoV88N9es3TLfWokWLCb+nbN3u2rWtQpuEhATEx8cDANzcGuLx40fw8/PFu3dvERj4Gq9evUShQrYKjylevITwe8o895RpKQBgYFAACQlh6dZGRERE2pGjpp28fv0aNWrUwOHDh4VlT58+Ra9evVC9enW4u7vDz89P4TEymQw+Pj5o0KABnJycMGDAAAQGBiq0UUcflHN5eHji0qULiI+Px9WrV5TC9/nzZ9C3b3e8f/8OFStWxvDhozFy5Nh0+9TXN0j3/tmz52PPnoPo3r0nvnwJw+zZ0zFu3Mh0H/P92VRkMhlMTEywdesehZ/duw9i3rzk6S27d2/HqFFDEB4ejho1amH8+Kno0aO3Ur96esrfocXiHLVqE+VbYrEIenpijf3o6voMRJR1OWbLd2JiIiZMmIBv374Jy8LDw9G/f380bdoUc+bMwf379zFnzhxYWlqiU6dOAIB169Zh7969WLhwIezs7LB06VIMGjQIJ06cgIGBgVr6oJzNw6Mpdu3ahhMnjqJw4SIoUaKkwv07d25FmzbtMWHCVGHZ1auXASQf1JiZUxICwKNHD3Hx4lmMHj0exYuXRNeuP+Hs2VOYO3cmwsO/wMrKOsM+Spcui5iYGCQkJKB06TLC8sWL56Fs2XLo1Kkbtm/fggEDBqFXr37C/f7+OyCX84JERLmBNq6hkJXrJBCRbuWY8L169WqYmJgoLNu/fz8MDAwwe/Zs6OnpoUyZMggMDMSmTZvQqVMnJCQkYMuWLZg4cSIaNWoEAFi5ciUaNGiAc+fOoVWrVmrpI78wsnHIlc9ZrlwFFC1aDBs3rkWvXv2V7re1tcPDh//g33+fwdTUFNeuXcbhw/sBJE/zyOz5vU1MTHD48AHo6emjbdsOiI+Px/nzZ1C0aHFYWFgmvy4jY7x58xqRkRGp9lGnTl2UK1cev/46FWPHToSdnT2OHj2MkyePYcWKNULdt27dQP36DSGRiHH6dAAuX74Ea2ubTNVLRLqh6WsoZOc6CUSkOzkifN+6dQv79u3DkSNH4O7uLiy/ffs2nJ2dFXaru7q6wtfXF2FhYQgKCkJMTAxcXV2F+83NzVGpUiXcunULrVq1UksfeV3y5d2lKNV6kI6eX5rtDw4PD09s3+6ncJaTFGPHTsKSJfMxcuRgGBjoo2zZ8pgxYw5mzZqGJ08eoUaNWpl6rlKlSmP+/KXYunUTfv/9AMRiMWrWdMby5T7CdI/u3Xtiz54dePv2jcIZT1JIJBKsXLkO69Z5Y9asqYiNjUWJEqUwf/4S1K7tAgCYOXMuVqxYjJ9/7g1jYxNUrlwFEyZMxfLli/Dx4wc4OBTOwkgRkbbltmsoEJFm6Tx8R0VFYdKkSZgxYwYcHBS3ggYHB6N8+fIKy2xtkw82+/DhA4KDgwFA6XG2trb4+PGj2vrI62QyOcLDY3U2dzA5/GcufB88eFzh9qBBwzBo0LA026xatU6pjyZNmqXaduDAIUqXmffyagMvrzbC7fr1G6B+/QZp1vdjH9eu3VZqY2lpiWnTZqXZR4UKjvD13aq0vH37Tmn2W7NmbaVl06fPTvM5iIiISLt0Hr5nz56N6tWro02bNkr3xcXFKc25TpkiEB8fj9jYWABItU1kZKTa+sgqPb3UD3qTyXLeATJZCcCUv2VyqnyWSSQ8eJRyJ229d7mOEOUuOg3fR44cwe3bt3H8+PFU7zc0NERCQoLCspTTsBkbG8PQMPm0agkJCcLvKW2MjIzU1kdWJB9oY5LqfXFxEnz+LIZEIkozoBNRMnPzrK+HRPkB1xGi3EWn4fvQoUMICwtTmOcNALNmzYKfnx8KFy6M0NBQhftSbtvZ2SEpKUlYVrx4cYU2jo7JF1mxt7fPdh9ZIZPJERX1LdX7EhLiIZPJIJXKkZSU9rmmiXIykUg7W9yiomIhlXI9odxHIhFrJRhzHSHKGnNzI53sOdJp+F62bBni4uIUljVr1gyjR4+Gl5cXTp48ib1790IqlUIiST5V0/Xr11GqVCnY2NjAzMwMpqamuHHjhhCco6Ki8OTJE/Tq1QsA4OzsnO0+siqtYC2VcnoH5X7aOuOhVCrjl1SidHAdIcpddDrnwc7ODiVKlFD4AQAbGxsUKVIEnTp1QnR0NKZPn44XL17g8OHD2L59O4YMST6QzcDAAL169cKyZctw4cIFPHv2DGPHjoW9vT08PT0BQC19EBERERGpg84PuEyPjY0NNm/ejPnz56NDhw4oVKgQJk2ahA4dOghtRo8ejaSkJMyYMQNxcXFwdnaGn5+fcAClOvogIiIiIlIHkZyXy9MIqVSGL19iUr0vMTEBYWEfYWPjkOFlzIlyMj09MYJCIhGfKM1aB/IkREd9xoFLb/Dlq+KB0SWLWGHBGC+Eh8dwlzrlSnp6YlhZmeDJ9rkaOc+3kV1xVOr7K9cRoiyytjbRyZxvnmqDiIiIiEhLcvS0E9Ke5Msg556L7BARERHlRgzfBLFYBEsrI0jEEp08v1QmRUR4bKYCeOfObRAc/L8rkIrFYhgbG6NcuQr4+eehcHKqoYlSU+Xn54tTp04oXXWTiIiI6EcM3wSxWASJWALfyzvwITJEq89d2MIOQxr1gVgsyvTW7+7de6FHj+TTQcrlQFRUBHx912L8+FHYs+cQbG3tNFGykh49eqNjx65aeS4iIiLK3Ri+SfAhMgSBYe91XYbKjIyMYGNTULhdsGBBTJw4De3bt8Tly5fQpUt3rdRhbGwMY2NjrTwXERER5W484JLylJQLKenr66Nz5zbw8VmOXr26wMurCe7evQ25XI7du7ejS5d2aNKkPvr1+wlnz54SHn/37m00alQHd+/eRq9eXeDhUQ9DhvTH27eB2L7dD23aNEPLlh5YuXIJUk4U5Ofni86d2wAAPn78ADe32rh797ZCXW5utREQcFxoP2bMcBw4sBft2jVH06ZumDVrGsLCPuO3336Fp2cDdOzYCqdOndDGkBEREZEWccs35RmfPoXCx2cFjIyM4epaH7t2bcORI4ewePFKmJmZoXTpsti4cR3Onj2FceMmo2TJUrh//y6WLVuE6OhodOzYBQAglUqxevUKTJnyKwoUMMD06ZMwdOgAuLrWw5o1G3Hv3h0sW7YQLi51Ub9+gyzV+uDBPZiZmcLHxxdBQe8xdep43Lp1A3369EffvgPg778bS5cuQL16brCwsFTjKBEREalO0ydkyI8nXWD4plxr586t2Lt3F4DkwJyQkICSJUth7tyFsLe3BwC4utaHs3MdAEBsbCz27duDmTPnCKG5SJGiCA7+iD17dgjhGwB+/nkYqlSpCgBwd/fA/v3+mDRpOgwNDVGiREls2bIRr169zHL4lslkmDx5JszMzFCiREmUL18Benr66N49eQ579+49cfz473j37h3DNxER6YRYLIKVlRHEGjwhg0wmRXgmT7qQ2zF8U67Vvn0ndO6cPK9bLBbD3NwCpqamCm2KFi0m/P7mzSskJMRj3rxZWLBgjrA8JbjHx8cJy4oXLyH8XqCAIaytbWBoaCgsMzAwQEJCfJZrt7KyhpmZmcJz2NnZK/QPIFvPQURElB3JW70leH1iE2LDPmb8gEwysnFAqdaDsnTShdyM4ZtyLTMzc4VwnZoCBQoIv6es2HPnLkKJEiWV2n5/tVE9PcVVQyzO+uERSUlJSst+7D+7z0FERKQpsWEfNXKV1vyKn/aUb5QoURISiQTBwR9RtGgx4ef69T/h779TLeFXX18fABAdHS0se//+Xbb7JSIioryBW74p3zA1NUX79p2wadN6mJiYoGpVJzx4cB/r1/ugZ8++ankOG5uCKFy4CPbt241ixYojPj4OPj4rhGkkRERElL8xfJOgsIV2Lkqjy+ccNWocrKys4efni8+fP6FQIVv07z8IvXr1U0v/IpEIv/76G7y9l2HAgJ6ws7PHwIFDsHnzBrX0T0RERLmbSJ5ysmJSK6lUhi9fYlK9LzExAWFhH2Fj46Awz1hXcuPl5Sln0NMTIygkEvGJ0qx1IE9CdNRnHLj0Bl++JijcVbKIFRaM8UJ4eAySkmRqqJZIu/T0xLCyMsGT7XM1Ml/WyK44KvX9lesIaUxefw9bW5tAItH+DGxu+SbIZHJEhMdq9DyeGT0/gzcRERHlBwzfBIABmIiIiEgbeLYTIiIiIiItYfgmIiIiItIShm8iIiIiIi1h+NYhnmiG8j05IIec6wIREeUbDN86IJEkn9IvISFex5UQ6Zg8EVKpHNFxWTxVIRERUS7Ds53ogFgsgZGRKaKjwwEABgYFIBLp5jR/RNkhk4kgkyUB8kyGZzkAeSK+fYvCo1fhSOQ5ionyLLFYpNFT2fJsXZTbMHzriLm5NQAIAZwoNxKLxfgaFYskaebCsxxySKVyPHoVjhtPwzRUHRHpmlgsgqWlsUYvZCKVyhAR8Y0BnHINhm8dEYlEsLCwgZmZFaTSJF2XQ5RpEokIFhbGWLnjMoJCojL1WLk8eaoJt3gT5W1isQgSiRhr/f9EUGik2vsvYmuBET3qQywWMXxTrsHwrWNisRhise4vMU+UWXp6YhgaGuJrrFTp0vBERN8LCo3EmyDu6SUCeMAlEREREZHWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWmJnq4LICKitInFIojFIo31L5PJIZPJNdY/EREpYvgmIsqhxGIRLC2NIZFobielVCpDRMQ3BnAiIi1h+CYiyqHEYhEkEjHW+v+JoNBItfdfxNYCI3rUh1gsYvgmItIShm8iohwuKDQSb4LCNda/prasc0oLEZEyhm8ionzKwswQcpkM5uZGGulfJpMiPDyWAZyI6DsM30RE+ZSJoQFEYjFen9iE2LCPau3byMYBpVoP4pQWIqIfMHwTEeVzsWEfERvyVtdlEBHlCzzPNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZbwbCdERKQxmrqAD8CL+BBR7sTwTUREaqdnYg6ZBi/gAwBSmRQRvIgPEeUyDN9ERKR2egWMIRaL4Xt5Bz5Ehqi9/8IWdhjSqA8v4kNEuQ7DNxERacyHyBAEhr3XdRlERDkGD7gkIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItISnYfvsLAwTJw4Ea6urqhRowYGDx6MFy9eCPc/ffoUvXr1QvXq1eHu7g4/Pz+Fx8tkMvj4+KBBgwZwcnLCgAEDEBgYqNBGHX0QEREREWWXzsP3sGHD8O7dO2zatAkHDx6EoaEh+vXrh9jYWISHh6N///4oWbIkDh06hFGjRsHb2xuHDh0SHr9u3Trs3bsX8+bNw759+yASiTBo0CAkJCQAgFr6ICIiIiJSB52G7/DwcBQtWhS//fYbqlatijJlymD48OH49OkT/vvvP+zfvx8GBgaYPXs2ypQpg06dOqFfv37YtGkTACAhIQFbtmzBqFGj0KhRIzg6OmLlypUICQnBuXPnAEAtfRARERERqYNOw7eVlRVWrFiBcuXKAQA+f/4MPz8/2Nvbo2zZsrh9+zacnZ2hp6cnPMbV1RWvX79GWFgYnj17hpiYGLi6ugr3m5ubo1KlSrh16xYAqKUPIiIiIiJ10Mu4iXbMnDlT2Eq9fv16GBsbIzg4GOXLl1doZ2trCwD48OEDgoODAQAODg5KbT5+/AgAaukjq/T0dD6rh0hjJBLtvL+19Tw5UX5+7arKyWPEdYRjkNvx76cZOSZ89+3bF926dYO/vz9GjBiBPXv2IC4uDgYGBgrtChQoAACIj49HbGwsAKTaJjIyEgDU0kdWiMUiWFmZZPnxRJTM3NxI1yVQDsb3B8cA4Bjkdvnt75djwnfZsmUBAL/99hvu37+PXbt2wdDQUOmgx/j4eACAsbExDA0NASTP2075PaWNkVHyH1IdfWSFTCZHVNS3LD+eKKeTSMRa+YcZFRULqVSm8efJibQ1xrlZTn5/cB3hGOR2ef3vZ25upJOt7joN32FhYbh+/TpatmwJiUQCABCLxShTpgxCQ0Nhb2+P0NBQhcek3Lazs0NSUpKwrHjx4gptHB0dAUAtfWRVUhL/ERBll1Qq47pEaeL7g2MAcAxyu/z299PpJJvQ0FCMHz8eN2/eFJYlJibiyZMnKFOmDJydnXHnzh1IpVLh/uvXr6NUqVKwsbGBo6MjTE1NcePGDeH+qKgoPHnyBLVr1wYAtfRBRERERKQOOg3fjo6OcHNzw5w5c3D79m08f/4ckydPRlRUFPr164dOnTohOjoa06dPx4sXL3D48GFs374dQ4YMAZA8T7tXr15YtmwZLly4gGfPnmHs2LGwt7eHp6cnAKilDyIiIiIiddDptBORSIRVq1Zh+fLl+OWXX/D161fUrl0bu3fvRuHChQEAmzdvxvz589GhQwcUKlQIkyZNQocOHYQ+Ro8ejaSkJMyYMQNxcXFwdnaGn5+fcACljY1NtvsgIiIiIlIHnR9waWZmhtmzZ2P27Nmp3l+tWjXs27cvzcdLJBJMnDgREydOTLONOvogIiIiIsqu/HViRSIiIiIiHWL4JiIiIiLSEoZvIiIiIiItYfgmIiIiItISnR9wSUREpEtisQhisUjt/eriynlElPMxfBMRUb4lFotgaWnMoExEWsPwTURE+ZZYLIJEIsZa/z8RFBqp1r6dKhRGtxbV1donEeV+DN9ERJTvBYVG4k1QuFr7LFzIXK39EVHewP1sRERERERawvBNRERERKQlDN9ERERERFrC8E1EREREpCUqh+9nz55psg4iIiIiojxP5fDduXNnbNy4EXK5XJP1EBERERHlWSqHb09PT6xYsQI//fQT3r17p8maiIgEEokYenqa+dHEVQ2JiIjSo/J5vleuXIk2bdpg9uzZaNu2LSZPnozu3btrsjYiyscszAwhl8lgbm6kseeQyaQID4+FTMY9ekREpB2ZusiOh4cHXFxcsGTJEsyZMwcXLlzA/PnzYWtrq6n6iCifMjE0gEgsxusTmxAb9lHt/RvZOKBU60EQi0UM30REpDWZvsKlqakp5s6di06dOmHmzJlo06YNKlSooNBGJBJh+/btaiuSiPKv2LCPiA15q+syiIiI1CJLl5eXy+V48uQJQkJCIJfLlQ7C5EGZRERERETKMh2+nz17hunTp+PJkydo3Lgx5syZg0KFCmmiNiIiIiKiPEXl8J2QkAAfHx9s27YNJiYmWLx4Mdq2bavJ2oiIiIiI8hSVw3fr1q3x9u1bNG3aFLNnz0bBggU1WRcRERERUZ6jcviOiorC8uXL0apVK03WQ0RERESUZ6kcvmfNmoWGDRtqshYiIiIiojxN5Stcjhs3Di9fvtRkLUREREREeZrK4ZunDyQiIiIiyh6VwzcREREREWVPps7z/eTJE8THx6vU1tnZOUsFERERERHlVZkK33PmzMmwjVwuh0gkwtOnT7NcFBERERFRXpSp8D1z5kyULVtWU7UQEREREeVpmQrfVapUQbVq1TRVCxERERFRnsYDLomIiIiItIThm4iIiIhIS1QO3zt27ECZMmU0WQsRERERUZ6m8pxvFxcX4ffY2Fj8+eefeP/+PeRyORwcHODq6gpLS0sAQEBAAExMTNCoUSO1F0xERERElFtl6oBLqVSKtWvXYuvWrYiLi1O46qWBgQF69eqFoUOHYtGiRRg1apTaiyUiIiIiys0yFb7Hjx+P06dPw8vLC15eXihRogTEYjHevXuHM2fOYPv27fj9999RqFAhdOjQQVM1ExERERHlSiqH74CAAJw9exarV6+Gp6enwn1lypSBu7s7ypcvj8WLF2PIkCHQ08tUriciIiIiyvNUPuBy//796NChg1LwTiGXy3Hw4EFYWlri4sWLaiuQiIiIiCivUDl8P3/+HE2aNEnz/mfPnuHTp0+YOXMm/vvvP7UUR0RERESUl6gcvmNjY2FmZpbm/RUrVsS1a9dga2uLuLg4tRRHRERERJSXqDwxu2jRonjy5AmcnZ3TbGNgYIDHjx+jaNGiaimOiIiIKCMSiWauGSiTySGTyTNuSJQJKodvT09PbN++HZ06dYKpqWmqbSIjI7F9+3ae6YSIiEhL8nPwtDAzhFwmg7m5kUb6l8mkCA+PzfHjQLmLyuG7d+/eOHToEPr06YPZs2ejWrVqCvffvXsXs2fPhkgkQp8+fdReKBEREf2Pnok5ZBoMnlKZFBE5PHiaGBpAJBbj9YlNiA37qNa+jWwcUKr1IIjFohw9BpT7qBy+rays4OvrizFjxqBbt26wsbERppe8f/8eYWFhKF68ODZs2CBc6ZKIiIg0Q6+AMcRiMXwv78CHyBC19l3Ywg5DGvXJNcEzNuwjYkPe6roMIpVk6mTcjo6OOHr0KI4fP46LFy8iKCgIcrkcVapUQZMmTdCmTRsYGhpqqlYiIiL6wYfIEASGvdd1GUSkokxfCcfQ0BBdunRBly5dMmwrl8uxdu1adOvWDYUKFcpSgUREREREeYVmjtL4fzKZDGvXrkVoaKgmn4aIiIiIKFfQaPgGkrd+ExERERGRFsI3ERERERElY/gmIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItyfQVLlPIZDJEREQAAKysrCASiZTaSCQS7NixA6VKlcpygUREREREeUWmw/eJEyewd+9e/PPPP0hKSgKQfMn5mjVrokePHmjatKlCexcXF/VUSkRERESUy6kcvmUyGSZMmICAgADY2trCy8sLBQsWBACEhITg5s2bGDVqFNq1a4dFixZprGAiIiIiotxK5fC9Z88enD59GlOmTEGfPn0gFitOF5fJZPD398eCBQvQoEEDtGrVSu3FEhERERHlZiofcHn48GF069YN/fr1UwreACAWi9GzZ0907doV+/fvV2uRRERERER5gcrh+82bN2jUqFGG7Ro0aIBXr15lqygiIiIiorxI5fAdGxsLCwuLDNtZWVnhy5cv2SqKiIiIiCgvUjl8y+VySCSSjDsUiyGTybJVFBERERFRXpTl83xTzicWiyAWK59/XV1kMjlkMrnG+iciIiLKazIVvmfPng1TU9N020RHR2erIFIPsVgEKysjiMUZ763IKplMivDwWAZwIiIiIhWpHL6dnZ0BJE8/SY+JiQlq166dvaoo25K3ekvw+sQmxIZ9VHv/RjYOKNV6EMRiEcM3ERHlWRKJyjN0M417kPMnlcP3zp07NVkHaUhs2EfEhrzVdRlERES5ip6JOWQyGczNjTT2HFKZFBHcg5zvZHnOd2RkJD5+/Ai5XA4HBwdYWlqqsSwiIiIi3dErYAyxWAzfyzvwITJE7f0XtrDDkEZ9uAc5H8p0+L5+/TrWrVuHO3fuKExBqVWrFoYOHQo3Nze1FkhERESkKx8iQxAY9l7XZVAekqnwvW3bNixevBgODg7o1asXSpQoAYlEgrdv3+LChQsYNGgQJk6ciAEDBmiqXiIiIiKiXEvl8P3gwQMsXboUvXv3xsSJE6Gvr69w/4QJE7B8+XIsX74ctWvXRrVq1dReLBERERFRbqbyIbzbt2+Hs7Mzpk2bphS8geSL60ycOBH16tXDjh071FokEREREVFeoHL4vnv3Ljp37pxhu44dO+LOnTvZKoqISFskEjH09NT/o8kLXBERUe6l8rSTz58/w97ePsN2hQoVwpcvX7JVFBGRpmn6NGI8hRgREaVG5fBtbW2N9+/fZ3gBnaCgIBQqVCjbhRERaZImTyPGU4gREVFaVA7fderUgb+/P9q1aweRKPXdqXK5HP7+/qhXr57aCiQi0iSeRoyIiLRJ5TnfAwcOxOPHjzFjxgzExcUp3R8XF4epU6fi2bNn6Nu3r1qLJCIiIiLKC1Te8l2hQgXMnz8f06dPx/nz51G3bl0ULVoUenp6CAoKwtWrV/Ht2zcsWrQIZcqU0WTNRERERES5UqYustOuXTuUK1cOGzZswLVr1xAdHQ0AMDIygoeHB4YMGYLy5ctrpFAiIiIiotwu05eXr1SpEnx8fCCXyxEREQG5XA5ra2tN1EZERERElKeoPOf7RyKRCFZWVkrBOzo6GgsXLsx2YUREREREeU2mwvf+/fvRtWtXdO3aFXv27FG6/8iRI2jRogWvcElERERElAqVp53s3LkT8+fPh4ODAwwNDfHbb79BIpGgW7duePPmDaZNm4Z79+7B3NwcM2bM0GTNRERERES5ksrh+9ChQ2jQoAHWr18PPT09LFmyBFu3bkX58uUxaNAgfPv2Dd26dcMvv/wCS0tLDZZMRERERJQ7qTzt5O3bt+jWrRv09JLzeu/evfHmzRv88ssvcHBwwP79+zF79mwGbyIiIiKiNKgcvmNjYxUuG29jYwMAKF68OA4cOIAqVapkqYCIiAj8+uuvaNiwIWrWrIkePXrg9u3bwv1Pnz5Fr169UL16dbi7u8PPz0/h8TKZDD4+PmjQoAGcnJwwYMAABAYGKrRRRx9ERERERNmlcviWy+UKl5WXSCQAgCFDhsDQ0DDLBYwbNw7//PMPVqxYgYMHD6Jy5coYOHAgXr58ifDwcPTv3x8lS5bEoUOHMGrUKHh7e+PQoUPC49etW4e9e/di3rx52LdvH0QiEQYNGoSEhAQAUEsfRERERETqkOnzfP/Iysoqy48NDAzEn3/+CX9/f9SsWRMAMH36dFy5cgUnTpyAoaEhDAwMMHv2bOjp6aFMmTIIDAzEpk2b0KlTJyQkJGDLli2YOHEiGjVqBABYuXIlGjRogHPnzqFVq1bYv39/tvsgIiIiIlKHLJ/nO8X3W8Mzy8rKChs3blSYsiISiSCXyxEZGYnbt2/D2dlZmGcOAK6urnj9+jXCwsLw7NkzxMTEwNXVVbjf3NwclSpVwq1btwBALX0QEREREalDprZ8jxgxAgYGBgrLhg4dCn19fYVlIpEI58+fz7A/c3NzYWtzilOnTuHt27dwc3PDypUrlS5Xb2trCwD48OEDgoODAQAODg5KbT5+/AgACA4OznYfWaWnl+3vNlkmkWjnubX1PJTz8G+fseyOEcc4YxxjzeL4al5OHiNmCc1QOXy3b98+W1u5VXHnzh1MmzYNTZo0gYeHBxYuXKgU9gsUKAAAiI+PR2xsLACk2iYyMhIAEBcXl+0+skIsFsHKyiTLj88tzM2NdF0CUY7F9UPzOMaaxfHVPI5x/hsDlcP3okWLAAAPHjxAUFAQihcvjsqVK6utkPPnz2PChAlwcnLCihUrAACGhoZKBz3Gx8cDAIyNjYUDPRMSEhQO+oyPj4eRkZHa+sgKmUyOqKhvWX58dkkkYq28maOiYiGVyjT+PJTzaOs9lptld/3gGGeMY6xZHF/Ny8mfo3k9S5ibG+lkq7vK4TsqKgpDhgzB/fv3hWXVq1fHihUrlKZsZNauXbswf/58eHp6YtmyZcJWaHt7e4SGhiq0TbltZ2eHpKQkYVnx4sUV2jg6Oqqtj6xKSsqZK5M6SaWyfPE6ibKC64fmcYw1i+OreRzj/DcGKsf9VatW4cmTJxg1ahR8fX0xefJkvH79GjNnzsxWAXv27MFvv/2Gnj17YtWqVQrTP5ydnXHnzh1IpVJh2fXr11GqVCnY2NjA0dERpqamuHHjhnB/VFQUnjx5gtq1a6utDyIiIiIidVB5y/elS5cwbtw49O3bFwDQsGFD2NnZYcKECfj27RuMjY0z/eSvX7/GggUL4OnpiSFDhiAsLEy4z9DQEJ06dcLmzZsxffp0/Pzzz3jw4AG2b9+OOXPmAEiep92rVy8sW7YM1tbWKFKkCJYuXQp7e3t4enoCgFr6ICIiIiJSB5XD96dPn5TmeNepUwdSqRQfP35EmTJlMv3kZ86cQWJiIs6dO4dz584p3NehQwcsWrQImzdvxvz589GhQwcUKlQIkyZNQocOHYR2o0ePRlJSEmbMmIG4uDg4OzvDz89P2IJuY2OT7T6IiIiIiNRB5fCdlJSkFEYtLCwA/O8AxswaOnQohg4dmm6batWqYd++fWneL5FIMHHiREycOFGjfRARERERZZdaDvGUy+Xq6IaIiIiIKE9TS/jW9Pm/iYiIiIjygkxd4XL27NkwNTUVbqds8Z45cyZMTP53QRmRSITt27erqUQiIiIiorxB5fDt7OwMQHmKSWrLOQ2FiIiIiEiZyuF7586dmqyDiIiIiCjP0/41NYmIiIiI8imGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItIShm8iIiIiIi1h+CYiIiIi0hKGbyIiIiIiLWH4JiIiIiLSEoZvIiIiIiItYfgmIiIiItIShm8iIiIiIi1h+CYiIiIi0hI9XRdARERERFknFosgFovU3q9Ewm20msDwTURERJRLicUiWFoaMyjnIgzfRERERLmUWCyCRCLGWv8/ERQaqda+nSoURrcW1dXaJzF8ExEREeV6QaGReBMUrtY+CxcyV2t/lIz7KIiIiIiItIThm4iIiIhISxi+iYiIiIi0hOGbiIiIiEhLGL6JiIiIiLSE4ZuIiIiISEsYvomIiIiItIThm4iIiIhIS3iRHcoWTV3OViaTQyaTa6RvIiIiIl1h+KYs0TMxh0wmg7m5kUb6l8qkiAiPZQAnIiKiPIXhm7JEr4AxxGIxfC/vwIfIELX2XdjCDkMa9YFYLGL4JiIiojyF4Zuy5UNkCALD3uu6DCIiIqJcgQdcEhERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpiZ6uCyAiIiKi/Esi0dy2YJlMDplMrrH+s4Lhm4iIiIi0Ts/EHDKZDObmRhp7DqlMiojw2BwVwBm+iYiIiEjr9AoYQywWw/fyDnyIDFF7/4Ut7DCkUR+IxSKGbyIiIiIiAPgQGYLAsPe6LkNreMAlEREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaUmOCt/r1q1D7969FZY9ffoUvXr1QvXq1eHu7g4/Pz+F+2UyGXx8fNCgQQM4OTlhwIABCAwMVHsfRERERETZlWPC97Zt2+Dj46OwLDw8HP3790fJkiVx6NAhjBo1Ct7e3jh06JDQZt26ddi7dy/mzZuHffv2QSQSYdCgQUhISFBbH0RERERE6qDz8B0SEoKff/4Z3t7eKFWqlMJ9+/fvh4GBAWbPno0yZcqgU6dO6NevHzZt2gQASEhIwJYtWzBq1Cg0atQIjo6OWLlyJUJCQnDu3Dm19UFEREREpA46D9+PHz+GhYUFjh07BicnJ4X7bt++DWdnZ+jp/e905K6urnj9+jXCwsLw7NkzxMTEwNXVVbjf3NwclSpVwq1bt9TWBxERERGROuj8IjseHh7w8PBI9b7g4GCUL19eYZmtrS0A4MOHDwgODgYAODg4KLX5+PGj2vogIiIiIlIHnYfv9MTFxcHAwEBhWYECBQAA8fHxiI2NBYBU20RGRqqtj6zS09PdjgWJROc7NbItL7yGvIx/n4xld4w4xhnjGGsWx1fzOMaal9PGKEeHb0NDQ6WDHuPj4wEAxsbGMDQ0BJA8bzvl95Q2RkZGausjK8RiEaysTLL8eALMzbM+/kQ5Ad/Dmscx1iyOr+ZxjDUvp41xjg7f9vb2CA0NVViWctvOzg5JSUnCsuLFiyu0cXR0VFsfWSGTyREV9S3Lj88uiUSc495smRUVFQupVKbrMigNeeE9pmnZfQ9zjDPGMdYsjq/mcYw1L60xNjc30slW8Rwdvp2dnbF3715IpVJIJBIAwPXr11GqVCnY2NjAzMwMpqamuHHjhhCco6Ki8OTJE/Tq1UttfWRVUhKDY3ZIpTKOIeVqfA9rHsdYszi+mscx1rycNsY5axLMDzp16oTo6GhMnz4dL168wOHDh7F9+3YMGTIEQPI87V69emHZsmW4cOECnj17hrFjx8Le3h6enp5q64OIiIiISB1y9JZvGxsbbN68GfPnz0eHDh1QqFAhTJo0CR06dBDajB49GklJSZgxYwbi4uLg7OwMPz8/4QBKdfShKWKxCGKxSCN957SDC4iIiIgoh4XvRYsWKS2rVq0a9u3bl+ZjJBIJJk6ciIkTJ6bZRh19qJtYLIKlpTFDMhEREVE+kqPCd34iFosgkYix1v9PBIVm75SGqXGqUBjdWlRXe79ERERElHUM3zoWFBqJN0Hhau+3cCFztfdJRERERNnDOQ9ERERERFrC8E1EREREpCUM30REREREWsLwTURERESkJQzfRERERERawvBNRERERKQlDN9ERERERFrC8E1EREREpCUM30REREREWsLwTURERESkJQzfRERERERawvBNRERERKQlDN9ERERERFrC8E1EREREpCUM30REREREWsLwTURERESkJQzfRERERERawvBNRERERKQlDN9ERERERFrC8E1EREREpCUM30REREREWsLwTURERESkJQzfRERERERawvBNRERERKQlDN9ERERERFrC8E1EREREpCUM30REREREWsLwTURERESkJQzfRERERERawvBNRERERKQlDN9ERERERFrC8E1EREREpCUM30REREREWsLwTURERESkJXq6LoBIk8RiEcRikcb6l8nkkMnkGuufiIiI8haGb8qzxGIRLC2NIZFobgePVCpDRMQ3BnAiIiJSCcM35VlisQgSiRhr/f9EUGik2vsvYmuBET3qQywWMXwTERGRShi+Kc8LCo3Em6BwXZdBRERExAMuiYiIiIi0heGbiIiIiEhLGL6JiIiIiLSE4ZuIiIiISEsYvomIiIiItIThm4iIiIhISxi+iYiIiIi0hOGbiIiIiEhLeJEdomzS1OXrZTI5r5xJRESUxzB8E2WRhZkh5DIZzM2NNNK/TCZFeHgsAzgREVEewvBNlEUmhgYQicV4fWITYsM+qrVvIxsHlGo9CGKxiOGbiIgoD2H4Jsqm2LCPiA15q+syiIiIKBfgAZdERERERFrC8E1EREREpCUM30REREREWsLwTURERESkJQzfRERERERawvBNRERERKQlDN9ERERERFrC8E1EREREpCUM30REREREWsIrXBLlYBKJ5r4fy2RyXrqeiIhIyxi+iXIgPRNzyGQymJsbaew5pDIpIsJjGcCJiIi0iOGbKAfSK2AMsVgM38s78CEyRO39F7aww5BGfSAWixi+iYiItIjhmygH+xAZgsCw97oug4iIiNSEB1wSEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnDNxERERGRljB8ExERERFpCcM3EREREZGWMHwTEREREWkJwzcRERERkZYwfBMRERERaQnD9/+TyWTw8fFBgwYN4OTkhAEDBiAwMFDXZRERERFRHsLw/f/WrVuHvXv3Yt68edi3bx9EIhEGDRqEhIQEXZdGRERERHkEwzeAhIQEbNmyBaNGjUKjRo3g6OiIlStXIiQkBOfOndN1eURERESURzB8A3j27BliYmLg6uoqLDM3N0elSpVw69YtHVZGRERERHmJSC6Xy3VdhK6dPXsWo0aNwj///ANDQ0Nh+ZgxYxAXFwdfX99M9ymXyyGTpT20IhEgFosRGR0HqVSWpbrTY6AvgalxASTGREEuk6q9f7GeAfSMTBAV+xVJau5fTyyBuZEZZDIZsvPuzM1jrMnxBdQzxrl5fAG+hwG+hwHNjjHfw3wPpyc3jHFufg8DGY+xWCyCSCRS+/NmWJfWnzEHio2NBQAYGBgoLC9QoAAiIyOz1KdIJIJEkvEf1MLUMMM22aFvYq7R/s2NzDTWt1isnh0zuXmMNTm+gHrGODePL8D3MMD3MKDZMeZ7mO/h9OSGMc7N72FAfWOsLjmrGh1J2dr948GV8fHxMDIy0kVJRERERJQHMXwDcHBwAACEhoYqLA8NDYW9vb0uSiIiIiKiPIjhG4CjoyNMTU1x48YNYVlUVBSePHmC2rVr67AyIiIiIspLOOcbyXO9e/XqhWXLlsHa2hpFihTB0qVLYW9vD09PT12XR0RERER5BMP3/xs9ejSSkpIwY8YMxMXFwdnZGX5+fkoHYRIRERERZRVPNUhEREREpCWc801EREREpCUM30REREREWsLwTURERESkJQzfRERERERawvBNRERERKQlDN9ERERERFrC8E1EREREpCUM30RaEBERgaSkJF2XkadxjImIKDdg+CYkJSXh8ePHCA4O1nUpud6NGzcwevRohIaGAgBCQ0PRvXt31K1bF87Ozli3bp2OK8z9OMaalZiYiEuXLiE2NlZYtnfvXgwdOhQzZszAy5cvdVgdkeqeP3+OhIQE4fbVq1cxb948rF+/Hl++fNFhZXkTs4TqGL7zmSNHjqBjx4748OEDAODly5do1qwZOnfuDA8PD0yfPh1SqVTHVeZON27cwIABA4RQCABTp07F06dP8euvv2LOnDnYs2cPDh8+rMMqczeOsWaFhYWhXbt2GD58uPA/Yt26dZgzZw7Cw8Px4cMHdO3aFS9evNBxpURpi4mJQd++fdGuXTu8e/cOAHDgwAEMHjwY58+fx5EjR9CuXTvhPU6ZxyyRPQzf+ciZM2cwdepUlCpVCoaGhgCAKVOmIDo6Gr6+vti5cyfu3LmDHTt26LjS3Gnjxo3o1q0b9u7dC1tbW7x9+xZ//vknunfvjh49eqBt27YYP3489uzZo+tScy2OsWatXbsWBgYGCAgIQJkyZRATE4ONGzeiTp062LdvH7Zs2YIuXbrAx8dH16XmSV++fMHZs2dx584dXZeSq/n6+uL9+/fYtGkTSpUqhYSEBCxduhSVKlXCuXPncObMGbi6umL16tW6LjVXYpbIPobvfGTnzp0YOXIkli9fDmtrazx//hwPHz5Er1690LBhQ9SqVQu//PILtxpm0cOHD9GtWzfh9l9//QWRSARPT09hWbVq1bjbPhs4xpr1xx9/YNKkSShVqhQA4Pr164iLi0PXrl2FNi1atMCtW7d0VWKesXbtWtSpUweBgYEAgLt376JZs2YYPXo0evbsif79+yMuLk7HVeZOKeHQzc0NYrEYN27cQFRUFHr27Al9fX0AQLdu3XD16lUdV5o7MUtkH8N3PvLs2TO0aNFCuH39+nWIRCI0btxYWFaxYkW8fftWF+XlerGxsTAzMxNu3759G4aGhnBychKWSSQSiEQiXZSXJ3CMNSs0NFQI3kDy+IpEIri6ugrLbG1tER0drYvy8ox9+/bB19cX3bp1g42NDQBg2rRpMDY2xsmTJ3H58mXExMTA19dXx5XmTh8/fkTFihWF27du3YJIJEL9+vWFZYULF0ZkZKQuysv1mCWyj+E7H0lMTISBgYFw+86dOzA1NUWVKlWEZUlJScKWAcqcokWL4r///gMASKVS/PXXX3B2dlYYz7///htFixbVVYm5HsdYs8zNzREeHi7c/vvvv1GuXDlYW1sLy16/fq1wmzLvwIEDmDJlCsaNGwdTU1M8ePAAb968QZ8+fVCmTBnY2dlh2LBhCAgI0HWpuZKRkRFiYmKE2zdv3kTx4sVhZ2cnLPvw4QMsLCx0UV6uxyyRfQzf+UipUqXw6NEjAEBcXBz++usv1K1bV2Er4aVLl1CyZEkdVZi7tW7dGgsXLsT58+cxd+5cfPnyBZ06dRLuf/DgAdasWYPmzZvrsMrcjWOsWXXr1sXOnTsBJB/c+uzZMzRr1ky4XyaTYdOmTahdu7auSswTXr58iXr16gm3//77b4hEIjRq1EhYVrZsWR4QmEU1atTA0aNHAQD//fcf/vnnHzRp0kShza5duxT2mJHqmCWyT0/XBZD2dOrUCfPnz0dISAj+/vtvREdHo0ePHgCSv8leuHAB69evxy+//KLbQnOpQYMGITAwEKNGjYJYLEbv3r2FELh48WJs3boVLi4u+Pnnn3Vcae7FMdasUaNGoUePHnBxcUFMTAyKFi2Kvn37AgBOnz6N9evX4/3799i/f7+OK839vg8qd+7cgbW1NcqVKycsi4mJgZGRkS5Ky/WGDx+OPn364Nq1awgKCoK5uTn69esHIPlL5ZYtW/Dnn39i165dui00l2KWyD6RXC6X67oI0h5vb2/4+/tDLBZj8ODBwj+kuXPnYs+ePWjXrh0WLlwIsZg7RbIqZT6sqampsOzWrVv4+vUrGjduzPnIasAx1pywsDCcPn0aIpEIrVq1EnbNb968Gf/88w9GjBgBR0dHHVeZu3Xv3h2dO3dG586dERUVhYYNG6J58+ZYvHix0GblypW4c+cOA2IW/ffffzh8+DDEYjG6deuG4sWLAwCWLVuGv/76C2PHjkWDBg10XGXuxSyRPQzfBAD4999/AQAVKlTQcSVERHnb8ePH8euvv6Jz5864d+8enjx5gv3796NKlSoIDQ3F8ePHsXLlSsyfPx/t2rXTdblEKmOWUA2/khCA5BUlZWUJCwvTcTW506BBg/D161eFZZcvX1Y4XVhYWBjnGWYDx1izAgICFK4ImJro6GjMnj1bOwXlUW3atMH06dNx9+5diEQirFq1SjhYbePGjVi5ciUGDRrE4J1FDx48yPACL7Gxsdi0aZOWKso/mCVUw/Cdj3h5eSEiIkJhmb+/v8Jpwz5//gw3NzctV5Y3XLt2TSm4jB07Fp8+fRJuy+VyxMfHa7u0PINjrFnjx49X+nLj7u6OoKAg4XZcXBz27dun7dLynM6dO+PQoUM4cOCAwkGtgwYNwtWrVzFmzBgdVpe7devWTemzrkePHggJCRFux8TEYMWKFVquLG9glsg+hu985NWrV0pbA5YuXapwajEgObxQ5qU2bqkt43zkrOMYa1ZqYxkZGQmZTKaDavInOzs7WFlZISkpCQ8ePNB1OblSau/jZ8+eZbhXh1TDLJF9DN/5HIMLEZF2OTk54cuXLwrLli9frrA1MSIiQuFqrkQ5GbNE5jB8ExERaVF8fLxSWNm9e7fSlB9uOSTKmxi+iYiIdIxbDonyD15kh0iN7t27p3DJYrlcjgcPHiA4OBhA8vxZyh6OseaIRCKlwMcASLlNau9jopyE4TufOXXqlMKFSWQyGc6dOwdra2sAUNrtSZkzatQopS1Y48ePV7jND4Xs4RhrjlwuR6dOnRQujBEbG4vevXtDIpEAAA++pBxPLpdjxIgR0NfXF5bFx8djwoQJKFCgAIDkKzFS1jFLZA/Ddz4zb948pWVLlizRQSV5z4ULF3RdQp7HMdaskSNH6roEomzr0KGD0rIiRYooLStZsqQWqsmbmCWyh1e4JCIi0iJHR0cMHDgQRkZGwjJfX190795dmFL17ds3bN26FU+fPtVVmUSkIQzfpCAyMhJPnjxB3bp1dV1KrnPr1i2V2zo7O2uwkryLY6x7Dx48wOLFi7F7925dl5JreXh4qNz24sWLGqyESDOYJdLH8E0Krl69isGDB3NrSxY4OjpCJBJleHowkUjE8c0ijrHu8X8E5XR9+vRRue2OHTs0WEn+xf8T6eOcbyI14XxkzeMYU34SFhYGGxsbXZeR66Q2v5soJ2H4JlITVf/h82wRWccxprzAy8sLe/bsgaWlpbDM398fbdq0Ec4g8fnzZzRo0IBbDrNg4cKFui6BKF28yA6RFl29ehWVK1fWdRl5GseYcrpXr15BKpUqLFu6dCnCw8MVlnFWqOYEBgbC29tb12VQPsUt30REBAA4cuRIhm3+/fdfzReSD/EKl9r19u1bbNiwAWPGjNF1KZQPMXznIx4eHhn+M4+Li9NSNUSU00yZMkWldgyFRPkXs0T2MXznIx06dOCHJhGl6dmzZ7ougYhyOGaJ7GP4zkdGjRql6xKIKBd4/vw5ChQogBIlSui6FCLKYZglso/hO585f/48jh07Bn19fbRs2RJNmzbVdUl5xtSpUzNsExISooVK8i6OsWYFBwdj6NChwrzuihUrwtvbG8WKFdNxZXnPqVOnhDObAMln6Dl37hysra0BAF+/ftVVabnehw8fMmwTFhamhUryLmaJ7OFFdvKRAwcOYObMmShZsiQkEglevXqFiRMnYsCAAbouLU/o3bu3ym137typwUryLo6xZo0bNw6PHz/GqFGjIBaLsX79ehQsWBBbt27VdWl5iqOjo0rteLGorEm5GFd65HI5xzeLmCWyj+E7H2nfvj0aN24sHN29ceNG7NixA9euXdNxZUSUE7i5ucHb2xu1atUCADx9+hRdunTB3bt3YWBgoOPqiFRz8+ZNldu6uLhosJK8iVki+xi+85EaNWrg+PHjKFq0KAAgJiYGtWrVwl9//SXs6iSi/Kty5cq4dOkSbG1tASRvHaxatSrOnTsHBwcHHVeX/zx+/JjnrKcch1ki+zjnOx+JjY2FkZGRcNvExARGRkb49u0bVxg16NOnj8ptd+zYocFK8i6OsWZJpVJIJBLhtkgkgr6+PpKSknRYVd704MEDnDp1ChKJBK1bt1aYihIfH49Vq1Zh586dePTokQ6rzJ1u3bqlcltnZ2cNVpI3MUtkH8M38SpqaqLqpc8p6zjGlBecOXMGY8eOhYGBAfT09LBt2zZs3boVzs7OuHfvHiZNmoR3796hY8eOui41V+rduzdEIlGGn22c861ezBKqY/jOR0QiEc/NqUELFy7UdQl5HsdY8+7duwcLCwvhtlwux4MHDxAcHKzQjlsMs27jxo1o2rQpli1bBrFYjEWLFmHVqlUYMGAAxowZA3t7e2zduhV169bVdam50oULF3RdQp7GLJF9nPOdjzg6OqJGjRrQ19cXlt2+fRtVq1ZFgQIFFNpylz1R/pNylghuMdSsmjVrYvfu3ahYsSIAICoqCvXq1YOZmRkaN26MGTNmwNjYWMdVEqWOWSL7uOU7H+nQoYPSMu7GV58mTZqo3JZbZrKGY6xZHDPt+PbtGwoVKiTcNjc3h56eHry8vDBz5kwdVpY3HDlyROW27du311gdeRWzRPYxfOcj3GWvWUFBQRCJRKhduzZcXFy4W04DOMaaxQ9Q7fnxvSsSidC1a1cdVZO3TJkyRRjf9PbiiEQihu8sYJbIPoZvIjXZt28fAgICcPr0aQQGBqJFixZo1aoVnJycdF1ansEx1qw1a9akulxfXx8WFhaoWrUqT32nQZxqoh7169fHzZs3Ub16dbRq1QrNmzeHlZWVrssiEnDOdz6S1lW/JBIJLC0tUaVKFQwfPhzVqlXTQXV5y+3btxEQEICzZ8/C0NAQXl5e8PLyUvnKdpQxjrH6eXh4pLpcLpcjMjISsbGxaNy4MXx8fKCnx203WeXo6Ig1a9YoHNg6aNAgzJ8/XzjHegoe2Jo1EREROHv2LAICAnDv3j04OzujdevW8PT0hImJia7Ly9WYJbKP4TsfOXz4cKorjEwmQ0REBG7duoXr169j586dXGnURCaT4caNGzh16hTOnj0La2trtGrVCiNGjNB1aXkGx1h7Hj16hPHjx6Nt27Yc32zgga3a9fnzZ5w5cwYBAQF49OgRGjRoAC8vL3h4eMDQ0FDX5eU6zBLZx/BNCubNm4f3799jw4YNui4lT3nz5g0CAgKwZcsWxMTE8ANVAzjG2nHq1Cn4+Pjg1KlTui4l1woKClK5Lefhq1dISAiOHTuGjRs3QiqV4u7du7ouKU9ilkgf9xuSgnbt2mHIkCG6LiNPePPmDU6fPo1Tp07h+fPncHR0xKBBg+Dl5aXr0vIMjrH2VapUCR8/ftR1GbkaA7X2JSQk4MqVKzh16hT++OMPiEQiNG3aVNdl5VnMEulj+CYFNjY2iI6O1nUZuVZKGAwICMDz589Rrlw5tGzZEt7e3ihZsqSuy8sTOMa6JZVKlc7lS5nDy59rx/eB+9KlSwCAxo0bY/HixWjYsCEMDAx0XGHexSyRPoZvUhAYGKhw/llSXbt27fD8+XOULVsWzZs3x6pVq1C6dGldl5WncIx179y5cyhfvryuy8jVePlzzTp//rywhVsmk8Hd3R2LFi1Co0aN+MVRS5gl0sc53yT48uULhg4diqpVq/JCD1ng6OgIPT092NraZnj+aV7MJGs4xpqV1hZZmUyGr1+/4tatW9izZw9WrlzJXfbZwDnfmuXo6Ah9fX3Uq1cP7u7uMDIySrMtz/OtfswSGeOW73ykT58+qS6Xy+WIiorCq1evULJkSYwePVrLleUNI0eO1HUJeR7HWLMy2iJbrlw5LFiwgME7mz58+IAaNWrwdI0alJiYiMuXL+Py5ctptuFFdrKGWSL7uOU7H5k6dWqqy/X09IQLaHh4eEBfX1/LleUv7969Q7FixXRdRp7GMc6atLbI6unpwdLSkrvs1aRixYq4du0abGxsdF0KUaYxS2QfwzeRFshkMly8eBH+/v64fv06njx5ouuS8hyOMeUWjo6O+PPPPxm+dejevXvYt28fFi1apOtSKB/iPq986vXr17h79y6+fPkCa2trVK9eHWXKlNF1WXlOSEgI9u/fj4MHDyI0NBSmpqbo37+/rsvKUzjG6nf//n3s3LlT+B9hZWWFGjVqoFevXqhVq5auy8sTMjpmgdQvJiYGx44dw969e/Hvv//CyMiI4TubmCWyhlu+85lPnz5h+vTpuHr1qsK8TpFIhHr16mHBggWws7PTYYV5w9WrV7F3715cvnwZSUlJEIlEGDZsGAYOHMhLG6sJx1gztm3bhiVLlqBYsWKoU6cOrKysEBUVhZs3b+L169f45ZdfMHjwYF2Xmas5OjrCy8tLpWk8Cxcu1EJFeduzZ8/g7++PEydO4Nu3b7C2tsZPP/2En376CVZWVrouL1dilsgehu985Nu3b+jSpQuSkpIwYsQI1K1bV/hg/fvvv7FmzRpIpVIcPnyY4SULvnz5gkOHDmH//v149+4dbG1t4eXlBS8vL/To0QNHjx5F2bJldV1mrsYx1qzbt2+jX79+mD59Onr06KF0/4EDBzBnzhxs2bIFLi4uOqgwb3B0dET16tVVmhO7c+dOLVSU9yQkJCAgIAD+/v548OABJBIJ6tWrh2vXruHIkSM8XWY2MEtkH6ed5CPbt28HAKUVwtraGl5eXmjYsCF69OiBrVu38qwSWeDu7g4bGxs0adIEzZs3R+3atblrWc04xpq1detW9OzZM9XgDQBdunTB69evsW3bNobvbFq7di3nfGvIov9r787DakwfPoB/T4sspVPImp1JCVEoexmGItUQsg1jxhKzWCZDfhhke42xJX5jKXpbLJFdlpRIlmEs2U2RNEqpLC3nvH/MNeedMy1SOs855/l+rst1eZ7nlm/nmsn3POd+7nvZMuzbtw/Z2dmwtbXFggUL0L9/f0ilUlhZWUFHR0foiBqNXaLi+F+giBw6dAjTpk0r8Z2ooaEhpk+fjqNHj6o4mXYwNTVFZmYm/vjjD9y8eROpqalCR9I6fI0r17Vr19679NrgwYNx7do11QTSUnzDWLm2b9+OWrVqYf369di+fTs8PT0hlUqFjqU12CUqjuVbRJ48eYK2bduWOsbKyuqDNoCg/3f69GmsX78eRkZGWL16NRwdHTFixAgEBgYKHU1r8DWuXK9evXpvSalZsyZev36tmkBairM9K9eiRYtQs2ZNTJkyBfb29pg7dy7i4uJQWFgodDStwC5RcSzfImJgYICcnJxSx7x69YpztMpJIpGgW7duWL16NWJjYzFv3jzk5eVh6dKlKCwsxLJly3D+/HmhY2o0vsaVq0GDBrh582apY27duoVGjRqpKJF28vPzg5GRkdAxtNawYcMQEhKCQ4cO4fPPP8fZs2cxYcIEdO/eHTKZDMnJyUJH1GjsEhXH8i0i1tbWOHLkSKljIiMj0a5dOxUl0l41a9aEl5cX9uzZg/3792PMmDG4desWvvjiCwwcOFDoeFqBr/HH9+mnn2LDhg3Iy8sr9vrr16+xbt06fPbZZypOpl1atGgBXV3dUse8efMGW7ZsUVEi7dSiRQvMmjUL0dHR2LhxIzp16gRdXV1MmTIFI0aMwOHDh4WOqJHYJT4COYlGTEyM3MrKSn706NFir+/du1fetm1beUJCgoqTaYeoqCh5Xl5eidfz8/Plx44dk3/99dcqTKVd+BpXrqysLLmTk5Pc3d1dHhUVJU9PT5fLZDJ5VlaW/MSJE3IXFxe5s7OzPDc3V+ioGs3CwkL+4sULpXPDhw+Xp6amKo7//PNPuYWFhaqjab2MjAz5tm3b5C4uLnx9y4ldouK41KDI+Pv745dffoGFhQU6duwIqVSK7OxsXLx4Effv38esWbMwbtw4oWNqpOK2jPb394eXlxdq1qwpYDLtwde48qWmpmL27Nm4ePGi0oOBcrkcPXr0wJIlS2BmZiZgQs1X3A6XNjY2OHDgAMzNzQEAL168QI8ePXD79m2hYmosNzc3bN++HcbGxopzcrm8yIOuN2/ehJWVlarjaQV2iYrhUoMiM3nyZHTq1AlBQUE4fvw4MjMzIZVKFcsx2djYCB1RYxX3PnbLli1wcXFhMfxI+BpXvnr16iEwMBB3797F1atXlX5GcOc60gS3b99GQUGB0rlOnTph//79ijc3AFi8K4BdomJYvkWoc+fOXKNXRfjBUuXja1w5WrdurbQRSUnzwIk0AX9OfHzsEuXHBy5F6OrVq3j79q3SuaNHjyIhIUGgRESkLu7du4cJEyYgKSlJ6fwPP/yAMWPG4NGjRwIlIyJ1wi5RfizfIiKXyzFv3jyMHDkSv/32m9K1ffv2YcyYMfjpp5+ECUdEgvvjjz8watQopKWlFbnT7eTkhMzMTIwcORJPnjwRKKF2kEgk3GiHNBa7RMVx2omIhIWF4dChQ1i+fHmRj4o2bdqEyMhIzJ8/H23btoWbm5tAKTXbkSNHYGhoqDiWyWQ4ceIETE1Nlca9bxdBKhlf48qzYcMGtG3bFps2bYK+vr7SNRcXF/Tt2xcTJkzAxo0bsXTpUoFSaj65XI6pU6cqvcbv3r3DzJkzYWBgAADIz88XKp7GK+7NDd/sfDzsEhXH1U5ExN3dHUOHDsWIESNKHLN582acOHEC4eHhKkymHSwsLMo0TiKRcAWDcuJrXLl69+6N1atXo2PHjiWOiYuLw7x583Dq1CkVJtMuPj4+ZS6Dfn5+lZxG+1hYWKB+/frQ0fn/D/dTUlJQt27dIuurnzx5UtXxNB67RMXxzreIPH78GN26dSt1jJOTEzZv3qyiRNolMTFR6Ahaj69x5Xr58iXq1q1b6pjGjRsjPT1dRYm007Jly9475vXr11izZk3lh9FC3t7eQkfQauwSFcfyLSIGBgZFHo4ozvt2XiMi7VSvXj08fvwYDRs2LHHM48ePUbt2bRWm0j55eXlYsWIFDh48CF1dXbi6umLmzJmKO7WxsbGYP38+UlNT8eOPPwqcVvOwfFcudomK4wOXImJpaYkzZ86UOubkyZNo3ry5agIRkVpxcnKCv79/kTWS/1ZQUICAgID33vWi0q1atQohISFwdHTEp59+ipCQEAQEBEAmk2HRokX48ssvoa+vjx07dggdlagIdomKY/kWkZEjR8Lf3x/R0dHFXj9z5gw2btwIT09PFScjInUwceJEJCcnY/To0Thz5gxevnwJmUyGjIwMnDx5EqNGjcKDBw/w9ddfCx1Vo0VFRWHu3LlYunQpFixYgNWrV2Pv3r1YsGABQkJCMGHCBERGRsLOzk7oqERFsEtUHB+4FJkVK1Zg69atsLS0hI2NDWrWrInMzEz89ttvSExMhKenJxYsWCB0TCISyOPHjzF79mxcv369yPbyHTt2xKJFi9CyZUsBE2o+a2trHD58WLHbYmFhIaytrWFsbIw1a9agS5cuAickKh27RMWwfIvQ2bNnERwcjBs3biArKwumpqawsbHBsGHD4ODgIHQ8jXXlyhV06NBB6Ql7Esbr169RvXp1oWNotJs3byp+RpiYmKBjx47cXv4jsbCwwLlz51CrVi3FORsbGyxcuBCDBw8WMBlR2bFLlB/Lt4ikpaXBzMxM6Bhay8LCAoaGhujSpQu6deuG7t27o3HjxkLH0jpv377FhQsXoKOjg86dO6Nq1apK10+fPo1Fixbh9OnTAiXUXPPnz0fPnj3h4ODANy+VqKTyHRERgSZNmgiYjOj92CUqjqudiMiAAQNgbm6OXr16oVevXrxL+5GFh4fj8uXLSEhIwNq1a/HTTz+hYcOGcHBwQPfu3WFvbw8jIyOhY2q0xMREfPnll0hPT4dcLkfDhg0RFBSEBg0aICsrC4sWLcKhQ4d4h7acGjVqhG3btmHWrFno0KEDevXqhZ49e/LBqUpQ3Drf/Hn88Tx48ADr16+Hn58fqlatChsbG6UVOuzt7bF161YBE2oudomK451vEcnPz8elS5dw9uxZREdHIz09Hd26dUPPnj3Rs2fPIjsEUsXcvXsXCQkJuHz5Mi5duoSMjAy0bdsW3bt351JY5fTll18iLS0N8+fPR5UqVbBy5UqYmpri22+/xfjx4/Hnn39i4sSJmDx5MqpUqSJ0XI2VnZ2NmJgYnD17FrGxsahatSp69uyJXr16oWvXropdGKl8LCwsMHDgQKXXMTIyEo6OjqhRo4bSWG6y8+EePXqEzz//HC1btsS6detgZmYGGxsbTJ06FbVq1UJKSgrWrVuHgIAA9OrVS+i4GoddouJYvkXs6dOniI6OxtmzZxEfH48WLVoo3sm2a9dO6Hha4/Xr17h8+TKOHz+OgwcP4u3bt9x9sZy6dOmCX375BV27dgUAJCcnw9XVVbEu9cqVK8u8CyaV3e+//46zZ8/i7NmzuHv3LmxtbbFlyxahY2ms0aNHl3lsUFBQJSbRTnPmzEF6ejoCAgIUnzDY2NjgwIEDiodcv/vuOxQWFmLt2rVCRtUK7BIfjuWbAPy16UN8fDyio6MRExODY8eOCR1JY8nlcly/fh0xMTGIiYnBzZs3oa+vrzQXvFmzZkLH1EiWlpY4ffq00i6M1tbW6NSpEzZt2lRk/jd9fBkZGTh37hwGDRokdBSiYvXu3RsrVqxA586dFef+Xb7j4uLwww8/ICYmRqiYWoldomw455tQUFCAe/fuoVWrVujRo4fQcTRWREQEYmJicO7cOWRlZeGTTz5B9+7d8d1336FTp07Q19cXOqLGk8lk0NNT/rGlp6eH6dOns3h/JPn5+YiNjUXXrl1RrVo1AEBISAjOnDmDOnXqYNy4cSzepNZevHhR5GF3d3d3GBoaKo6bNm2KzMxMFSfTbuwSZccZ8iITEREBd3d3pKSkAPjroZR+/frh888/h6OjI+bOnYvCwkKBU2omHx8fXL16FdOnT0dsbCwiIiIwc+ZMdO3alcW7ktWpU0foCFohPT0drq6umDJliuJnxMaNG7Fw4UK8fPkST58+xbBhw3D//n2BkxKVTCqVFinWvr6+MDExURynp6dzbnIFsEtUDMu3iBw7dgxz5sxBs2bNFHcJfXx8kJOTg4CAAAQFBeHy5csIDAwUOKlmcnFxwbt377B06VJMmzYN/v7+uHHjhtCxtIpEIimySkRxq0ZQ+WzYsAFVqlTB4cOH0aJFC+Tm5mLz5s3o0qULQkNDsXXrVgwdOpTzZEmtWVpaIioqqtQxx44dQ/v27VWUSLuwS1Qcp52ISFBQELy9vTF16lQAf63G8fvvv2PKlCno2bMnAODbb7/Fhg0b8MUXXwgZVSOtWrUKwF+bk8TExCA2NhYbNmyAoaGhYq53t27duD5qBcjlcnTr1q3IuX79+hUZy4daP9yZM2ewePFixTMJ58+fx9u3bzFs2DDFmM8++wyTJ08WKiLRew0bNgwzZ85E27Zt0bt37yLXY2NjERgYiICAANWH0wLsEhXH8i0iiYmJWLhwoeL4/PnzkEgk6NOnj+JcmzZtkJSUJEQ8rWFlZQUrKytMmjQJOTk5uHDhAmJjY7F582bMnTsXrVq1wv79+4WOqZG47FrlSktLU3oY+NKlS5BIJIrVZQDAzMwMOTk5QsQjKpO+ffvC3d0dkyZNQteuXeHg4AATExNkZmYiISEBsbGxGDt2LOzt7YWOqpHYJSqO5VtE8vPzldY+vnz5MgwNDdG2bVvFuYKCAs5P/sgMDAxgamqKRo0a4fnz50hPTxc6ksZyc3MTOoJWq1mzJl6+fIn69esDAC5cuIBWrVopzY199OgR58qS2ps/fz7s7OwQFBSENWvWQCaTQSKRwNraGqtWrcLAgQOFjqix2CUqjuVbRJo1a4YbN27A3Nwcb9++RVxcHBwcHJTmzJ4+fRpNmzYVLqSGS05OxpUrV3DlyhVcvXoV9+/fR7Vq1WBra4tu3bph5syZ+OSTT4SOqbEOHz6Mvn37lrqBTk5ODlatWoUFCxaoLpiWsLe3R1BQEPz8/BAfH4/ExESlDaFkMhm2bNkCW1tbAVMSlc2AAQMwYMAAFBYWIiMjA1KplIXwI2CXqDiWbxHx8PDAkiVL8Pz5c1y4cAE5OTkYMWIEgL/eyZ48eRL+/v749ttvhQ2qobp374709HTo6uqiXbt26NevH/7zn/+gffv2RZbHo/KZMWMGYmNjUatWLcW53r17Y9euXYqNdt6+fYvQ0FCW73KYNm0aRowYgc6dOyM3NxeNGjXC2LFjAQBHjx6Fv78/njx5grCwMIGTEpWdrq4uV0T6iNglKo6NQERGjx6NjIwMbNq0CTo6OvDx8VHMefPz80NwcDBcXV3h5eUlcFLN5OzsDAcHB9jZ2aF69epCx9FKxe0JlpWVBZlMJkAa7dO0aVMcPHgQR48ehUQigbOzM4yMjAAAT548QePGjbF8+XK0aNFC4KREJXN0dCzTKkgSieS9q6JQUewSFccdLgkAcOfOHQDglIgKSE9PV7ojW5y8vDxERUVxvmE5WVhY4Ny5c0qv8793rnvx4gV69OjB1U6IRGrdunWllu8DBw4gKSkJDRo0wKlTp1SYTPuxS5QN73wTAOX/UcpSIqmo7t27F5kSMWPGDPz444+Kc69evcKMGTNYvkktcU49aYNp06YVez4lJQXz5s1DUlIShg4dih9++EHFybQfu0TZcJMdERk4cGCRXb/+93//V2nZsBcvXqB79+4qTqYdivsQ6dSpU3j9+vV7xxGpgxkzZiA7O1vpXO/evfH06VPF8d9z6ok0SVhYGAYPHoyHDx9iy5Yt+Omnn5S2m6eyY5eoOJZvEXn48GGR7V5XrlyJly9fKp1jOaxc3JGx/LjDZeXinHrSNqmpqZgwYQLmz5+P/v374+DBg+jRo4fQsTQau0TFcdqJyBX3PwfLDKkruVwODw8P6Oj8/32DN2/eYPTo0dDV1QUAFkUiAgCEh4dj2bJlMDIywpYtW1i6KxG7xIdh+SYijfHPNaeJiIqTmpqKuXPnIi4uDh4eHvDx8eEUE1IrLN9EHxHf6Vculm8ieh9nZ2e8fv0a5ubmKCwsxJIlS0oc6+fnp8JkRH9h+Sb6iBYvXgwDAwPFcX5+PlauXIkaNWoAAN69eydUNK3z/PlzJCYmIjs7G0ZGRmjTpg3MzMyEjqXROKeetIGlpaXi90+ePBEwCVHxWL5F5siRI0ofv8lkMpw4cQKmpqYAUGSlAyo7Ozs7/Pnnn0rnbGxs8PLlS6UHUbg1d8XcuXMHixcvxqVLl5TmGUokEnTp0gVz585Fq1atBEyouTinnrRBUFCQ0BG0HrtExXCTHRGxsLAo89jExMRKTEJUPvfu3cPw4cPRpEkTeHl5oXXr1qhZsyays7Nx48YNhIaGIikpCbt370azZs2Ejqtx1q9fX+axnAJEJE7sEhXH8k1EGsPb2xv5+fnYsGED9PSKfnAnk8ng7e0NqVSKpUuXCpCQiIRW0vbyenp6kEqlsLa2xrhx49CoUSMB0hFx2gn9S1ZWFm7dugV7e3uho2icMWPGlGmcRCLBjh07KjmNdrp8+TI2btxYbPEGAB0dHYwfPx4+Pj4qTiYe169fx/Lly7Fr1y6hoxAVy83NrdjyLZPJkJmZiYsXL+LAgQMIDQ3lJ2SVhF2idCzfpOT69ev46quvcPv2baGjaJyGDRuWev3SpUtITk7mklcV8OrVK9SvX7/UMY0aNUJaWpqKEolPVlYWrly5InQMohKVtL38P33//fdYt24dVq9erYJE4sMuUTqWb6KPpKQlq3JycrBs2TIkJyfDwcEBixcvVnEy7VFYWAh9ff1Sx+jp6SE/P19FiYhIE40aNQrTp08XOgaJFMs3USU6d+4cfH198erVKyxcuBCenp5CR9JoxS2FR0T0oerVq4esrCyhY5BIsXwTVYLc3FwsW7YM4eHhsLe3x5IlS9CgQQOhY2k8uVyOqVOnlnr3m3e9ieh9UlNTFcviEakayzfRR/b33e6srCwsWLAAw4cPFzqS1nBzcyvTuKZNm1ZuEC0VERHx3jF37typ/CBElSgvLw+bNm3iw4AkGC41KCIlLb/0T2/fvkVGRgYfkiiH3NxcLF++XOlu9/seDiRSJ2Vdv1cikfBnBKmtOXPmFHteLpfj1atXuH79OiQSCcLCwvgzuhzYJSqOd75FpKTll+jjGDRoEJ49ewZzc3N07NgRe/bsKXEsNyipPFwKr/y4IQZpg5K2lNfX14exsTHGjx8PDw8PGBsbqziZdmCXqDje+Sb6SBwdHcs0TiKR4OTJk5WcRrxiYmK4xBUREakt3vkWoezsbBgZGQEADh48iIKCAsW1Vq1awcrKSqhoGu3UqVNCRyCqsIyMDGzduhXffPMN9PX1MWjQILx+/Vpx3cHBAT/99JOACYnKLicnBzdu3EBGRgZMTU1hZWWl+PePKoZdovxYvkVm48aN2LRpE44dO4b69evD19cXb968UVyvXbs2jh49yo1giEQoLS0NHh4e0NfXh5eXF+rXr48nT57Aw8MDUqkUKSkp2L17N4YMGYJOnToJHZeoRG/evMGKFSuwd+9evHv3TnHewMAArq6u8PHxQfXq1QVMqNnYJSqG5VtEDh8+DH9/f/j4+KB27dqK8ydOnIC5uTmePXsGV1dXhIWFYfz48QImJSIhBAQEoGHDhti+fTuqVq2qOD927FiYm5sDAJ4/f47Q0FCWb1JbBQUFGD9+PB4+fIhJkybB3t4eJiYmyMrKwoULF7Bjxw4kJiYiODgYenqsQR+KXaLi+F+diISEhGDKlCnw8vJSnPvnQxP169fHuHHjcPz4cf4PQ2qJS+FVrrNnz8LX11epeP+bl5cXd2kltRYcHIxnz57hwIEDqFu3rtK1du3awdXVFSNGjMDOnTsxbtw4YUJqMHaJimP5FpHbt2/D19dX6dy/n7d1cnLC1q1bVRmLqMx8fHzKNI5P4pdPamoqWrdurXSuS5cuSmX8k08+wZ9//qnqaERlFhERgenTpxcp3n+rW7cupk+fjsDAQJbvcmCXqDiWbxHJy8srMv9q27ZtSj+gatSogcLCQlVHIyoTLoVXuQwNDZGbm6t0btOmTUrH2dnZXKKN1Nrjx49ha2tb6hhbW1ssWrRIRYm0C7tExekIHYBUx8zMDI8fP1Y616FDB1SpUkVxfP/+fW6DThojOTkZ169fR3JycpE7L/ThWrZsiZiYmFLHREdHw9LSUkWJiD6cjo4O8vPzSx3z7t07pX/7qOzYJSqO5VtEevTogR07dpQ6JjAwEL1791ZNIKJykMvl+O9//4tevXqhX79+8PT0RL9+/dCzZ08EBARAJpMJHVFjubm5wd/fv8RPGO7cuYMtW7bAw8NDxcmIyq5NmzY4ffp0qWNOnjzJN5HlxC5RcdxkR0SSk5MxZMgQ9OjRAz4+PqhXr57i2osXL7BixQpER0cjMjISZmZmAiYlKtm0adNw5swZuLq6FlnFYP/+/ejatWuRqRJUdpMmTUJsbCyGDBkCe3t7mJqa4uXLl0hISEBERAT69OmD1atXCx2TqESHDh2Cr68vtm3bhvbt2xe5fuHCBUyePBmrVq2Ck5OTAAk1G7tExbF8i8z58+cxa9YspKeno0mTJjA1NUVmZib++OMPmJqa4ueff37vXDkioURERGDp0qUIDAyEhYVFkeuJiYkYO3YsZs+ezbuz5SSTybB161YEBwcjJSVFcb5OnToYPXo0Jk6cyAdaSe35+vpi37596NWrFzp27AipVIrs7GxcvHgR0dHRGDlyJObOnSt0TI3FLlExLN8ilJOTgyNHjuDSpUt48eIFTExM0KlTJ7i4uHDnL1JrI0aMgLOzM0aNGlXimF27duHQoUMIDg5WYTLtlJycjPT0dJiYmMDc3Bw6OpypSJojIiICgYGBSExMVExHs7a2xhdffIGBAwcKnE7zsUuUH8s3EWkMOzs7hIWFoVmzZiWOSUpKgoeHBxISElSYjIjU1bt375CVlQWpVMqHLEktcKlBEfmQMmJnZ1eJSYjKp6CgALq6uu8dx2kR5TNmzJgyjZNIJO994IpIKDNmzMDChQsVy+EZGBhw7vFHxC5RcSzfIjJ69GhIJJISl2T7Z2G5ffu2qmIRlVnLli0RFxeHxo0blzgmJiYGLVq0UGEq7dGwYcNSr1+6dAnJyclF1vglUiexsbFwdnaGn58fHBwchI6jddglKo7lW0ROnjxZ4rXHjx9j4cKFSE5OLnU+LZGQ3NzcsG7dOnTr1g3m5uZFrt+/fx/r16/H7NmzBUin+fz8/Io9n5OTg2XLliE5ORkODg7cXp7U2pEjR7Bw4UJMmDABXl5emDVrFgwMDISOpTXYJSqOc74JO3bswJo1a2BmZoYlS5bwCWVSWzKZDJMmTcLVq1fh7u4OGxsbSKVS5OTkID4+Hrt370aPHj2wdu1aoaNqjXPnzsHX1xevXr3CrFmz4OnpKXQkojI5ceIEFi1ahBo1amDFihVo166d0JG0GrtE2bF8i9gff/yBH3/8EVeuXIGXlxdmzpyJqlWrCh2LqFSFhYXw9/fHrl278PLlS8X52rVrY+zYsZgwYQJX5fgIcnNzsWzZMoSHh8Pe3h5LlizhjnWkcXJycrB27VqEhITAycmpyL9xJX3aQ2XHLvHhOO1EpP5+h1q7dm0EBQXxHSppDF1dXXh7e8Pb2xuPHj1CZmYmpFIpmjRpwtL9kfx9tzsrKwsLFizA8OHDhY5EVC55eXnIzs5Gfn4+njx5wlL4kbFLlA/vfItMUlISfHx8cPXqVb5DJSIlubm5WL58udLd7vr16wsdi6hcdu/ejZUrV6JKlSpYsGABd7P8iNglKoblW0QCAwPx888/o06dOli6dCnfoRKREkdHRzx79gzm5uYYPHhwqWO9vb1VlIrowyQlJcHX1xfx8fFwcXGBr68vjI2NhY6lNdglKo7lW0T+uR33+9ZB5vJAROLj6OhYpnESiaTUFQ+IhNS+fXsYGRlh0aJFZf5vmsqOXaLiOOdbRPhgCRGV5tSpU0JHIKqw/v37Y968eahZs6bQUbQSu0TF8c43EREREZGK8M63iKSkpJR5LJcUIxKfOXPmlHks734RiRO7RMWxfIuIo6Pje+dnyeVySCQSztMiEqEnT54IHYGI1By7RMVx2omIXLx4scxjO3fuXIlJiIiISBOxS1QcyzcREb1XZmYmDA0NoafHD0yJiCqC28GJ0N27d5GXl6c4jomJweLFi+Hv74+MjAwBkxGR0OLj4zF9+nSkpaUBANLS0jB8+HDY29vDzs4OGzduFDghEakDdonyY/kWkdzcXIwdOxaurq5ITk4GAISHh+Orr75CVFQUIiIi4Orq+kEPUxCR9oiPj8f48eMVxRv46yHM27dvY/78+Vi4cCGCg4Oxd+9eAVMSkZDYJSqO5VtEAgIC8OTJE2zZsgXNmjVDXl4eVq5cCUtLS5w4cQLHjh1D165dsW7dOqGjEpEANm/eDE9PT4SEhMDMzAxJSUk4d+4chg8fjhEjRmDw4MGYMWMGgoODhY5KRAJhl6g4lm8ROXbsGObMmYPu3btDR0cH8fHxePXqFby8vKCvrw8A8PT0RExMjMBJiUgIv//+Ozw9PRXHcXFxkEgk+PTTTxXn2rVrhwcPHggRj4jUALtExbF8i8izZ8/Qpk0bxXFCQgIkEgm6deumONegQQNkZWUJEY+IBPbmzRsYGRkpji9duoSqVauiffv2inO6urrvXWaMiLQXu0TFsXyLSLVq1ZCbm6s4vnjxIho3boy6desqzqWkpMDY2FiIeEQksEaNGuHevXsAgMLCQsTFxcHOzk5xNwsALly4gEaNGgkVkYgExi5RcSzfImJjY4P9+/cDAO7du4dr167ByclJaczOnTuV7nIRkXi4uLjAz88PUVFRWLRoETIyMuDh4aG4fv36daxfvx79+/cXMCURCYldouK4zreIXL9+HWPGjEGTJk3w9OlT6OrqIjIyEmZmZoiPj8fWrVtx7tw57Ny5Ex06dBA6LhGpWF5eHubNm4fIyEjo6Ohg5MiRmDt3LgBg+fLl2LZtGzp37owtW7bAwMBA4LREJAR2iYpj+RaZe/fuYe/evdDR0YGnpycaN24MAFi1ahXi4uLw3XffoUePHgKnJCIh5eTkAAAMDQ0V5xISEpCdnY0+ffpwzjeRyLFLVAzLNxERERGRinDONxERERGRirB8ExERERGpCMs3EREREZGKsHwTEdEHef36tdARiIg0Fss3KSkoKMD169eFjkFEAnn79i3OnDmDs2fP4u3bt0Wunz59Gs7OzgIkIyLSDizfItK+fXtkZGQonfuf//kfZGZmKo4zMzPh6emp4mREpA4SExPRt29fTJ48GV999RWcnZ2RkpICAMjKysKMGTMwefJkVK9eXeCkRCSkBw8e4LvvvlO8QbexsUGbNm0Uv8aPHy9wQvXG8i0i7969w79Xlty1axeys7OVznH1SSJxWrVqFUxNTREUFISwsDA0aNAAy5cvx6NHjzBkyBAcO3YMkydPxr59+4SOSkQCefToEYYNG4aUlBS8evVKcX7GjBlYunQpvL29ERcXh+joaAFTqjc9oQOQsIor2txAg0icfv/9d/zyyy+wtbUFACxduhSurq54+PAhDA0N4e/vDwsLC4FTEpGQNm/ejE6dOiEgIECpL/Tv3x/m5uYAgPv372PPnj3o1auXUDHVGu98ExERACA7OxvNmjVTHJubmyM/Px+1atVCeHg4izcR4fz58/jyyy9LvVE3dOhQXL16VYWpNAvLNxERAQBkMhn09JQ/ENXT08P06dNRtWpVgVIRkTp58eKFYjv5v7m7u8PQ0FBx3LRpU6XnyUgZyzcREZWqTp06QkcgIjUhlUqLFGtfX1+YmJgojtPT02FqaqriZJqDc75FZuvWrahWrZriuKCgAIGBgTA2NgbA9XuJxEwikRT5KJnPgBDRP1laWiIqKqrUaWjHjh1D+/btVZhKs0jkXNpCNBwdHcs89tSpU5WYhIjUkYWFRZGyLZfLiy3gt2/fVlUsIlIjUVFRmDlzJtasWYPevXsXuR4bG4spU6YgICAA9vb2qg+oAXjnW0RYqImoNH5+fkJHICI117dvX7i7u2PSpEno2rUrHBwcYGJigszMTCQkJCA2NhZjx45l8S4F73wTERER0Qc5cuQIgoKC8Ntvv0Emk0EikcDa2hrjxo3DwIEDhY6n1li+RSYjIwNbt27FN998A319fQwaNEhpnreDgwN++uknARMSkVAOHz6Mvn37okqVKiWOycnJwapVq7BgwQLVBSMitVVYWIiMjAxIpVLo6+sLHUcjcLUTEUlLS4OrqysOHz6MFy9eAACePHmCPn36wM3NDV26dMHu3btx+fJlgZMSkRBmzJhRZMfb3r174+nTp4rjt2/fIjQ0VNXRiEhN6erqok6dOizeH4BzvkUkICAADRs2xPbt25XW7B07dqxiV6rnz58jNDQUnTp1EiomEQmkuA9Cs7KyIJPJBEhDROrI0dGxTKsgSSQSREVFqSCR5mH5FpGzZ8/C19e31M0yvLy8sHjxYhWmIiIiIk3h5uZWavk+cOAAkpKS0KBBAxWm0iws3yKSmpqK1q1bK53r0qWLUhn/5JNP8Oeff6o6GhEREWmAadOmFXs+JSUF8+bNQ1JSEoYOHYoffvhBxck0B8u3iBgaGiI3N1fp3KZNm5SOs7OzFRvuEBEREb1PWFgYVqxYAUNDQ2zZsgU9evQQOpJa4wOXItKyZUvExMSUOiY6OhqWlpYqSkRE6oQ7XBLRh0hNTcWECRMwf/589O/fHwcPHmTxLgPe+RYRNzc3LF++HF27di12W9g7d+5gy5YtWLJkiQDpiEhocrkcHh4e0NH5//syb968wejRo6GrqwsAfPiSiAAA4eHhWLZsGYyMjHi3+wOxfIuIu7s7jh8/js8//xxDhgyBvb09TE1N8fLlSyQkJCAiIgJ9+vRB//79hY5KRALw9vYWOgIRqbnU1FTMnTsXcXFx8PDwgI+PDwwNDYWOpVG4yY7IyGQybN26FcHBwUhJSVGcr1OnDkaPHo2JEyfyY2YiIiIqVqdOnfD69WuYm5u/d1liPz8/FaXSLCzfIpacnIz09HSYmJjA3Nxc6aNmIhK358+fIzExEdnZ2TAyMkKbNm1gZmYmdCwiEtjo0aPLPDYoKKgSk2gulm9SyM/Px7FjxxASEoKdO3cKHYeIBHDnzh0sXrwYly5dUtp0RyKRoEuXLpg7dy5atWolYEIiIs3G8k1ITk5GaGgo9u7di4yMDNSrVw9nzpwROhYRqdi9e/cwfPhwNGnSBF5eXmjdujVq1qyJ7Oxs3LhxA6GhoUhKSsLu3bvRrFkzoeMSEWkklm+RkslkOHXqFEJCQhAXFwe5XI7WrVvjiy++gIuLC/T0+Cwukdh4e3sjPz8fGzZsKPZngEwmg7e3N6RSKZYuXSpAQiISWknby+vp6UEqlcLa2hrjxo1Do0aNBEinGVi+RSYtLQ1hYWEIDw/H8+fPYWpqiv79+yMsLAz79+9Hy5YthY5IRAKxt7fHxo0bYWNjU+KYS5cuwcfHB1FRUSpMRkTqYt26dcWWb5lMhszMTFy6dAmpqakIDQ3lJ2Ql4O1NEZk2bRpOnz6N6tWrw8nJCc7OzrC3t4euri7CwsKEjkdEAnv16hXq169f6phGjRohLS1NRYmISN2UtL38P33//fdYt24dVq9erYJEmoflW0ROnDiB5s2bY9KkSejevTtMTU2FjkREaqSwsBD6+vqljtHT00N+fr6KEhGRJho1ahSmT58udAy1xfItIr/++iv27t0LX19fFBQUwNbWFi4uLvj000+FjkZEaqC47eWJiD5UvXr1kJWVJXQMtcXyLSLdunVDt27dkJ2djcjISEURX7hwIWQyGS5fvozmzZtzvW8ikZLL5Zg6dWqpd79515uI3ic1NZWfrpeCD1yK3N27d7Fnzx5ERkYiIyMD9evXx4gRI/DVV18JHY2IVGzOnDllHsud64ioOHl5efD29oapqSmWLVsmdBy1xPJNAICCggKcPn0ae/bsQWxsLG7cuCF0JCIiIlIzJb1Jl8vlePXqFa5fvw6JRIKwsLD3PsAtVizfVER6ejpq1aoldAwiUkPXr1/H8uXLsWvXLqGjEJEAStpeXl9fH8bGxrC2toaHhweMjY1VnExzcM63CMXHx+PgwYO4ffs2srOzYWRkBEtLSwwePBi2trYs3kRUoqysLFy5ckXoGEQkkKCgIKEjaDyWbxEpLCzE3LlzERERgQYNGqBVq1Zo2rQpcnJycObMGYSHh2PIkCGcy0lERETvlZOTgxs3biAjIwOmpqawsrKCkZGR0LHUHsu3iGzfvh1RUVFYt25dscsLHj9+HPPmzUNYWBiGDRsmQEIiIiJSd2/evMGKFSuwd+9evHv3TnHewMAArq6u8PHxQfXq1QVMqN5YvkUkIiICM2fOLHFd7379+iEjIwN79uxh+SYiIqIiCgoKMH78eDx8+BCTJk2Cvb09TExMkJWVhQsXLmDHjh1ITExEcHAw9PRYM4vDV0VEkpOT0bVr11LHdOnSBWvWrFFNICJSKxEREe8dc+fOncoPQkRqKzg4GM+ePcOBAwdQt25dpWvt2rWDq6srRowYgZ07d2LcuHHChFRzLN8i8vbtWxgaGpY6xtDQkLtSEYmUj49PmcZxF0wi8YqIiMD06dOLFO+/1a1bF9OnT0dgYCDLdwlYvkXmff9o8h9VIvFKTEwUOgIRqbnHjx/D1ta21DG2trZYtGiRihJpHpZvkbl69Wqpa2/yrjcR/S05ORkvX76EiYkJGjVqxDfnRAQdHR3k5+eXOubdu3eoUqWKihJpHpZvkZk2bRret68S/4ElEi+5XI5ff/0VQUFBSEtLU5yvXbs2Ro0ahYkTJ0JHR0fAhEQkpDZt2uD06dNo0aJFiWNOnjwJS0tLFabSLCzfInLy5EmhIxCRmps+fTrOnDkDV1fXIqsY+Pv74+rVq9i0aZPQMYlIIMOHD4evry/s7OzQvn37Itf//lmxatUqAdJpBpZvEWnYsKHQEYhIjUVERCA+Ph7h4eGwsLBQujZgwACMGDECY8eOxZ49e+Dh4SFQSiISkrOzMy5cuAAvLy/06tULHTt2hFQqRXZ2Ni5evIjo6GiMHDkSTk5OQkdVWxL5++YgkNYoyzJifxsyZEil5SAi9TRixAg4Oztj1KhRJY7ZtWsXDh06hODgYBUmIyJ1ExERgcDAQCQmJkImkwEArK2t8cUXX2DgwIECp1NvLN8i8u87WSWRSCS4fft2JachInVjZ2eHsLAwNGvWrMQxSUlJ8PDwQEJCggqTEZG6evfuHbKysiCVSvmQZRlx2omIcBkxIipNQUEBdHV13zuOD2UTideMGTOwcOFCxb4hBgYGMDMzEziVZuEj60REBABo2bIl4uLiSh0TExNT6ioHRKTdYmNj4ezs/N6fFVQy3vkWkfXr15d5rLe3dyUmISJ15ObmhnXr1qFbt24wNzcvcv3+/ftYv349Zs+eLUA6IlIHR44cwcKFCzFhwgR4eXlh1qxZMDAwEDqWRuGcbxGxsLCAjo4O6tWrV+o4iUTCZQmJREgmk2HSpEm4evUq3N3dYWNjA6lUipycHMTHx2P37t3o0aMH1q5dK3RUIhLYiRMnsGjRItSoUQMrVqxAu3bthI6kMVi+RWT+/Pk4ceIEqlWrBmdnZzg7O5f5IUwiEofCwkL4+/tj165dePnypeJ87dq1MXbsWEyYMIGb7BARACAnJwdr165FSEgInJycULVqVaXrfn5+AiVTbyzfIlNYWIgLFy7g8OHDiIqKgqmpKVxcXODs7IymTZsKHY+I1MijR4+QmZkJqVSKJk2asHQTkZKMjAysXLkSERERaNu2bZHyHRQUJFAy9cbyLWL5+fmIjY3FkSNHcPLkSTRu3BgDBw6Es7MzGjRoIHQ8IiIiUlO7d+/GypUrUaVKFSxYsICb6nwAlm8CAOTl5SE8PBw///wzcnNzuc43ERERFZGUlARfX1/Ex8fDxcUFvr6+MDY2FjqWRuFqJyL3/PlzHDlyBEePHsW1a9fQpEkTjB49WuhYREREpIYGDRoEIyMjbNy4EY6OjkLH0Ui88y1C/y7c5ubmGDBgAAYMGMAHMImIiKhEs2fPxrx581CzZk2ho2gslm8R2b59O44ePYrr16+jQYMGGDBgAD777DNYWVkJHY2IiIhIFFi+RcTCwgL6+vpwcHCAtbV1qWO5yQ4RERHRx8fyLSJlnZvFTXaIiIiIKgfLNxERERGRinDHBCIiIiIiFWH5JiIiIiJSEZZvIiIiIiIVYfkmIiIiIlIR7nBJRCSgv3eUDQoKKvZ6fHw8xowZg8DAQHTp0gXAXysXPX36tMSvGR0djXr16mH06NG4ePFiieOsrKywd+9exfHdu3fh7++PixcvIisrC1KpFLa2tvjqq69gaWkJAFi3bh3Wr1//3u/rzp07it//8ssv2LhxI4YPH46FCxeW+GcyMzMRHByMEydO4MmTJ8jLy0PDhg3h5OSE8ePHw8TERDG2LDmuXLmCGjVqvDcrEZEqsXwTEWmgXr16YcqUKcVeMzU1Vfze0tIS//nPf4odV716dcXv7927B09PT7Rr1w5z585F7dq1kZqaip07d8LT0xNBQUHo0KEDhg4dih49eij+XHh4OHbv3o3Q0NBi/w6ZTIaIiAi0bt0akZGRmD17drGF+O7du/j666+Rn5+PUaNGwdraGrq6uvjtt9+wY8cOHD58GKGhoahdu7bSnyvp7wWAatWqlXiNiEgoLN9ERBrI1NQUHTp0eO84Q0PDMo3btm0bpFIp/vvf/0JfX19xvm/fvhgwYAA2btyIzZs3o169eqhXr57iekxMDACU+HfExcUhJSUFu3btwpgxYxAZGYnhw4crjXn37h2+/fZbSCQS7N+/H7Vq1VJc69q1K5ydneHq6oq1a9di0aJFSn+2LN8bEZE6YfkmIiK8ePECAPDvrR+qV6+OOXPm4M2bN+X6unv27EHz5s1ha2sLe3t7hISEFCnfR44cwYMHDxAQEKBUvP9mbm6OyZMn4/Xr1+XKQESkTli+iYg0kFwuR0FBQZHzenp6ZRoHALq6upBIJACA3r17Izo6GsOHD4eHhwe6du2K5s2bQyKR4LPPPitXxqysLERFRWHatGkAAHd3d3z//fe4du0a2rdvrxgXFRUFY2Nj9OzZs8SvNXHixGLPl/S96ejoQEeHawoQkfph+SYi0kARERGIiIgocn7Xrl2wtbVVHCckJMDKyqrYr7FixQq4uroCAEaOHIk///wTv/76q2Jqh4mJCbp3747Ro0crleWyioyMRGFhoeLv+PTTT2FsbIyQkBClr5eUlARzc/MiZbmwsLDInfh/v7ko6Xv7/PPPsWTJkg/OTERU2Vi+iYg0UJ8+fTB16tQi55s3b650bGVlVeIKI+bm5krH33zzDcaNG4eYmBicP38e8fHxiIyMxMGDBzFnzhyMHTv2gzLu2bMHdnZ2qFatGl69egXgrznkhw4dwpw5c1CzZk0ARae6/PN7fP78udK5kydPolGjRorj3bt3F/tn//nQKRGROmH5JiLSQFKpFNbW1u8dV6NGjTKN+5uxsTFcXFzg4uICALh16xZmz56NVatWYfDgwUrL/ZUmMTERt27dAgDY2dkVub5v3z5FmW/YsCGuXbsGuVyumAYDAJs3b0Z+fj4A4MyZM8UuLfgh3xsRkTrghDgiIpF7/vw5unfvjvDw8CLXLC0t8e233yIvLw/Jycll/pq7d+9GtWrVsH37dgQGBir9atGihdISgU5OTsjIyCiyJrmFhQWsra1hbW2Nhg0blv8bJCJSIyzfREQiV7t2bejp6SE4OBjv3r0rcv3hw4cwMDBAkyZNyvT18vLyEBkZCUdHR9jb26NLly5Kv9zd3fHgwQNF2XZxcUHz5s0xf/58pKWlFfs17927V/5vkIhIjXDaCRGRwFJTU7F9+/Yi51u2bKm05nZ55OTk4Lfffivxetu2baGnp4cFCxZg6tSp8PDwgJeXF1q0aIE3b97g3Llz2LVrF7755hsYGxuX6e+MiopCZmYmnJ2di70+ePBgrF69GiEhIejcuTOqVauG9evXY8qUKRg0aBCGDx+Ojh07wsDAAPfu3cO+fftw8+ZN9OzZs8hc7tK+t6ZNm0IqlZYpMxGRqrB8ExEJLCkpCX5+fkXOu7m5wc3NrUJf+9atW/D09Czx+vnz52FqaorevXsjLCwMv/76KzZt2oSMjAxUqVIFlpaW+Pnnn9GvX78y/5179+6FsbGx0k6Y/2RmZgYHBwccP34c6enpqFWrFlq0aIF9+/YhLCwMR44cQUhICHJzc2FmZgY7Ozv4+Pigc+fORb5Wad/bL7/8Uu5lEomIKotEXtJj5kRERERE9FFxzjcRERERkYqwfBMRERERqQjLNxERERGRirB8ExERERGpCMs3EREREZGKsHwTEREREakIyzcRERERkYqwfBMRERERqQjLNxERERGRirB8ExERERGpCMs3EREREZGKsHwTEREREanI/wFLtlnsQTPqqgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create plot\n",
    "sns.set(style= 'darkgrid')\n",
    "plt.figure(figsize= [8,6])\n",
    "sns.barplot(x= Total_units['LIFESTAGE'], y= Total_units['PROD_QTY'], hue= Total_units['PREMIUM_CUSTOMER'])\n",
    "plt.title('Total number of units bought per customers by LIFESTAGE and PREMIUM_CUSTOMER')\n",
    "plt.xticks(rotation= 90)\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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}