Transactional and Segmentation Analysis - Task1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "855b9e8f",
   "metadata": {},
   "source": [
    "# Task 1 - Data Preparation and Customer Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53dfc233",
   "metadata": {},
   "source": [
    "Conducting analysis on our client's transaction dataset and identifying customer purchasing behaviours to generate insights and provide commercial recommendations.\n",
    "\n",
    "Background information for the task:\n",
    "\n",
    "We need to present a strategic recommendation to the Product Manager that is supported by data which he/she can then use for the upcoming category review however to do so we need to analyse the data to understand the current purchasing trends and behaviours. The client is particularly interested in customer segments and their product purchasing behaviour. Consider what metrics would help describe the customer's purchasing behaviour.\n",
    "\n",
    "Main goals of this task are :\n",
    "\n",
    "1. Examining transaction data - checking for missing data, anomalies, outliers and clean them.\n",
    "2. Examining customer data - similar to above transaction data.\n",
    "3. Data analysis and customer segments - creating charts and graphs, note trends and insights.\n",
    "4. Deep dive into customer segments - determining which segments should be targetted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f40bf5cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the necessary libraries for our project:\n",
    "import pandas as pd \n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt \n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8b15f296",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Uploading our Dataset (Transactions):\n",
    "transactional_data = pd.read_csv(\"QVI_transaction_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "4b08b151",
   "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>43390</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>43599</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>43605</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>43329</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>43330</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  43390          1            1000       1         5   \n",
       "1  43599          1            1307     348        66   \n",
       "2  43605          1            1343     383        61   \n",
       "3  43329          2            2373     974        69   \n",
       "4  43330          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": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the first 5 entries of our (Transactions Dataset):\n",
    "transactional_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "fa6bbf6b",
   "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_QTY</th>\n",
       "      <th>TOT_SALES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>264836.000000</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>43464.036260</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>std</th>\n",
       "      <td>105.389282</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",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>43282.000000</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>43373.000000</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>43464.000000</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>43555.000000</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>43646.000000</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                DATE     STORE_NBR  LYLTY_CARD_NBR        TXN_ID  \\\n",
       "count  264836.000000  264836.00000    2.648360e+05  2.648360e+05   \n",
       "mean    43464.036260     135.08011    1.355495e+05  1.351583e+05   \n",
       "std       105.389282      76.78418    8.057998e+04  7.813303e+04   \n",
       "min     43282.000000       1.00000    1.000000e+03  1.000000e+00   \n",
       "25%     43373.000000      70.00000    7.002100e+04  6.760150e+04   \n",
       "50%     43464.000000     130.00000    1.303575e+05  1.351375e+05   \n",
       "75%     43555.000000     203.00000    2.030942e+05  2.027012e+05   \n",
       "max     43646.000000     272.00000    2.373711e+06  2.415841e+06   \n",
       "\n",
       "            PROD_NBR       PROD_QTY      TOT_SALES  \n",
       "count  264836.000000  264836.000000  264836.000000  \n",
       "mean       56.583157       1.907309       7.304200  \n",
       "std        32.826638       0.643654       3.083226  \n",
       "min         1.000000       1.000000       1.500000  \n",
       "25%        28.000000       2.000000       5.400000  \n",
       "50%        56.000000       2.000000       7.400000  \n",
       "75%        85.000000       2.000000       9.200000  \n",
       "max       114.000000     200.000000     650.000000  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for the statistics behind our (Transactions Dataset):\n",
    "tansactional_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "908db212",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Uploading our Dataset (Purchases Behaviour):\n",
    "purchase_behaviour = pd.read_csv(\"QVI_purchase_behaviour.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "074c991d",
   "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>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": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the first 5 entries of our (Purchases Behaviour Dataset):\n",
    "purchase_behaviour.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "dbed0a35",
   "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>LYLTY_CARD_NBR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7.263700e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.361859e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.989293e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.620200e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.340400e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.033750e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.373711e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       LYLTY_CARD_NBR\n",
       "count    7.263700e+04\n",
       "mean     1.361859e+05\n",
       "std      8.989293e+04\n",
       "min      1.000000e+03\n",
       "25%      6.620200e+04\n",
       "50%      1.340400e+05\n",
       "75%      2.033750e+05\n",
       "max      2.373711e+06"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for the statistics behind our (Purchases Behaviour Dataset):\n",
    "purchase_behaviour.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "a671cc26",
   "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": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for null values\n",
    "transactional_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "7d34fab9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LYLTY_CARD_NBR      0\n",
       "LIFESTAGE           0\n",
       "PREMIUM_CUSTOMER    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for null values\n",
    "purchase_behaviour.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "df117ad3",
   "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>LYLTY_CARD_NBR</th>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "      <th>DATE</th>\n",
       "      <th>STORE_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>1000</td>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>43390</td>\n",
       "      <td>1</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>1307</td>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>43599</td>\n",
       "      <td>1</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>1343</td>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>43605</td>\n",
       "      <td>1</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>2373</td>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>43329</td>\n",
       "      <td>2</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>2426</td>\n",
       "      <td>MIDAGE SINGLES/COUPLES</td>\n",
       "      <td>Budget</td>\n",
       "      <td>43330</td>\n",
       "      <td>2</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": [
       "   LYLTY_CARD_NBR               LIFESTAGE PREMIUM_CUSTOMER   DATE  STORE_NBR  \\\n",
       "0            1000   YOUNG SINGLES/COUPLES          Premium  43390          1   \n",
       "1            1307  MIDAGE SINGLES/COUPLES           Budget  43599          1   \n",
       "2            1343  MIDAGE SINGLES/COUPLES           Budget  43605          1   \n",
       "3            2373  MIDAGE SINGLES/COUPLES           Budget  43329          2   \n",
       "4            2426  MIDAGE SINGLES/COUPLES           Budget  43330          2   \n",
       "\n",
       "   TXN_ID  PROD_NBR                                 PROD_NAME  PROD_QTY  \\\n",
       "0       1         5    Natural Chip        Compny SeaSalt175g         2   \n",
       "1     348        66                  CCs Nacho Cheese    175g         3   \n",
       "2     383        61    Smiths Crinkle Cut  Chips Chicken 170g         2   \n",
       "3     974        69    Smiths Chip Thinly  S/Cream&Onion 175g         5   \n",
       "4    1038       108  Kettle Tortilla ChpsHny&Jlpno Chili 150g         3   \n",
       "\n",
       "   TOT_SALES  \n",
       "0        6.0  \n",
       "1        6.3  \n",
       "2        2.9  \n",
       "3       15.0  \n",
       "4       13.8  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Right merge of the Data to check for outliers:\n",
    "merged_data = pd.merge(purchase_behaviour, transactional_data, on = 'LYLTY_CARD_NBR', how = 'right')\n",
    "merged_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "b194ee48",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "264836\n",
      "264836\n",
      "72637\n"
     ]
    }
   ],
   "source": [
    "# Checking how many columns we have after merging:\n",
    "print(len(merged_data))\n",
    "print(len(transactional_data))\n",
    "print(len(purchase_behaviour))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "aaebe2f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 264836 entries, 0 to 264835\n",
      "Data columns (total 10 columns):\n",
      " #   Column            Non-Null Count   Dtype  \n",
      "---  ------            --------------   -----  \n",
      " 0   LYLTY_CARD_NBR    264836 non-null  int64  \n",
      " 1   LIFESTAGE         264836 non-null  object \n",
      " 2   PREMIUM_CUSTOMER  264836 non-null  object \n",
      " 3   DATE              264836 non-null  int64  \n",
      " 4   STORE_NBR         264836 non-null  int64  \n",
      " 5   TXN_ID            264836 non-null  int64  \n",
      " 6   PROD_NBR          264836 non-null  int64  \n",
      " 7   PROD_NAME         264836 non-null  object \n",
      " 8   PROD_QTY          264836 non-null  int64  \n",
      " 9   TOT_SALES         264836 non-null  float64\n",
      "dtypes: float64(1), int64(6), object(3)\n",
      "memory usage: 22.2+ MB\n"
     ]
    }
   ],
   "source": [
    "# Checking Data Types of the merged Data:\n",
    "merged_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "df6e8f8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting DATE column into Date format\n",
    "from datetime import date, timedelta\n",
    "start = date(1899, 12, 30)\n",
    "new_date_format = []\n",
    "for date in merged_data[\"DATE\"]:\n",
    "  delta = timedelta(date)\n",
    "  new_date_format.append(start + delta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "84fc41d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "datetime64[ns]\n"
     ]
    }
   ],
   "source": [
    "# Checking our result\n",
    "merged_data[\"DATE\"] = pd.to_datetime(pd.Series(new_date_format))\n",
    "print(merged_data[\"DATE\"].dtype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "2b977eb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Natural Chip        Compny SeaSalt175g',\n",
       "       'CCs Nacho Cheese    175g',\n",
       "       'Smiths Crinkle Cut  Chips Chicken 170g',\n",
       "       'Smiths Chip Thinly  S/Cream&Onion 175g',\n",
       "       'Kettle Tortilla ChpsHny&Jlpno Chili 150g',\n",
       "       'Old El Paso Salsa   Dip Tomato Mild 300g',\n",
       "       'Smiths Crinkle Chips Salt & Vinegar 330g',\n",
       "       'Grain Waves         Sweet Chilli 210g',\n",
       "       'Doritos Corn Chip Mexican Jalapeno 150g',\n",
       "       'Grain Waves Sour    Cream&Chives 210G',\n",
       "       'Kettle Sensations   Siracha Lime 150g',\n",
       "       'Twisties Cheese     270g', 'WW Crinkle Cut      Chicken 175g',\n",
       "       'Thins Chips Light&  Tangy 175g', 'CCs Original 175g',\n",
       "       'Burger Rings 220g', 'NCC Sour Cream &    Garden Chives 175g',\n",
       "       'Doritos Corn Chip Southern Chicken 150g',\n",
       "       'Cheezels Cheese Box 125g', 'Smiths Crinkle      Original 330g',\n",
       "       'Infzns Crn Crnchers Tangy Gcamole 110g',\n",
       "       'Kettle Sea Salt     And Vinegar 175g',\n",
       "       'Smiths Chip Thinly  Cut Original 175g', 'Kettle Original 175g',\n",
       "       'Red Rock Deli Thai  Chilli&Lime 150g',\n",
       "       'Pringles Sthrn FriedChicken 134g', 'Pringles Sweet&Spcy BBQ 134g',\n",
       "       'Red Rock Deli SR    Salsa & Mzzrlla 150g',\n",
       "       'Thins Chips         Originl saltd 175g',\n",
       "       'Red Rock Deli Sp    Salt & Truffle 150G',\n",
       "       'Smiths Thinly       Swt Chli&S/Cream175G', 'Kettle Chilli 175g',\n",
       "       'Doritos Mexicana    170g',\n",
       "       'Smiths Crinkle Cut  French OnionDip 150g',\n",
       "       'Natural ChipCo      Hony Soy Chckn175g',\n",
       "       'Dorito Corn Chp     Supreme 380g', 'Twisties Chicken270g',\n",
       "       'Smiths Thinly Cut   Roast Chicken 175g',\n",
       "       'Smiths Crinkle Cut  Tomato Salsa 150g',\n",
       "       'Kettle Mozzarella   Basil & Pesto 175g',\n",
       "       'Infuzions Thai SweetChili PotatoMix 110g',\n",
       "       'Kettle Sensations   Camembert & Fig 150g',\n",
       "       'Smith Crinkle Cut   Mac N Cheese 150g',\n",
       "       'Kettle Honey Soy    Chicken 175g',\n",
       "       'Thins Chips Seasonedchicken 175g',\n",
       "       'Smiths Crinkle Cut  Salt & Vinegar 170g',\n",
       "       'Infuzions BBQ Rib   Prawn Crackers 110g',\n",
       "       'GrnWves Plus Btroot & Chilli Jam 180g',\n",
       "       'Tyrrells Crisps     Lightly Salted 165g',\n",
       "       'Kettle Sweet Chilli And Sour Cream 175g',\n",
       "       'Doritos Salsa       Medium 300g', 'Kettle 135g Swt Pot Sea Salt',\n",
       "       'Pringles SourCream  Onion 134g',\n",
       "       'Doritos Corn Chips  Original 170g',\n",
       "       'Twisties Cheese     Burger 250g',\n",
       "       'Old El Paso Salsa   Dip Chnky Tom Ht300g',\n",
       "       'Cobs Popd Swt/Chlli &Sr/Cream Chips 110g',\n",
       "       'Woolworths Mild     Salsa 300g',\n",
       "       'Natural Chip Co     Tmato Hrb&Spce 175g',\n",
       "       'Smiths Crinkle Cut  Chips Original 170g',\n",
       "       'Cobs Popd Sea Salt  Chips 110g',\n",
       "       'Smiths Crinkle Cut  Chips Chs&Onion170g',\n",
       "       'French Fries Potato Chips 175g',\n",
       "       'Old El Paso Salsa   Dip Tomato Med 300g',\n",
       "       'Doritos Corn Chips  Cheese Supreme 170g',\n",
       "       'Pringles Original   Crisps 134g',\n",
       "       'RRD Chilli&         Coconut 150g',\n",
       "       'WW Original Corn    Chips 200g',\n",
       "       'Thins Potato Chips  Hot & Spicy 175g',\n",
       "       'Cobs Popd Sour Crm  &Chives Chips 110g',\n",
       "       'Smiths Crnkle Chip  Orgnl Big Bag 380g',\n",
       "       'Doritos Corn Chips  Nacho Cheese 170g',\n",
       "       'Kettle Sensations   BBQ&Maple 150g',\n",
       "       'WW D/Style Chip     Sea Salt 200g',\n",
       "       'Pringles Chicken    Salt Crips 134g',\n",
       "       'WW Original Stacked Chips 160g',\n",
       "       'Smiths Chip Thinly  CutSalt/Vinegr175g', 'Cheezels Cheese 330g',\n",
       "       'Tostitos Lightly    Salted 175g',\n",
       "       'Thins Chips Salt &  Vinegar 175g',\n",
       "       'Smiths Crinkle Cut  Chips Barbecue 170g', 'Cheetos Puffs 165g',\n",
       "       'RRD Sweet Chilli &  Sour Cream 165g',\n",
       "       'WW Crinkle Cut      Original 175g',\n",
       "       'Tostitos Splash Of  Lime 175g', 'Woolworths Medium   Salsa 300g',\n",
       "       'Kettle Tortilla ChpsBtroot&Ricotta 150g',\n",
       "       'CCs Tasty Cheese    175g', 'Woolworths Cheese   Rings 190g',\n",
       "       'Tostitos Smoked     Chipotle 175g', 'Pringles Barbeque   134g',\n",
       "       'WW Supreme Cheese   Corn Chips 200g',\n",
       "       'Pringles Mystery    Flavour 134g',\n",
       "       'Tyrrells Crisps     Ched & Chives 165g',\n",
       "       'Snbts Whlgrn Crisps Cheddr&Mstrd 90g',\n",
       "       'Cheetos Chs & Bacon Balls 190g', 'Pringles Slt Vingar 134g',\n",
       "       'Infuzions SourCream&Herbs Veg Strws 110g',\n",
       "       'Kettle Tortilla ChpsFeta&Garlic 150g',\n",
       "       'Infuzions Mango     Chutny Papadums 70g',\n",
       "       'RRD Steak &         Chimuchurri 150g',\n",
       "       'RRD Honey Soy       Chicken 165g',\n",
       "       'Sunbites Whlegrn    Crisps Frch/Onin 90g',\n",
       "       'RRD Salt & Vinegar  165g', 'Doritos Cheese      Supreme 330g',\n",
       "       'Smiths Crinkle Cut  Snag&Sauce 150g',\n",
       "       'WW Sour Cream &OnionStacked Chips 160g',\n",
       "       'RRD Lime & Pepper   165g',\n",
       "       'Natural ChipCo Sea  Salt & Vinegr 175g',\n",
       "       'Red Rock Deli Chikn&Garlic Aioli 150g',\n",
       "       'RRD SR Slow Rst     Pork Belly 150g', 'RRD Pc Sea Salt     165g',\n",
       "       'Smith Crinkle Cut   Bolognese 150g', 'Doritos Salsa Mild  300g'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# lets Check if the product name column to make sure all items are categorized for \"Chips\"\n",
    "merged_data[\"PROD_NAME\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "6eef9235",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "a5c52435",
   "metadata": {},
   "outputs": [],
   "source": [
    "split_prods = merged_data[\"PROD_NAME\"].str.replace(r'([0-9]+[gG])','').str.replace(r'[^\\w]',' ').str.split()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "e82d0fb6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chips       49770\n",
      "Kettle      41288\n",
      "Smiths      28860\n",
      "Salt        27976\n",
      "Cheese      27890\n",
      "            ...  \n",
      "Sunbites     1432\n",
      "Pc           1431\n",
      "Garden       1419\n",
      "NCC          1419\n",
      "Fries        1418\n",
      "Length: 198, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# We categorized the order of the most sold Product\n",
    "word_counts = {}\n",
    "def count_words(line):\n",
    "  for word in line:\n",
    "    if word not in word_counts:\n",
    "      word_counts[word] = 1\n",
    "    else:\n",
    "      word_counts[word] += 1\n",
    "split_prods.apply(lambda line: count_words(line))\n",
    "print(pd.Series(word_counts).sort_values(ascending = False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "a41bc06e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       LYLTY_CARD_NBR     STORE_NBR        TXN_ID       PROD_NBR  \\\n",
      "count    2.648360e+05  264836.00000  2.648360e+05  264836.000000   \n",
      "mean     1.355495e+05     135.08011  1.351583e+05      56.583157   \n",
      "std      8.057998e+04      76.78418  7.813303e+04      32.826638   \n",
      "min      1.000000e+03       1.00000  1.000000e+00       1.000000   \n",
      "25%      7.002100e+04      70.00000  6.760150e+04      28.000000   \n",
      "50%      1.303575e+05     130.00000  1.351375e+05      56.000000   \n",
      "75%      2.030942e+05     203.00000  2.027012e+05      85.000000   \n",
      "max      2.373711e+06     272.00000  2.415841e+06     114.000000   \n",
      "\n",
      "            PROD_QTY      TOT_SALES  \n",
      "count  264836.000000  264836.000000  \n",
      "mean        1.907309       7.304200  \n",
      "std         0.643654       3.083226  \n",
      "min         1.000000       1.500000  \n",
      "25%         2.000000       5.400000  \n",
      "50%         2.000000       7.400000  \n",
      "75%         2.000000       9.200000  \n",
      "max       200.000000     650.000000   \n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 264836 entries, 0 to 264835\n",
      "Data columns (total 10 columns):\n",
      " #   Column            Non-Null Count   Dtype         \n",
      "---  ------            --------------   -----         \n",
      " 0   LYLTY_CARD_NBR    264836 non-null  int64         \n",
      " 1   LIFESTAGE         264836 non-null  object        \n",
      " 2   PREMIUM_CUSTOMER  264836 non-null  object        \n",
      " 3   DATE              264836 non-null  datetime64[ns]\n",
      " 4   STORE_NBR         264836 non-null  int64         \n",
      " 5   TXN_ID            264836 non-null  int64         \n",
      " 6   PROD_NBR          264836 non-null  int64         \n",
      " 7   PROD_NAME         264836 non-null  object        \n",
      " 8   PROD_QTY          264836 non-null  int64         \n",
      " 9   TOT_SALES         264836 non-null  float64       \n",
      "dtypes: datetime64[ns](1), float64(1), int64(5), object(3)\n",
      "memory usage: 22.2+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(merged_data.describe(), '\\n')\n",
    "print(merged_data.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "921fbad4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.8, 50.75]       264834\n",
       "(50.75, 100.5]          0\n",
       "(100.5, 150.25]         0\n",
       "(150.25, 200.0]         2\n",
       "Name: PROD_QTY, dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# From above binning we see that PROD_QTY values above 50.75\n",
    "merged_data[\"PROD_QTY\"].value_counts(bins=4).sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "d91b5145",
   "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>LYLTY_CARD_NBR</th>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "      <th>DATE</th>\n",
       "      <th>STORE_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>69762</th>\n",
       "      <td>226000</td>\n",
       "      <td>OLDER FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>2018-08-19</td>\n",
       "      <td>226</td>\n",
       "      <td>226201</td>\n",
       "      <td>4</td>\n",
       "      <td>Dorito Corn Chp     Supreme 380g</td>\n",
       "      <td>200</td>\n",
       "      <td>650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69763</th>\n",
       "      <td>226000</td>\n",
       "      <td>OLDER FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>2019-05-20</td>\n",
       "      <td>226</td>\n",
       "      <td>226210</td>\n",
       "      <td>4</td>\n",
       "      <td>Dorito Corn Chp     Supreme 380g</td>\n",
       "      <td>200</td>\n",
       "      <td>650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217237</th>\n",
       "      <td>201060</td>\n",
       "      <td>YOUNG FAMILIES</td>\n",
       "      <td>Premium</td>\n",
       "      <td>2019-05-18</td>\n",
       "      <td>201</td>\n",
       "      <td>200202</td>\n",
       "      <td>26</td>\n",
       "      <td>Pringles Sweet&amp;Spcy BBQ 134g</td>\n",
       "      <td>5</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238333</th>\n",
       "      <td>219004</td>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>2018-08-14</td>\n",
       "      <td>219</td>\n",
       "      <td>218018</td>\n",
       "      <td>25</td>\n",
       "      <td>Pringles SourCream  Onion 134g</td>\n",
       "      <td>5</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238471</th>\n",
       "      <td>261331</td>\n",
       "      <td>YOUNG SINGLES/COUPLES</td>\n",
       "      <td>Mainstream</td>\n",
       "      <td>2019-05-19</td>\n",
       "      <td>261</td>\n",
       "      <td>261111</td>\n",
       "      <td>87</td>\n",
       "      <td>Infuzions BBQ Rib   Prawn Crackers 110g</td>\n",
       "      <td>5</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        LYLTY_CARD_NBR              LIFESTAGE PREMIUM_CUSTOMER       DATE  \\\n",
       "69762           226000         OLDER FAMILIES          Premium 2018-08-19   \n",
       "69763           226000         OLDER FAMILIES          Premium 2019-05-20   \n",
       "217237          201060         YOUNG FAMILIES          Premium 2019-05-18   \n",
       "238333          219004  YOUNG SINGLES/COUPLES       Mainstream 2018-08-14   \n",
       "238471          261331  YOUNG SINGLES/COUPLES       Mainstream 2019-05-19   \n",
       "\n",
       "        STORE_NBR  TXN_ID  PROD_NBR                                PROD_NAME  \\\n",
       "69762         226  226201         4         Dorito Corn Chp     Supreme 380g   \n",
       "69763         226  226210         4         Dorito Corn Chp     Supreme 380g   \n",
       "217237        201  200202        26             Pringles Sweet&Spcy BBQ 134g   \n",
       "238333        219  218018        25           Pringles SourCream  Onion 134g   \n",
       "238471        261  261111        87  Infuzions BBQ Rib   Prawn Crackers 110g   \n",
       "\n",
       "        PROD_QTY  TOT_SALES  \n",
       "69762        200      650.0  \n",
       "69763        200      650.0  \n",
       "217237         5       18.5  \n",
       "238333         5       18.5  \n",
       "238471         5       19.0  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking for outliers in Products\n",
    "merged_data.sort_values(by=\"PROD_QTY\", ascending=False).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "224c31fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Two outliers of value 200 in PROD_QTY will be removed. Both entries are by the same customer and will be examined by this customer's transactions\n",
    "merged_data = merged_data[merged_data[\"PROD_QTY\"] < 6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "a3ca1078",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(merged_data[merged_data[\"LYLTY_CARD_NBR\"]==226000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "aa5067df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                  264834\n",
       "unique                    364\n",
       "top       2018-12-24 00:00:00\n",
       "freq                      939\n",
       "first     2018-07-01 00:00:00\n",
       "last      2019-06-30 00:00:00\n",
       "Name: DATE, dtype: object"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data[\"DATE\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "575465c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-12-25'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#There are 365 days in a year but in the DATE column there are only 364 unique values so one is missing\n",
    "pd.date_range(start=merged_data[\"DATE\"].min(), end=merged_data[\"DATE\"].max()).difference(merged_data[\"DATE\"])\n",
    "#Using the difference method we see that 2018-12-25 was a missing date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "be79e462",
   "metadata": {},
   "outputs": [],
   "source": [
    "check_null_date = pd.merge(pd.Series(pd.date_range(start=merged_data[\"DATE\"].min(), end = merged_data[\"DATE\"].max()), name=\"DATE\"), merged_data, on = \"DATE\", how = \"left\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "7e73b1ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "trans_by_date = check_null_date[\"DATE\"].value_counts()\n",
    "dec = trans_by_date[(trans_by_date.index >= pd.datetime(2018,12,1)) & (trans_by_date.index < pd.datetime(2019,1,1))].sort_index()\n",
    "dec.index = dec.index.strftime('%d')\n",
    "ax = dec.plot(figsize=(15,3))\n",
    "ax.set_xticks(np.arange(len(dec)))\n",
    "ax.set_xticklabels(dec.index)\n",
    "plt.title(\"2018 December Sales\")\n",
    "plt.savefig(\"2018 December Sales.png\", bbox_inches=\"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "97a6675a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018-12-25      1\n",
       "2018-11-25    648\n",
       "2018-10-18    658\n",
       "2019-06-13    659\n",
       "2019-06-24    662\n",
       "Name: DATE, dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The day with no transaction is a Christmas day that is when the store is closed. So there is no anomaly in this.\n",
    "check_null_date[\"DATE\"].value_counts().sort_values().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "e525991e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count    258770.000000\n",
      "mean        182.324276\n",
      "std          64.955035\n",
      "min          70.000000\n",
      "25%         150.000000\n",
      "50%         170.000000\n",
      "75%         175.000000\n",
      "max         380.000000\n",
      "Name: 0, dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Exploring Packet sizes\n",
    "merged_data[\"PROD_NAME\"] = merged_data[\"PROD_NAME\"].str.replace(r'[0-9]+(G)','g')\n",
    "pack_sizes = merged_data[\"PROD_NAME\"].str.extract(r'([0-9]+[gG])')[0].str.replace(\"g\",\"\").astype(\"float\")\n",
    "print(pack_sizes.describe())\n",
    "pack_sizes.plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "6c07c773",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Burger         1564\n",
       "CCs            4551\n",
       "Cheetos        2927\n",
       "Cheezels       4603\n",
       "Cobs           9693\n",
       "Dorito         3183\n",
       "Doritos       24962\n",
       "French         1418\n",
       "Grain          6272\n",
       "GrnWves        1468\n",
       "Infuzions     11057\n",
       "Infzns         3144\n",
       "Kettle        41288\n",
       "NCC            1419\n",
       "Natural        6050\n",
       "Old            9324\n",
       "Pringles      25102\n",
       "RRD           11894\n",
       "Red            5885\n",
       "Smith          2963\n",
       "Smiths        28860\n",
       "Snbts          1576\n",
       "Sunbites       1432\n",
       "Thins         14075\n",
       "Tostitos       9471\n",
       "Twisties       9454\n",
       "Tyrrells       6442\n",
       "WW            10320\n",
       "Woolworths     4437\n",
       "Name: PROD_NAME, dtype: int64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data[\"PROD_NAME\"].str.split().str[0].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "160c1969",
   "metadata": {},
   "source": [
    "Some product names are written in more than one way. Example : Dorito and Doritos, Grains and GrnWves, Infusions and Ifzns, Natural and NCC, Red and RRD, Smith and Smiths and Snbts and Sunbites."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "ea6b3c7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Red, Rock, Deli, Sp, Salt, &, Truffle, g]        1498\n",
       "[Red, Rock, Deli, Thai, Chilli&Lime, 150g]        1495\n",
       "[Red, Rock, Deli, SR, Salsa, &, Mzzrlla, 150g]    1458\n",
       "[Red, Rock, Deli, Chikn&Garlic, Aioli, 150g]      1434\n",
       "Name: PROD_NAME, dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data[\"PROD_NAME\"].str.split()[merged_data[\"PROD_NAME\"].str.split().str[0] == \"Red\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "c6886423",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_data[\"Cleaned_Brand_Names\"] = merged_data[\"PROD_NAME\"].str.split().str[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "c9c8a4aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_brand_names(line):\n",
    "    brand = line[\"Cleaned_Brand_Names\"]\n",
    "    if brand == \"Dorito\":\n",
    "        return \"Doritos\"\n",
    "    elif brand == \"GrnWves\" or brand == \"Grain\":\n",
    "        return \"Grain Waves\"\n",
    "    elif brand == \"Infzns\":\n",
    "        return \"Infuzions\"\n",
    "    elif brand == \"Natural\" or brand == \"NCC\":\n",
    "        return \"Natural Chip Co\"\n",
    "    elif brand == \"Red\":\n",
    "        return \"RRD\"\n",
    "    elif brand == \"Smith\":\n",
    "        return \"Smiths\"\n",
    "    elif brand == \"Snbts\":\n",
    "        return \"Sunbites\"\n",
    "    elif brand == \"WW\":\n",
    "        return \"Woolworths\"\n",
    "    else:\n",
    "        return brand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "49c15926",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_data[\"Cleaned_Brand_Names\"] = merged_data.apply(lambda line: clean_brand_names(line), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "c108345b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "merged_data[\"Cleaned_Brand_Names\"].value_counts(ascending=True).plot.barh(figsize=(10,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "700b79b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LYLTY_CARD_NBR         0\n",
       "LIFESTAGE              0\n",
       "PREMIUM_CUSTOMER       0\n",
       "DATE                   0\n",
       "STORE_NBR              0\n",
       "TXN_ID                 0\n",
       "PROD_NBR               0\n",
       "PROD_NAME              0\n",
       "PROD_QTY               0\n",
       "TOT_SALES              0\n",
       "Cleaned_Brand_Names    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ec8e224",
   "metadata": {},
   "source": [
    "1. Who spends the most on chips (total sales), describing customers by lifestage and how premium their general purchasing behaviour is.\n",
    "2. How many customers are in each segment 3. How many chips are bought per customer by segment 4. What's the average chip price by customer segment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "4e650995",
   "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></th>\n",
       "      <th>sum</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>168363.25</td>\n",
       "      <td>7.269570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>157621.60</td>\n",
       "      <td>7.558339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>155677.05</td>\n",
       "      <td>7.252262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>139345.85</td>\n",
       "      <td>7.287201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">OLDER SINGLES/COUPLES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>136769.80</td>\n",
       "      <td>7.430315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mainstream</th>\n",
       "      <td>133393.80</td>\n",
       "      <td>7.282116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>132263.15</td>\n",
       "      <td>7.449766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>113147.80</td>\n",
       "      <td>7.443445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>103445.55</td>\n",
       "      <td>7.262395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>97646.05</td>\n",
       "      <td>7.456174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>92788.75</td>\n",
       "      <td>7.189025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>90803.85</td>\n",
       "      <td>7.647284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>84025.50</td>\n",
       "      <td>7.266756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>80658.40</td>\n",
       "      <td>7.208079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>61141.60</td>\n",
       "      <td>6.615624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>58432.65</td>\n",
       "      <td>7.112056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>41642.10</td>\n",
       "      <td>6.629852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>35514.80</td>\n",
       "      <td>7.074661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">NEW FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>21928.45</td>\n",
       "      <td>7.297321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mainstream</th>\n",
       "      <td>17013.90</td>\n",
       "      <td>7.317806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>11491.10</td>\n",
       "      <td>7.231655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               sum      mean\n",
       "LIFESTAGE              PREMIUM_CUSTOMER                     \n",
       "OLDER FAMILIES         Budget            168363.25  7.269570\n",
       "YOUNG SINGLES/COUPLES  Mainstream        157621.60  7.558339\n",
       "RETIREES               Mainstream        155677.05  7.252262\n",
       "YOUNG FAMILIES         Budget            139345.85  7.287201\n",
       "OLDER SINGLES/COUPLES  Budget            136769.80  7.430315\n",
       "                       Mainstream        133393.80  7.282116\n",
       "                       Premium           132263.15  7.449766\n",
       "RETIREES               Budget            113147.80  7.443445\n",
       "OLDER FAMILIES         Mainstream        103445.55  7.262395\n",
       "RETIREES               Premium            97646.05  7.456174\n",
       "YOUNG FAMILIES         Mainstream         92788.75  7.189025\n",
       "MIDAGE SINGLES/COUPLES Mainstream         90803.85  7.647284\n",
       "YOUNG FAMILIES         Premium            84025.50  7.266756\n",
       "OLDER FAMILIES         Premium            80658.40  7.208079\n",
       "YOUNG SINGLES/COUPLES  Budget             61141.60  6.615624\n",
       "MIDAGE SINGLES/COUPLES Premium            58432.65  7.112056\n",
       "YOUNG SINGLES/COUPLES  Premium            41642.10  6.629852\n",
       "MIDAGE SINGLES/COUPLES Budget             35514.80  7.074661\n",
       "NEW FAMILIES           Budget             21928.45  7.297321\n",
       "                       Mainstream         17013.90  7.317806\n",
       "                       Premium            11491.10  7.231655"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets find out \n",
    "\n",
    "grouped_sales = pd.DataFrame(merged_data.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"])[\"TOT_SALES\"].agg([\"sum\", \"mean\"]))\n",
    "grouped_sales.sort_values(ascending=False, by=\"sum\")     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "44c26205",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1933115.0000000002"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_sales[\"sum\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "94e57d77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='LIFESTAGE,PREMIUM_CUSTOMER'>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped_sales[\"sum\"].sort_values().plot.barh(figsize=(12,7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "9cf60d17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Values of each group\n",
    "bars1 = grouped_sales[grouped_sales.index.get_level_values(\"PREMIUM_CUSTOMER\") == \"Budget\"][\"sum\"]\n",
    "bars2 = grouped_sales[grouped_sales.index.get_level_values(\"PREMIUM_CUSTOMER\") == \"Mainstream\"][\"sum\"]\n",
    "bars3 = grouped_sales[grouped_sales.index.get_level_values(\"PREMIUM_CUSTOMER\") == \"Premium\"][\"sum\"]\n",
    " \n",
    "bars1_text = (bars1 / sum(grouped_sales[\"sum\"])).apply(\"{:.1%}\".format)\n",
    "bars2_text = (bars2 / sum(grouped_sales[\"sum\"])).apply(\"{:.1%}\".format)\n",
    "bars3_text = (bars3 / sum(grouped_sales[\"sum\"])).apply(\"{:.1%}\".format)\n",
    " \n",
    "# Names of group and bar width\n",
    "names = grouped_sales.index.get_level_values(\"LIFESTAGE\").unique()\n",
    "\n",
    "# The position of the bars on the x-axis\n",
    "r = np.arange(len(names))\n",
    "\n",
    "plt.figure(figsize=(13,5)) \n",
    "\n",
    "# Create brown bars\n",
    "budget_bar = plt.barh(r, bars1, edgecolor='grey', height=1, label=\"Budget\")\n",
    "# Create green bars (middle), on top of the firs ones\n",
    "mains_bar = plt.barh(r, bars2, left=bars1, edgecolor='grey', height=1, label=\"Mainstream\")\n",
    "# Create green bars (top)\n",
    "tmp_bar = np.add(bars1, bars2)\n",
    "prem_bar = plt.barh(r, bars3, left=bars2, edgecolor='grey', height=1, label=\"Premium\")\n",
    "\n",
    "for i in range(7):\n",
    "    budget_width = budget_bar[i].get_width()\n",
    "    budget_main_width = budget_width + mains_bar[i].get_width()\n",
    "    plt.text(budget_width/2, i, bars1_text[i], va='center', ha='center', size=8)\n",
    "    plt.text(budget_width + mains_bar[i].get_width()/2, i, bars2_text[i], va='center', ha='center', size=8)\n",
    "    plt.text(budget_main_width + prem_bar[i].get_width()/2, i, bars3_text[i], va='center', ha='center', size=8)\n",
    "    \n",
    "# Custom X axis\n",
    "plt.yticks(r, names)\n",
    "plt.ylabel(\"LIFESTAGE\")\n",
    "plt.xlabel(\"TOTAL SALES\")\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "\n",
    "plt.title(\"Total Sales per Lifestage\")\n",
    "\n",
    "plt.savefig(\"lifestage_sales.png\", bbox_inches=\"tight\")\n",
    "\n",
    "# Show graphic\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "b14d6397",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top contributor per LIFESTAGE by PREMIUM category\n",
      "LIFESTAGE\n",
      "NEW FAMILIES                  Budget\n",
      "OLDER FAMILIES                Budget\n",
      "OLDER SINGLES/COUPLES         Budget\n",
      "YOUNG FAMILIES                Budget\n",
      "MIDAGE SINGLES/COUPLES    Mainstream\n",
      "RETIREES                  Mainstream\n",
      "YOUNG SINGLES/COUPLES     Mainstream\n",
      "Name: PREMIUM_CUSTOMER, dtype: object\n"
     ]
    }
   ],
   "source": [
    "stage_agg_prem = merged_data.groupby(\"LIFESTAGE\")[\"PREMIUM_CUSTOMER\"].agg(pd.Series.mode).sort_values()\n",
    "print(\"Top contributor per LIFESTAGE by PREMIUM category\")\n",
    "print(stage_agg_prem)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1e1ae91",
   "metadata": {},
   "source": [
    "The top 3 total sales contributor segment are (in order):\n",
    "\n",
    "1. Older families (Budget) $156,864.\n",
    "\n",
    "\n",
    "2. Young Singles and Couples (Mainstream) $147,582.\n",
    "\n",
    "\n",
    "3. Retirees (Mainstream) $145,169."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "28c38bd9",
   "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></th>\n",
       "      <th>LYLTY_CARD_NBR</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>8088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>6479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">OLDER SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>4930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>4929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>4750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>4675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>4454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>4017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>3872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>3779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>3340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>2831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>2728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>2574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>2433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>2431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>2273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>1504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">NEW FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>1112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mainstream</th>\n",
       "      <td>849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>588</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         LYLTY_CARD_NBR\n",
       "LIFESTAGE              PREMIUM_CUSTOMER                \n",
       "YOUNG SINGLES/COUPLES  Mainstream                  8088\n",
       "RETIREES               Mainstream                  6479\n",
       "OLDER SINGLES/COUPLES  Mainstream                  4930\n",
       "                       Budget                      4929\n",
       "                       Premium                     4750\n",
       "OLDER FAMILIES         Budget                      4675\n",
       "RETIREES               Budget                      4454\n",
       "YOUNG FAMILIES         Budget                      4017\n",
       "RETIREES               Premium                     3872\n",
       "YOUNG SINGLES/COUPLES  Budget                      3779\n",
       "MIDAGE SINGLES/COUPLES Mainstream                  3340\n",
       "OLDER FAMILIES         Mainstream                  2831\n",
       "YOUNG FAMILIES         Mainstream                  2728\n",
       "YOUNG SINGLES/COUPLES  Premium                     2574\n",
       "YOUNG FAMILIES         Premium                     2433\n",
       "MIDAGE SINGLES/COUPLES Premium                     2431\n",
       "OLDER FAMILIES         Premium                     2273\n",
       "MIDAGE SINGLES/COUPLES Budget                      1504\n",
       "NEW FAMILIES           Budget                      1112\n",
       "                       Mainstream                   849\n",
       "                       Premium                      588"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_cust = merged_data.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"])[\"LYLTY_CARD_NBR\"].nunique().sort_values(ascending=False)\n",
    "pd.DataFrame(unique_cust)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "b179d238",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='LIFESTAGE,PREMIUM_CUSTOMER'>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5EAAAGbCAYAAABd1hTwAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAACeo0lEQVR4nOzdeZQdVb328e9DZAizMr0MaiQMXhkMEEEUvCCI8IICTsyYiwoqyCQCir4XFS8oeFEmEREZBMSrgAgCEUgYBIEOhAyMRoKXiEIYAiExQPK8f9Q+UDk53X066U53wvNZ66zU2VP9qrpZi1/vXbtkm4iIiIiIiIh2LNHfAURERERERMSiI0lkREREREREtC1JZERERERERLQtSWRERERERES0LUlkREREREREtO0t/R1ARPTMqquu6iFDhvR3GBERERGxGBszZsxU26u1qksSGbGIGTJkCB0dHf0dRkREREQsxiQ90VldlrNGRERERERE25JERkRERERERNuSREZERERERETb8kxkxCJm/JRpDDn+uv4OIyIiIiL60ORTdu3vEDqVmciIiIiIiIho20JNIiUNlnSrpOUkPSxpk1rdsZLOVeWbkh6T9KikUZI2qrWb3jTmCElnleMTJc2QtHqr9pLWkHSZpL9KGiPpLkl7tohzCUlnSJogabykeyW9q9RNlrRqObakH9b6HSPpxNr3/SWNkzRR0gOSzpe0cqkbLWl403m3kzRN0tjaZ8dSd0IZZ1wp36rWbx9JJ5TjXSR1SHqo3OPTau0OLmUPS7pH0ja1utevqxbLtbV7/Ew574OSvtB875uuY3K5b41rOKOUv1/S3aXsofq9akXSkHKPv1srW1XSq63O29T345KO76pNF32/MT/9FoSkTSRduLDPGxERERHRUwt7OetBwJW2X5Z0JHCOpA8BawGHAMOBQ4EPAO+1PUPSTsA1kjay/a82zjEV+CpwXL1QkoCrgYts71vK3gl8vMUYe5WYNrU9R9I6wMst2s0CPiHpZNtTm863M3AUsIvtKZIGAZ8F1gBe6CL+223v1jTW1sBuwOa2Z5Vkb6lak52BMyRtDJwF7Gr7YUlvAQ4uY+xGdY+3sT1V0ubA1ZK2tP2PLuJpuML2YSVBnyjpmm7ab998T4CLgM/YfqDcjw3bOO9fqa79W+X7p4GJ3XWyfQ3QXYyd+QbwX82F5XdItufM57idsj1e0jqS3mH7b709fkREREREb1nYy1n3A34HYPsG4CngQOB04ETbz1Mlf1+xPaO0GwncWfq24wJgL0lvayr/MPCK7XMbBbafsH1mizHWBJ5qJAu2nyyxNXsNOI8qWWx2AnCM7SlljNm2L7D9SJvX0RzPVNuzylhTbf8dXk9shgH3AccC37P9cGn3mu1zyhjHAV9rJHa276NK6g7tSSC2nwYmAe+cj+tYnepn3rgfD7bRZybwUG3Wdi/g141KSR8rs5v3S7pJ0hqlvD5DfWGZWb6zzEJ/qpSvKem2MjM6QdK2kk4BBpeyS8ts6EOSzqG6x2+X9LUyOz1O0rdrsVytaoZ7oqSDa+XTJX2/1N0kacsyE/1XSfU/Yvwe2LvVTSizyB2SOmbPmNbGbYuIiIiI6BsLLYmUtBSwru3JteIjge8Bq9m+RNKKwHK2JzV17wA2oj3TqRLJI5rKN6JKAtrxa+BjJZH4oaTNumh7NrCfpJUW4Hx122ru5axDgZFUycujks6R9O+19psBD9g2sDEwppNxN2pR15P7CoCkdYF1gb9003RU7RoaSfbpwCOSrpJ0iKRl2jztr4C9y4zwbODvtbo7gPfb3qy0O7aTMdYEtqGa1TyllO0L3Gh7GPBeYKzt44GZtofZbvzhYkPg4nKODYH1gS2pkvctymw6wEG2t6CaUT9c0iqlfDlgdKl7CTgJ+AiwJ/CdWowdwLatgrd9nu3htocPWrb5Vy0iIiIiYuFZmMtZV6VpGaftv0u6Bbi2m74C3EV9c90ZwFjVnlecZ0DpbKqk4hXb72uK60lJG1LNXn4YuFnSp23fPM+J7RclXQwcTjVr1upcmwCXACsA37B9RRfXMs9y1jLGFlQJxvbAFZKOt30h1VLW67sYryv1+9rq/tbL9lL1DOUs4BDbz1WToJ2aZzmr7e9IuhTYiSqB2wfYro04bwC+C/wTaL5361DdjzWplvg+3skYV5eZ5Qcbs5XAvcAFkpYs9WM76fuE7T+X453K5/7yfXmqpPI2qsSx8Yzt20v5s8Ar5RoAxgOzbL8qaTwwpHaep6mWUUdEREREDFgLcznrTKDVzNOc8sH2i8DLZbarbnOgsfRxZpnVbHgb1XOQr7P9AnAZ8OVa8cQyTqPNocAOwGqtgrU9y/b1tr9G9XzcHl1c24+Az1HNOM1zPtvjy2zX9cDgLsbpVFn+Odr2fwKHAZ8sVTtRzVQ2zrlFJ0M82KKufl+fBd5aq2u+r1eU2bmtbF81P9cAYHuS7Z9Q3fv31mbruurzCtUs6leB3zZVnwmcZXsTqmc+O5vdnFU7Vhn3NuBDwBTgEkkHdtK3/jysgJPLvRhmez3bP5e0HbAjsLXt91IlmY1YXi0zxVD9rjeWJc9h7j/kLEMnf4iIiIiIiBgoFloSWZ4pHNTGEsZTqTaJGQyganfSbaiSQoBbgf1L3WDgM8CoFuP8N1VS0fif9FuAZSR9qdZm2VYBSNpc0lrleAlgU+CJLq7tOaolsJ+rFZ8MnFaWYDbMVwIpaUNJ69eKhgFPlCW0b7H9bCk/FfiGpA0asUs6utT9APh+I2mTNAwYATSemRwNHFDqBlHd41b3db5J2lVvTF+uT7U09YXyjODF3XT/IXBc7VobVqJKAqHauKgn8bwTeNr2z4Cf88YfGV4ts5Ot3AgcJGn5MsbaZbOhlYDny2ZQ7wbe35NYig2ACfPRLyIiIiJioVnYu7OOpEoIb+qizZlUM2LjJc0G/gHsbrsxQ3ME8FNJh1PNCl1cZpTmUnYgvYqy6Y1tS9oDOF3SscAzVDNMxzX3pdoA5meSli7f76Ha9bQrP6SaIWyc/w+SVgOuL0nZC1QJwo21PtdJerUc30X1fOW2ksbW2pxEtUTzTFWvB3mN6nnEg6meq3v9Xtoep2rX28slLUu1HPW6UneNpLWBOyWZ6tm8/W0/Vbp/F/iJpAeo7usNwC+7uWaAEeW+NjSSp1Hl5wcwzvaBVEnq6ZJmlOvYz/ZsSe+gmxk42xNpvSvricD/SJoC/Bl4VxsxN2wHfK38DKZTbfIE1WZJ4yTdR7VBUj2OkZL+Dbir5MPTqRLuG4AvShoHPFJi6antKT+vrmyy9kp0DOCXz0ZERETE4k1vrLJbCCerNqg52vYBC+2kizFJ5wPn157XWyRJOhW4xPa4/o6lv5Q/WNxK9QqW17pqO3z4cHd0dCycwCIiIiLiTUnSGNvDW9Ut1JlI2/dLGiVpkO3Z3feIrtj+fH/H0BvKc6dvdu8Aju8ugYyIiIiI6G8Lezkrti9Y2OeMGOhsPwY81t9xRERERER0Z2HuzhoRERERERGLuCSRERERERER0bYkkREREREREdG2JJERERERERHRtiSRERERERER0baFvjtrRCyY8VOmMeT46/o7jIiIiFhIJp+ya3+HEDGXzERGRERERERE25JELqIkDZZ0q6RBkoZImilprKQHJV0sacnSbjtJ00pd47NX7fgfkqbUvi8laXrp29Nxdyx1s5vKjy/lu0m6X9IDZbxDurnG7SRZ0udqZZuVsmO66ftFSQfOx31dWdKXe9pvQZV78+2Ffd6IiIiIiJ7KctZF10HAlbZnSwKYZHuYpEHAH4HPAJeWtrfb3q2p/xUAkk4Epts+rVFRxmvo6bgAM20PqxeU5PM8YEvbT0paGhjSxnWOB/YCfl6+7w080F0n2+e2MXYrKwNfBs5prpA0yPbs+Ry3O9cB35X0fdsz+ugcERERERELLDORi679gN81F5Yk5x5g7d48WS+MuwLVHy2eLePNsv1IG/3+BiwjaQ1V2e3OwPWNSklfkHRvmd38raRlS/mJjdlKSaMlfV/SPZIelbRtKd+olI2VNE7S+sApwNBSdmqZDR0l6TJgfJn5PbWcc1xjNlXS8pJulnSfpPGSdi/lQyQ9LOl8SRMkXSppR0l/kvSYpC3L/TAwGmiVlCPpYEkdkjpmz5jW03sfEREREdFrkkQugiQtBaxre3KLumWArYAbasXbNi0vHTof5+zJuIObl8/afg64BnhC0uWS9pPU7u/fb4BPAx8A7gNm1equtP0+2+8FHgI+16I/wFtsbwkcCfxnKfsi8OMyazoceBI4njL7avtrpd2WwAm231PGn2b7fcD7gC9IehfwL2BP25sD2wM/1BtTuusBPwY2Bd4N7AtsAxwDfKMWYwewbavgbZ9ne7jt4YOWXanzOxURERER0ceynHXRtCrwQlPZUEljgfWB39geV6vrbNlpO+Zn3HmWswLY/rykTYAdqRKojwAj2ojh11TLb98NXE6VTDZsLOkkqmWoywM3djLGleXfMbyxjPYu4ARJ61Alo481LeVtuMf24+V4J2BTSZ8q31eiujdPAv8l6UPAHKoZ2zVKm8dtjweQNBG42bYljWfuJb1PA2t1En9ERERExICQmchF00xgmaaySSVxWw94v6SP99K5enVc2+Ntn06VQH6yzT7/AF4tfW5uqr4QOMz2JsC3mfe+NDRmL2dT/nhi+zLg41T380ZJH+6k78u1YwFfKTOVw2y/y/ZIquXFqwFblPv1z1os9ZnTObXvc5j7DznLlFgiIiIiIgasJJGLINvPA4PKEtPmuqeolmR+vZfPuUDjlmcGt6sVDQOeKHV7Sjq5myH+H3Bci41tVgCeKhv37NfDmNYF/mr7DKqltpsCL5UxO3Mj8CW9sUvtBpKWo5qRfNr2q5K2B97Zk1iKDYAJ89EvIiIiImKhyXLWRddIqufqbmpRdzVwYmMDGcqzi7X6k2z/Zj7O2e64g5vKbwC+Bxwr6adUs20v88ZS1qHAi12d2PadnVR9C7ibKiEdT9cJYLO9gP0lvQr8A/iO7efKpjcTqDbwua6pz/lUS1DvK888PgPsQbVj7e8ldQBjgYd7EEfD9rSRpG+y9kp05KXDEREREdFPVG0KGYsaSZsBR9s+oL9jWVCSfgkcZfuZ/o6lv0haA7jM9g7dtR0+fLg7OjoWQlQRERER8WYlaYzt4a3qMhO5iLJ9f3n1RF++u3ChsL1/f8cwALwD+Gp/BxERERER0Z0kkYsw2xf0dwzRO2zf298xRERERES0IxvrRERERERERNuSREZERERERETbkkRGRERERERE25JERkRERERERNuSREZERERERETbsjtrxCJm/JRpDDn+uv4OIyIi+tnkU3bt7xAi4k0qM5ERERERERHRtn5JIiUNlnSrpEHl+0aSbpH0qKTHJH1LkkrdCElntRhjsqTx5fOgpJMkLV3qhkiaKWls7XNgU79xJYZ3dhLjQbV2EyTtXsovlPSpcjxaUketz3BJo2vftyxtHpN0n6TrJG1S6k6UdEyL885uivv4Ur6bpPslPVCu95BanzUljSzHG0j6g6S/SHpI0q8lrVHqtpF0j6SHy+fg2hivX1etbHqL+/mgpHMlLVHKJ7S4hgslPV67hjtL+RqSrq1dwx9a3fumsSZLur2pbGyr8za1WUvSb7obv5O+IyStNT9955ekpSTdJimrAyIiIiJiQOuv/2E9CLjS9mxJg4FrgC/ZHilpWeC3wJeBs7sZZ3vbUyUtD5xXPp8tdZNsD+um37eBbwJfqFdKWgc4Adjc9rQy/mqdjLW6pF1sX980xhrAr4F9bTeSqG2AocD4Lq5pZnPckpYs17al7SdLsjyk1mRn4EZJywDXAUfb/n3puz2wWknKLwP2sH2fpFVLnym221kbOcn2sJLk3ALsAdzXRfuv2W5O4r4D/NH2j0tsm7ZxXoAVJL3d9v9K+rd2Otj+O/Cpbhu2NgKYAPy9uULSINuz53PcTtl+RdLNwF7Apb09fkREREREb+mv5az7Ab8rx/sCf7I9EsD2DOAw4Ph2B7M9HfgisIekt/UgjruAtVuUrw68BExvjG/78U7GOJUqEW12GHBRI4Es49xh++oexNewAlXC/2wZZ5btR2r1OwPXU93LuxoJZGk7yvYE4FDgQtv3lfKpwLH04D6Xfq8BdwLrzcd1rAk8WRtrXJv9fk2VXAHsA1zeqCizobeXmd77JH2gVj6hHI+QdKWkG8qs8A9K+aAyazqhzDofVWZjhwOXlhnPwWU29P9JugP4tKSdJN1Vzvc/5Y8MlDb3lvHOK4l7Y8b69DLT+JCk95V4HpN0Uu06r6b6byMiIiIiYsBa6EmkpKWAdW1PLkUbAWPqbWxPApaXtGK749p+EXgcWL8UDW1aFrpti247U/2Pe7MHgH8Cj0v6haSPdXHqu4BZZcavbiO6nqnrzOCmuPey/RzVbO0Tki6XtJ+kJaBKhIANbT8IbEzTvWyKp7muo5S3rcwU70DXs6kAp9auoTGzdjbwc0mjJJ3QgyWjvwE+UY4/Bvy+Vvc08BHbm1Mlmmd0MsawUr8JsJekt5eytW1vbHsT4Bdl9rQD2M/2MNszS/9/2d4GuInqjwY7lnN2AEeXNmfZfp/tjYHBwG61879i+0PAuVR/QDmU6uc1QtIqpc0E4H2tgpd0sKQOSR2zZ0zr9EZFRERERPS1/ljOuirwQu27AHfStrPyzqh23NVy1lFluenTtJhFLMtsd6b6H/odgNMlbWH7xE7GO6mMc1yngUl3AysCI20f0cU1zLOctcT0eVXPU+4IHAN8hGrZ5VbA3V2M93oItL6fbvq3VR2UpLyU/c729ZKGdHG+eZaz2r5R0rpUyfsuwP2SNrb9TDexPwc8L2lv4CFgRq1uSeAsScOA2cAGnYxxs+1pAJIeBN4JTATWlXQm1TLgkV3EcEX59/3Ae4A/lYnGpaj+kACwvaRjgWWBt5XxGwnvNeXf8cBE20+VWP4KvB14tvzevSJpBdsv1U9uu7Fcm6XXXL+n/11ERERERPSa/ljOOhNYpvZ9ItXywdeVRGN68/9Id0XSClTPCT7aRvPteSOJ+E6rBq7cY/tkYG/gk50NZvsWqmt6f614IrB5rc1WwLeAldqIr7PzjLd9OlUC2YhnF+CG2jm36KT7PPe5tH2wHD8LvLVRUZYFT621nVRm5jbrIplu5xqes32Z7QOAe4EPtdn1CqqZzMubyo+imjV+L9X1LdVJ/1m149nAW2w/X/qNppoZPL+L879c/hXVc53Dyuc9tj9Xnkc9B/hUmdX8GXP/njfOP6cpljnM/cecpYF/dRFHRERERES/WuhJZPkf90Hlf7qh2kRkG0k7QrVzK9WSxB+0O2Z5Ju0c4OoyfjtxzASOBA5sfo5S1c6em9eKhgFPdDPk96ieMWw4m2qp4gdqZcu2E1szSctL2q6TeHYAbi7HlwEfkLRrre/OZQazEc+wUr4K8H3euM+jqZZ5NpKwEcCo+Ym3i+v4cFkO20j6hwJ/K98f7qb7VSXWG5vKVwKesj0HOAAY1IN4VgWWsP1bqgS/8TN/ieo51Fb+DHxQ0npljGUlbcAbCWNjo6ceb+pTfibP2H61p30jIiIiIhaW/tqddSSwDXCT7ZmqXp9xpqSzqZKAS4D6az1GSNqj9r0x4zeqbF6yBFWS8d1am8byy4YLbM/1vJztpyRdTjULVe+7JHBaeWbvX8AzVBv3dMr2HyQ9U/v+D0l7Ad+XtDbV0tmpzD3z+U1JR9b6rEN5JrLW5gZKgirpp1QzuS9T3ZPVqJ7Ve7H0nylpN+BHkn4EvAqMA46w/U9J+wM/KwmcgB81NuGxfa2kLYAxkmYDk7q75mJDSU/Wvh9V/j1VUn2p8JZUM59nSXqN6md2vu17SzJXX4o8jzIr/X2Asoy04Rzgt5I+TZX0vjxv706tDfyi8Xwp8PXy74XAuZJmAls3xfGMpBHA5SqvlAG+aftRST+jWq46mWqWtae2B7p97ckma69ER14wHRERERH9RPbCf7xK0mZUr6E4YKGffDFSksJ1bJ/S37EsiJL4rtuc5L/ZSLoS+HrTzrvzGD58uDs6OrpqEhERERGxQCSNsd38OBzQTzORtu8vO3T2yTv33ixs/7K/Y+gNtq/t7xj6W1lGfHV3CWRERERERH/rr+Ws2L6gv84dMdDYfgW4uL/jiIiIiIjoTn/szhoRERERERGLqCSRERERERER0bYkkREREREREdG2JJERERERERHRtiSRERERERER0bZ+2501IubP+CnTGHL8df0dRkRE9LPJp+za3yFExJtUZiIjIiIiIiKibYtdEilpsKRbJQ0q3zeSdIukRyU9JulbklTqRkg6q8UYkyWNL58HJZ0kaelSN0TSTElja58Dm/qNKzG8s5MYD6q1myBp91J+oaRPlePRkjpqfYZLGl37vmVp85ik+yRdJ2mTUneipGNanHd2U9zHl/LdJN0v6YFyvYfU+qwpaWQ53kDSHyT9RdJDkn4taY1St42keyQ9XD4H18Z4/bpqZdNb3M8HJZ0raYlSPqHFNVwo6fHaNdxZyteQdG3tGv7Q6t43jdX4eY0t/+7eXZ+m/i1j7EH/IyUtW/t+k6S3zu94ERERERELw+K4nPUg4ErbsyUNBq4BvmR7ZPkf9t8CXwbO7mac7W1PlbQ8cF75fLbUTbI9rJt+3wa+CXyhXilpHeAEYHPb08r4q3Uy1uqSdrF9fdMYawC/Bva13UiitgGGAuO7uKaZzXFLWrJc25a2nyzJ8pBak52BGyUtA1wHHG3796Xv9sBqJSm/DNjD9n2SVi19pthuZ93lJNvDJL0FuAXYA7ivi/Zfs/2bprLvAH+0/eMS26ZtnBfe+HltCIwEftdmv95wJPBLYEb5fgnV7+b3FmIMERERERE9stjNRAL78UYisC/wJ9sjAWzPAA4Djm93MNvTgS8Ce0h6Ww/iuAtYu0X56sBLwPTG+LYf72SMU6kS0WaHARc1Esgyzh22r+5BfA0rUP0x4dkyzizbj9Tqdwaup7qXdzUSyNJ2lO0JwKHAhbbvK+VTgWPpwX0u/V4D7gTWm4/rWBN4sjbWuB72XxF4HuadYZR0jKQTy/EWZbbzLqrrbrRZtszMjpN0haS7JQ0vdTtJuqvMGP+PpOUlHQ6sBYySNKoMcw2wT4+vPCIiIiJiIVqskkhJSwHr2p5cijYCxtTb2J4ELC9pxXbHtf0i8Diwfika2rQsdNsW3XYGrm5R/gDwT+BxSb+Q9LEuTn0XMKvM+NVtRNczdZ0Z3BT3Xrafo0penpB0uaT9JC0BoGpJ8Ia2HwQ2puleNsXTXNdRyttWZop3oOvZVIBTa9dwaSk7G/i5pFGSTpC0VpunHVUSxltpnbA3+wVwuO2tm8q/DDxve1Pgu8AW5ZpWLePuaHtzqvtytO0zgL9TzYRuD2D7eWBpSas0n1TSwZI6JHXMnjGtzUuLiIiIiOh9i9ty1lWBF2rfBbiTtp2Vd0a1466Ws44qy02fpkVSUpbZ7gy8jyphOl3SFrZP7GS8k8o4x3UamHQ31UzaSNtHdHEN8yxnLTF9XtXzlDsCxwAfAUYAWwF3dzHe6yHQ+n666d9WdVCS8lL2O9vXSxrSxfnmWc5q+0ZJ61Il77sA90va2PYz3cTeWM46FLhZtedOm0laCVjZ9q2l6JJyLoBtgB+XWCZIasyEvh94D/CnatUvS1H9caAzT1PNUD7bdH2NJdUsveb6Pf3djYiIiIjoNYvVTCQwE1im9n0iMLzeoCQa022/1O6gklagek7w0Taabw+8s5z7O60auHKP7ZOBvYFPdjaY7Vuorun9teKJwOa1NlsB3wJWaiO+zs4z3vbpVAlkI55dgBtq59yik+7z3OfS9sFy/Czw+oYxZVnw1FrbSbaH2d6si2S6nWt4zvZltg8A7gU+1IO+k6hmiN8DvMbc/200fqe6+qOEuij/Y7m+YbbfY/tzXYSyDNXvcURERETEgLRYJZFlOeCgsgkMwKXANpJ2hGrnVuAM4Aftjlk2vjkHuLqM304cM6k2TTmw+TlKSWtJ2rxWNAx4opshv0f1jGHD2cAISR+olS3LfCjP523XSTw7ADeX48uAD0jatdZ35zKD2YhnWClfBfg+b9zn0cBeZbkxVLOcjecAe4WkDzd2Oi1J/1Dgb+X7w230Xx14F9W1/5NqU6NVykZDuwHYfgGYVjYxgur524Y7gM+Usd4DbFLK/wx8UNJ6pW5ZSRuUupeonkltxCDg/wCTe3LtEREREREL0+K2nBWqHTa3AW6yPVPVaxvOlHQ2MIhqCWL9tR4jJO1R+96Y8RtV/qd+CeAqqufcGhrLLxsuKM+4vc72U5Iup9p8pd53SeC08szev4BnqDbu6ZTtP0h6pvb9H5L2Ar4vaW2qJZBTmXvm85uSjqz1WYfyTGStzQ2UBFXST6lmwF6muierAf8qz4NS7uVuwI8k/Qh4FRgHHGH7n5L2B35WEjgBP2pswmP7WklbAGMkzQYmdXfNxYaSnqx9P6r8e6qk+lLhLalmPs+S1JhFPN/2veWZxM5mCaH6Oc+m+rkcb/ufAJK+Q7WU93GgnoT+B3CBpBnAjbXyc4CLyjLW+8u9mWb7GUkjgMtLQgrV8uRHqZanXi/pqfJc5BbAn8sGQ53aZO2V6MgLpiMiIiKin8hevB6vkrQZ1cYlB/R3LIuykhSuY/uU/o5lQZTEd93mJL8PzjMIWNL2vxrPVwIb2H6lB2P8GLjG9s1dtRs+fLg7Ojq6ahIRERERsUAkjbHd/MgasBjORNq+v+zQOcj27P6OZ1Fl+5f9HUNvsH3tQjrVslSzmktSzXx+qScJZDGhuwQyIiIiIqK/LXZJJIDtC/o7hnhzKRs1tfxLTQ/G+FkvhRMRERER0WcWq411IiIiIiIiom8liYyIiIiIiIi2JYmMiIiIiIiItiWJjIiIiIiIiLYliYyIiIiIiIi2LZa7s0YszsZPmcaQ46/r7zAiIqKXTD5l1/4OISKiRzITGREREREREW1bpJJISYMl3SppUPm+kaRbJD0q6TFJ35KkUjdC0lktxpgsaXz5PCjpJElLl7ohkmZKGlv7HNjUb1yJ4Z2dxHhQrd0ESbuX8gslfaocj5bUUeszXNLo2vctS5vHJN0n6TpJm5S6EyUd0+K8s5viPr6U7ybpfkkPlOs9pNZnTUkjy/EGkv4g6S+SHpL0a0lrlLptJN0j6eHyObg2xuvXVSub3uJ+PijpXElLlPIJLa7hQkmP167hzlK+hqRra9fwh1b3vmmsxs/rAUkjJf2f7vr0lKSPN+5zL4x1mKT/6I2xIiIiIiL60qK2nPUg4ErbsyUNBq4BvmR7pKRlgd8CXwbO7mac7W1PlbQ8cF75fLbUTbI9rJt+3wa+CXyhXilpHeAEYHPb08r4q3Uy1uqSdrF9fdMYawC/Bva13UiitgGGAuO7uKaZzXFLWrJc25a2nyzJ8pBak52BGyUtA1wHHG3796Xv9sBqJSm/DNjD9n2SVi19pthuZ03lJNvDJL0FuAXYA7ivi/Zfs/2bprLvAH+0/eMS26ZtnBfe+Hn9F/AN4PBGRbku2Z7T5ljzsH0N1e9gb7gA+BPwi14aLyIiIiKiTyxSM5HAfsDvyvG+wJ9sjwSwPQM4DGh7Zsj2dOCLwB6S3taDOO4C1m5RvjrwEjC9Mb7txzsZ41SqRLTZYcBFjQSyjHOH7at7EF/DClR/KHi2jDPL9iO1+p2B66nu5V2NBLK0HWV7AnAocKHt+0r5VOBYenCfS7/XgDuB9ebjOtYEnqyNNa6H/W8D1iszoA9JOocqkX27pK9JurfMHH8bXp9BfVjS+WU2+VJJO0r6U5kd3rK0e322u3lGtjYbu12Zuf61qhnzUyTtV2Z2x0saWq5pBjC5MXZERERExEC1yCSRkpYC1rU9uRRtBIypt7E9CVhe0ortjmv7ReBxYP1SNLRpWei2LbrtDFzdovwB4J/A45J+IeljXZz6LmBWmfGr24iuZ+o6M7gp7r1sP0c1U/aEpMtL8rIEgKolwRvafhDYmKZ72RRPc11HKW9bmSnega5nUwFOrV3DpaXsbODnkkZJOkHSWj05N7Bb7bwbAhfb3qwcrw9sCQwDtpD0odJuPeDHwKbAu6kS7W2AY6hmNXvivcARwCbAAcAGtrcEzge+UmvXAbT6fUPSwZI6JHXMnjGth6ePiIiIiOg9i9Jy1lWBF2rfBbiTtp2Vd0a1466Ws44qy02fpsUsYllmuzPwPqqE6XRJW9g+sZPxTirjHNdpYNLdwIrASNtHdHEN8yxnLTF9XtXzlDtSJUAfAUYAWwF3dzHe6yHQ+n666d9WdVCS8lL2O9vXSxrSxfnmWc5q+0ZJ61Il77sA90va2PYz3cQ+StJsYBzVfV4ZeML2n0v9TuVzf/m+PFVS+TfgcdvjASRNBG62bUnjmXtJcDvutf1UGWsSMLKUjwfqf0R4miphnYftxrJrll5z/Z7+fkdERERE9JpFZiYSmAksU/s+ERheb1ASjem2X2p3UEkrUCUFj7bRfHvgneXc32nVwJV7bJ8M7A18srPBbN9CdU3vrxVPBDavtdkK+BawUhvxdXae8bZPp0ogG/HsAtxQO+cWnXSf5z6Xtg+W42eBtzYqyrLgqbW2k2wPs71ZF8l0O9fwnO3LbB8A3At8qLs+VM9EDrN9oO0XStnLtXoBJ5c2w2yvZ/vnpW5Wrd2c2vc5tP7jy2uU/57K85ZL1eraHWsZqt/ziIiIiIgBa5FJIm0/Dwwqm8AAXApsI2lHqHZuBc4AftDumGXjm3OAq8v47cQxEzgSOLD5OUpJa0navFY0DHiimyG/R/WMYcPZwAhJH6iVLdtObM0kLS9pu07i2QG4uRxfBnxA0q61vjuXGcxGPMNK+SrA93njPo8G9irLjaGa5Rw1P/F2cR0fLsthG0n/UKrZQiQ9vABD3wgcVH4PkLS2pNXnc6zJvJGI7w4sOR9jbADMs2ttRERERMRAsigtZ4VqGeA2wE22Z6p6fcaZks4GBgGXAPXXeoyQtEfte2PGb1SZLVoCuAr4bq1NY/llwwW2z6gHYfspSZdTbTpT77skcFp5Zu9fwDNUG/d0yvYfJD1T+/4PSXsB35e0NtUSx6nMPfP5TUlH1vqsQ3kmstbmBkqCKumnVDNcL1Pdk9WAf5XnQSn3cjfgR5J+BLxKtQT0CNv/lLQ/8LOSwAn4UWMTHtvXStoCGFOWjk7q7pqLDSU9Wft+VPn3VEn1pcJbUiVnZ0lqzPadb/teVTvF1pci90jZ1fffgLuqXwemA/sDs+djuJ8Bv5N0D1Vy/nI37Vv5IPDt7hptsvZKdOTF1BERERHRT2QvOo9XSdqM6jUUB/R3LIuykhSuY/uU/o5lQZTEd93mJH9R1JPf7eHDh7ujo6O7ZhERERER803SGNvNj7UBi9hMpO37yw6dg2zPz2xRALZ/2d8x9Abb1/Z3DL1oVapnXyMiIiIiBrRFKokEsH1Bf8cQ0dts/7G/Y4iIiIiIaMcis7FORERERERE9L8kkREREREREdG2JJERERERERHRtiSRERERERER0bYkkREREREREdG2RW531og3u/FTpjHk+Ov6O4yIiOihyafs2t8hRET0isxERkRERERERNuSRA4gkgZLulXSoPJ9I0m3SHpU0mOSviVJpW6EpLNajDFZ0vjyeVDSSZKWLnVDJM2UNLb2ObCp37gSwzs7ibHRrtH/A6V8T0mW9O5a2yGl7Lu1slUlvdqIXdKJko4pxxdK+lTT+YZImlCOt5M0rSn+HUvdCZImlvjHStqqm3t9oqQppe3Dkn4iqUf/PUgaLWl4T/rU+m7XuHfl+2GS/mN+xoqIiIiIWJiSRA4sBwFX2p4taTBwDXCK7Q2A9wIfAL7cxjjb294E2BJYFzivVjfJ9rDa5+KmfpsCo4FvdjN+o/+dpWwf4A5g76a2fwV2q33/NDCxjWvozO1N8d8kaetyjs1L/DsC/9vGWKfbHga8B9gE+PcFiKuntqP6eTZcABy+EM8fERERETFfkkQOLPsBvyvH+wJ/sj0SwPYM4DDg+HYHsz0d+CKwh6S39SCOu4C1220saXngg8DnmDeJnAk8VJux2wv4dQ9iaceawFTbswBsT7X99x70XwpYBnge5p5hLDOnk8vxYEm/KrOdVwCDGwNI+lyZMR4t6We1mdbVJP1W0r3l80FJQ6h+LkeVmdBty893sqQtF/RmRERERET0pSSRA4SkpYB1bU8uRRsBY+ptbE8Clpe0Yrvj2n4ReBxYvxQNbVoOum2LbjsDV3cx7KjS9+7yfQ/gBtuPAs9J2ryp/a+AvSWtA8wGepLgNdu2Kf6hwEjg7SWJO0dSuzOKR0kaCzwFPGp7bDftvwTMKLOd3wO2AJC0FvAt4P3AR4B31/r8mGrG833AJ4Hzy8/43FI+zPbtpW0H0OrngaSDJXVI6pg9Y1qblxcRERER0fuyO+vAsSrwQu27AHfStrPyzqh2PKks4WxllKQ1gKfpfjnr1Nr3fYAfleNfle/31epvAL4L/BO4ov2wW7rd9m7NhZK2oErAtgeukHS87Qu7Get026dJWhL4jaS9bf+qi/YfAs4AsD1O0rhSviVwq+3nSiz/A2xQ6nYE3lMeZQVYUdIKnYz/NHMnoK+zfR5lWfLSa67f059/RERERESvSRI5cMykWlLZMJEqaXmdpHWB6bZfqiUlXSoJyxDgUWClbppvD7wMXAh8Bzi6jfFXAT4MbCzJwCDAko5ttLH9iqQxwFepZlg/1lbwPWB7NtWznKMljQc+S3Ud7fR9VdINVPf7V8BrvDFLv0xz8xZDdPXDWALY2vbMuTq0/vktQ/V7EBERERExYGU56wBh+3lgkKRG0nIpsE1t99HBVLNgP2h3zPKs4jnA1WX8duKYCRwJHNjmc5SfAi62/U7bQ2y/nWr57DZN7X4IHGf72Xbjb5ekDSWtXysaBjxR6k6WtGc3/UW1yc2kUjSZslSV6voabqN6bhVJGwOblvJ7gH+X9FZJb6FattowkupZ1sa5hpXDl4DmGckNgAldxRoRERER0d8yEzmwjKRKvm6yPVPS7sCZks6mmuG7BKi/1mOEpD1q399f/h1VEqMlgKuolpI2DC3PATZcYPuMehC2n5J0OXBoU99W9gFOaSr7LdXGQN+vjTmR9nZl/amkH5Xj/y3j123bFP9JVEnrmZJWpppF/AtwcKnfhGqX21aOkrQ/sCQwjirhBjgN+LWkA4Bbau1/AvyiLGMdS5U8YnuKpP8C7qZ63vNBoPHg4uHA2aXPW6gS0S8Cv6daQrs78JXyXOQHgW93dmMaNll7JTrywuqIiIiI6Cey83jVQCFpM+Bo2wf0dyyLC0k32v7oQjjP8ranl5nIq6iS86t60L/tn/3w4cPd0dGxANFGRERERHRN0hjbLd+JnuWsA4jt+6lmEQf1dyyLi4WRQBYnlhnSCVQzo1f3sP+qVDu8RkREREQMaFnOOsDYvqC/Y4ies33MAvb/Y2/FEhERERHRlzITGREREREREW1LEhkRERERERFtSxIZERERERERbUsSGREREREREW1rK4mUNEjSqrXvS0k6WNJDfRdaREREREREDDTdJpGS9gaeA8ZJulXS9sBfgV2A/fo4voiIiIiIiBhA2nnFxzeBLWz/RdLmwF3A3j15kXpE9J7xU6Yx5Pjr+juMiIg3lcmn7NrfIUREDBjtLGd9xfZfAGzfBzyeBHLxJmlwmXUeJGmIpJmSxkp6UNLFkpYs7baTNK3UNT571Y7/IWlK7ftSkqaXvj0dd8dSN7up/PhSvpuk+yU9UMY7pJtrrJ9jnKSbJK3ew/t0oqT5ej9kuf59a983kXTh/IwVEREREbEwtTMTubqko2vfl69/t/3fvR9W9LODgCttz5YEMMn2MEmDgD8CnwEuLW1vt71bU/8roEqygOm2T2tUlPEaejouwEzbw+oFJfk8D9jS9pOSlgaGtHGdr59D0snAocB/ttGvNwwB9gUuA7A9XtI6kt5h+28LKYaIiIiIiB5rZybyZ8AKtU/z91j87Af8rrnQ9mzgHmDt3jxZL4y7AtUfRJ4t482y/Ui7nVVltisAz5fvc80wSpogaUg5PkHSI5JuAjastXlfmdG8S9KpkiaU8kHl+72lvjFDegqwbZkJPaqU/R7Ye/5uQURERETEwtHtTKTtby+MQGJgkLQUsK7tyS3qlgG2Ao6oFW8raWzt+ydtT+rhOXsy7uCm8pNtXyHpGuAJSTcD1wKX257Tzakb51gFeBn4RjdxbkGV5G1G9d/OfcCYUv0L4GDbd0o6pdbtc8A02+8rM6R/kjQSOB44pmm2taOU/6DFuQ8GDgYYtOJq3VxWRERERETfaWd31l/Xjr/fVDeyL4KKfrUq8EJT2dCSbD0L/M32uFrd7baH1T49SSDnZ9yZTeVXANj+PLAD1YzmMcAFbZy/cY63UyWB8yRvTbYFrrI9w/aLwDUAklYGVrB9Z2l3Wa3PTsCB5TrvpkpY1+9k/KeBtVpV2D7P9nDbwwctu1L3VxYRERER0UfaWc5a/x/ejzTVZUpk8TMTWKapbFJ5DnE94P2SPt5L5+rVcW2Pt3061e/pJ3vY/RrgQ+X4Neb+b6N+P9yir1qU1eu+Ukt632W7sz++LEN1/yMiIiIiBqx2kshW/9PcTl0sgmw/DwwqS0yb656iWm759V4+5wKNK2l5SdvVioYBT5S6PcumOd3ZBmjMdk4GNi/9NwfeVcpvA/Ysu9euAHysxP888JKk95d29ecabwS+VNt5dgNJywEvMe8zxRsAE9qINSIiIiKi37SzO+uykjajSjgHl2OVz+C+DC76zUiqpOqmFnVXAydK2rZ8b3528STbv5mPc7Y7bvMzkTcA3wOOlfRTqpm8l4ERpX4o8GIn52ycQ8A04POl/Le8sQT1XuBRqF5xI+kKYCxVknp7bazPAT+T9DIwuowHcD7VTqz3lQ18ngH2AMYBr0l6ALiwzKBuD+QFkBERERExoMnuejJR0mi6mHG0vX0vxxT9rPyh4GjbB/R3LAtK0i+Bo2w/08fnWd524x2YxwNr2j6im271/ksDtwLb2H6tq7bDhw93R0fHAsUbEREREdEVSWNsD29V187urNv1ekQxoNm+X9IoSYPK6zcWWbb3X0in2lXS16n+m3qCN2ZC2/UO4PjuEsiIiIiIiP7WbRIp6RNd1du+svfCiYHCdju7m0ZRdom9YgH6PwY81nsRRURERET0jXaeifwN1TNgY8v3+k6UBpJERkREREREvEm0k0R+EtgL2BT4HdVL3P/Sp1FFRERERETEgNTtKz5sX2V7b+DfqV6B8ENJd0j69z6PLiIiIiIiIgaUdt4T2fAvqtcWvAgsx7wvpI+IiIiIiIjFXDsb62wP7ANsSfXewB/bzvsFIiIiIiIi3oTaeSbyZqoXo98BLE31EvYDG5W2D++j2CIiIiIiImKAaSeJ/I8+jyIi2jZ+yjSGHH9df4cREdHnJp+ya3+HEBERLbSzsc5FjQ/wW+A3TWXRCyQNlnSrpOUkPSxpk1rdsZLOVeWbkh6T9KikUZI2qrWb3jTmCElnleMTJc2QtHqr9pLWkHSZpL9KGiPpLkl7tohziKSZksbWPkuVuh9LmiJpiVr7EZIsaYda2Z6l7FPl+2hJw8vxZEmrdnMdU5rOv7KkZSVdKmm8pAll86flu7nnoyU9UsZ4SNLBXbXvZIzp3bfqtO8ISWvVvv9K0vrzO15ERERExMLQ1sY6kr4k6W/AE8DfJD0h6ct9G9qbzkHAlbZfBo4EzilJ49rAIcDXgUOBDwDvtb0BcDJwjaR2NzmaCny1uVCSgKuB22yva3sLYG9gnU7GmWR7WO3zSkkc9wT+F/hQU/vxVM/VNuwNPNBmzK2c3nT+F4AjgH/a3sT2xsDngFfbGGs/28OADwLfbyTEC8kIYK3a958Axy7E80dERERE9Fi3SaSkbwIfA7azvYrtVYDtgV1KXfSO/ajew4ntG4CngAOB04ETbT8PHAd8xfaM0m4kcGfp244LgL0kva2p/MPAK7bPbRTYfsL2mT2If3tgAlUitE9T3e3AlpKWLLOD6wFjezB2O9YEpjS+2H7E9qwe9F8eeBmYDfPM0n5K0oXl+F1llvZeSd+ttVlC0jmSJkq6VtIfajOtW5RZ5jGSbpS0ZqkbDlxaZkIHU92nHSW1s8w8IiIiIqJftDMTeQDwCdt/bRSU489QJTmxgMrs17q2J9eKjwS+B6xm+xJJKwLL2Z7U1L0D2Ij2TKdKJI9oKt8IuK8HIQ+tLSU9u5TtA1wOXAXsJmnJWntT7ez7UWB34JoenKuVo2rnH1XKLgCOKwneST1YFnqppHHAI8B3bc/upv2PgZ/Yfh/wj1r5J4AhwCbA54GtAcp9OBP4VJnhvQD4nu3fUP3s9iuzqTNtzwH+Ary3+aSSDpbUIalj9oxpbV5aRERERETva2s5q+1/tSibCczp9YjenFYFXqgX2P47cAvVzF5XRJWkdaa57gzgsyUpbT2gdLakByTd20mT+nLWQ0sS/H+Bq22/CNwN7NTU51dUy1j3pko2F0R9Oev2ALbHAusCpwJvA+6V9G9tjLWf7U2BdwDHSHpnN+0/yBvxX1Ir3wb4H9tzbP8DaCS3GwIbA3+UNBb4Jp0vEwZ4mrmXuAJg+zzbw20PH7TsSt1dU0REREREn2ln2dyTknawfXO9UNKHqZZcxoKbCbR6rnFO+WD7RUkvS1q3PisMbA7c2hhH0lK2Xynf30b1HOTrbL8g6TKg/kzrROCTtTaHls1t2n0f6M7ASsD46vFKlgVmAK9vIWr7HkkbAzNtP1ra9Srb04ErgSslzaFKbB9qs+8zku4DtqJ69reefDf/bFol7Z1dkICJtrduJ45yrpltto2IiIiIWOjamYk8HPippAslfUXSYZIuAs4DDuvb8N4cyvOOg9rYIOdU4Izy/BySdqSaAbus1N8K7F/qBlMtOR7VYpz/ptqsp/FHhFuAZSR9qdZm2R5cwj7A520PsT0EeBewk6TmMb4OfKMH47ZN0gclvbUcLwW8hyoZRNLNZYOirvovC2wGNJYL/1PSv9U2DGr4E9VsKsz9LOodwCfLs5FrANuV8keA1SS9vrxVb+yo+xKwQlMoG1Al9RERERERA1K3M5G2J5YZpH2pnp0TcBtwSKtlrjHfRlIlhDd10eZM4K1UM36zqZ7J270sLYbqWcefSjqc6ud0se3bmgexPVXSVcBR5bsl7QGcLulY4BmqTWaO6y7oknx9lCopbYz/sqQ7qDZkqp/3+u7GK8aVmUSAXwPjmuqPkrR/7fsewFDgJ2Wn2SWoZkF/W5LA9YDnOjnXpZJmAksDF9oeU8qPB66l2m12AtXGO1Dd48skHUH1ypuG3wI7lLaPUi3pnVZ2rv0UVfK/EtV/cz+iShQvBM4t598aWJFqpjYz/BERERExYMnu6nE6kDTSdvPzbdHLJG0GHG37gP6OZXFS/gBykO2jF8K5lrc9XdIqwD3AB8vzke32Pwp40fbPu2o3fPhwd3S0u9I4IiIiIqLnJI2xPbxVXTvPRK7Wy/FEC7bvlzRK0qA2dgiNNtmeAPR5AllcK2llYCmqnV7bTiCLF5h7s56IiIiIiAGnnSRyJUmf6KzS9pW9GM+bmu0L+juGmH+2t1vA/r/opVAiIiIiIvpMW0kksButd5801W6YERERERER8SbQThL5hO2D+jySiIiIiIiIGPDaecVH77/QLyIiIiIiIhZJ7SSRc+0WKmkVSXtK2qKPYoqIiIiIiIgBqp0k8pTymgQkrUn1HryDgEskHdmHsUVERERERMQA004S+a7ymgSA/wD+aPtjwFZUyWRERERERES8SbSzsc6rteMdgJ8B2H5J0pw+iSoiOjV+yjSGHH9df4cRETFfJp+ya3+HEBERC6idJPJ/JX0FeBLYHLgBQNJgYMk+jC0iIiIiIiIGmHaWs34O2AgYAexl+4VS/n4gL0dfBEkaLOlWSYMkDZE0U9JYSQ9KuljSkqXddpKmlbrGZ6/a8T8kTal9X0rS9NK3p+PuWOpmN5UfX8p3k3S/pAfKeId0c42Nc9wv6SFJ/9lH9/J8Se/ppbFukvTW3hgrIiIiIqKvdDsTaftp4IstykcBo/oiqOhzBwFX2p4tCWCS7WGSBgF/BD4DXFra3m57t6b+VwBIOhGYbvu0RkUZr6Gn4wLMtD2sXlCSz/OALW0/KWlpYEgb13m77d0kLQeMlXSt7TG1cd9i+7U2xumU7c8vSP8mlwBfBr7Xi2NGRERERPSqbpNISb8HXCsyMBUYZfuXfRVY9Kn9gH2bC0tSeQ+wdm+erBfGXYHqd/XZMt4s4JEenP9lSWOAoZI+BqxFlYROlXQEcC7wjtL8SNt/Kgnyu4A1gQ2Ao6lm33cBpgAfs/2qpNHAMbY7JE23vTyApE8Bu9keIelCYCbwbuCdVBtUfRbYGrjb9ohy7muA22mRREo6GDgYYNCKq7V76RERERERva6dZyJPa1H2NmB/SRvbPr6XY4o+JGkpYF3bk1vULUO16+4RteJtJY2tff+k7Uk9PGdPxh3cVH6y7SskXQM8Ielm4FrgctttbewkaRWqBPC7wHuALYBtbM+UdBlwuu07JL0DuBH4t9J1KLB96XNXifFYSVcBuwJXt30T4K3Ah4GPA78HPgh8HrhX0jDbY20/L2lpSavYfrbe2fZ5VLOxLL3m+iYiIiIiop+0s5z11lbl5X/qxwBJIhctqwIvNJUNLYnb+sBvbI+r1XW27LQd8zPuPMtZoVo2KmkTYEfgGOAjVM/pdmVbSfcDc4BTbE+U9GngGtszS5sdgffUluGuKGmFcnx9mW0cDwyibCoFjKe95bR1v7ftMtY/bY8HkDSxjDW2tHuaaqb02VaDRERERET0t3ZmIluqPU8Xi5aZwDJNZY1nF9cERkv6uO1reuFcvTpuSbzGS7oEeJzuk8jOEtWXa8dLAFvXkkrg9Wc7Z5XzzpH0qu3GDOAcWv+3U58hbL7Hs2p9Z9XKm8dahupnFBERERExIHW7O6ukt7X4DJX0bWDiQogxepHt54FBZYlpc91TVDPLX+/lcy7QuJKWl7RdrWgY8ESp21PSyQsQ3kjgsNq5hi3AWP+U9G+SlgD27GlnVZnr/wEmL0AMERERERF9qp2ZyDFUMyyNacfGxjqjgS/1TVjRx0YC2wA3tai7GjhR0rble/OziyfZ/s18nLPdcZufibyBaqOZYyX9lGqW7mXemIUcCrw4H/E0HA6cLWkc1X8Pt9FiN+I2HU/1vOb/AhOA5XvYfwvgz93tGLvJ2ivRkZd1R0REREQ/0Rsr9OLNQtJmwNG2D+jvWBaUpF8CR9l+pr9jWVCSfkz1vObNXbUbPny4Ozo6FlJUEREREfFmJGmM7eGt6tp5xcf+VMnmJU3lXwBetn1Z74QZC4vt+yWNkjTI9uz+jmdB2N6/v2PoRRO6SyAjIiIiIvpbt89EAl+l9asMrih1sQiyfcGinkAubmz/rL9jiIiIiIjoTjtJ5CDbLzUX2n4RWLL3Q4qIiIiIiIiBqp0kcklJyzUXlnfpLdX7IUVERERERMRA1U4S+XPgN5KGNArK8a9KXURERERERLxJdLuxju3TJE0HbpW0PNUrPl4GTrH9k74OMCIiIiIiIgaOdt4Tie1zgXNLEqlWz0hK+qzti3o7wIiIiIiIiBg4eu09kZLus715rwwWEZ1aes31veZnf9TfYUREdGryKbv2dwgREbGAunpPZDvPRLZ9nl4cq+cnlwZLulXScpIelrRJre5YSeeq8k1Jj0l6tLwrcaNau+lNY46QdFY5PlHSDEmrt2ovaQ1Jl0n6q6Qxku6StGeLOJeQdIakCZLGS7pX0rtK3WRJq5ZjS/phrd8xkk6sfd9f0jhJEyU9IOl8SSuXutGShjeddztJ0ySNrX12LHUnlHHGlfKtav32kXRCOd5FUoekh8o9Pq3W7uBS9rCkeyRtU6t7/bpqsVxbu8fPlPM+WN4/Ote9b7qOyeW+Na7hjFL+fkl3l7KH6veqFUlDJM0s7R+QdKekDbvq02KMljG22XdlSV+ufV9N0g3zM1ZERERExMLU1nLWNvXOlOb8Owi40vbLko4EzpH0IWAt4BBgOHAo8AHgvbZnSNoJuEbSRrb/1cY5plK9G/O4eqEkUb1L8yLb+5aydwIfbzHGXiWmTW3PkbQO1TOmzWYBn5B0su2pTefbGTgK2MX2FEmDgM8CawAvdBH/7bZ3axpra2A3YHPbs0qyV991d2fgDEkbA2cBu9p+WNJbgIPLGLtR3eNtbE+VtDlwtaQtbf+ji3garrB9WEnQJ0q6ppv22zffE+Ai4DO2Hyj3o52EcJLtYeUaDgG+QXUfF4aVgS8D5wDYfkbSU5I+aPtPCymGiIiIiIgeW2xmIoH9gN8B2L4BeAo4EDgdONH281TJ31dszyjtRgJ3lr7tuADYS9Lbmso/DLxSnh2ljP2E7TNbjLEm8JTtOaXdkyW2Zq8B51Eli81OAI6xPaWMMdv2BbYfafM6muOZantWGWuq7b/D68nxMOA+4Fjge7YfLu1es31OGeM44GuNxM72fVRJ3aE9CcT208Ak4J3zcR2rU/3MG/fjwR72XxF4HuadYZR0raTtyvF/qJrFvhX4YK3NUEl/LjPL32mapf5aKR8n6dul+BRgaJkJPbWUXU37v4sREREREf2iN5PIfps9kbQUsK7tybXiI4HvAavZvkTSisBytic1de8ANqI906kSySOayjeiSrTa8WvgYyV5+KGkzbpoezawn6SVFuB8dds2LWcdCowE3l4So3Mk/Xut/WbAA64enN0YGNPJuBu1qOvJfQVA0rrAusBfumk6qnYNjST7dOARSVdJOkTSMm2cspHETQKOBv67m/jWBL5NlTx+BHhPrfrHwI9tvw/4e63PTsD6wJZUCfkWZYb8eMpMqO2vleYdwLadnPvgspS4Y/aMaW1cWkRERERE3+h2Oauko7uqt/3f5d/Deiuo+bAqTcs4bf9d0i3Atd30FV0vxW2uOwMYq9rzivMMKJ0NbEM1O/m+prieLM/efbh8bpb0ads3z3Ni+0VJFwOHAzM7OdcmwCXACsA3bF/RxbXMs5y1jLEFVfKyPXCFpONtX0i1lPX6LsbrSv2+trq/9bK9yjOUs4BDbD9XTYJ2ap7lrLa/I+lSYCdgX2AfYLtuYqwvZ92LauZ35y7abwWMtv1M6XMFsEGp2xrYoxxfBjSeF92pfO4v35enSir/1mL8p6mWOs/D9nklPpZec/3+XjoeEREREW9i7cxEngbsD6xC9T/AKzR9BoKZQKuZpznlg+0XgZfLbFfd5kBj6ePMMqvZ8Daq5yBfZ/sFqiThy7XiiWWcRptDgR2A1VoFa3uW7evLDNR/8Uby0cqPgM8By7U6n+3xJRG6HhjcxTidKss/R9v+T+Aw4JOlaieqmcrGObfoZIgHW9TV7+uzwFtrdc339YoyI7eV7avm5xoAbE8q7y7dAXivpFV60P0a4EPl+DXm/m+j/rvV0wROwMnl+obZXs/2zztpuwyd/LEgIiIiImKgaCeJ3JwqkdiV6lm1PwHfsf1t29/usudCUp4pHNTGEsZTqTaJGQyganfSbaiSQoBbqRJmSpvPAKNajPPfVBvJNGZybwGWkfSlWptlWwUgaXNJa5XjJYBNgSe6uLbnqJbAfq5WfDJwWtmUp2G+EkhJG0pav1Y0DHiiLKF9i+1nS/mpwDckbdCIvTZL/QPg+42kTdIwYARl0xhgNHBAqRtEdY9b3df5JmlXvTF9uT4wG3hB0pZlNrc721A9jwkwGRhWrvHtVEtRAe4GtpO0iqQlgU/X+v+ZN5LvvWvlNwIHqXrHKpLWLhsIvcS8f4TZAJjQRqwREREREf2m2+WstscCY4HjJX2AapngmZKOs93dLpoL00iqROCmLtqcSTUjNl7SbOAfwO62G7M/RwA/lXQ41QzSxbZvax6k7EB6FWXTG9uWtAdwuqRjgWeodlw9rrkv1QYwP5O0dPl+D9Wup135IdUMYeP8f5C0GnB9ScpeoEo+bqz1uU7Sq+X4LqrnK7eVNLbW5iTgcaqf58pUM3B/odp19SPU7qXtcap2vb1c0rJUM3LXlbprJK0N3CnJVAnS/rafKt2/C/xE0gNU9/UG4JfdXDPAiHJfG95f/h1Vfn4A42wfSJWkni5pRrmO/WzPlvQOOp/dG1ruh4BXgM+X8j+V+zKe6r7eV67zKVWvDrmLahOf+4BBpc+RwC8lfbXcl2mlz0hJ/wbcVXLc6eXeTJL0J0kTgMas9Palb0RERETEgKVqz5Q2GlZJy2eoZl9eBb5l+899GFuPlA1qjrZ9QH/HsjiQdD5w/kD6Gc+PsvPpJbbH9fF5lgVmlj8o7A3sY3v3Ho5xG9UfNVrt1vu64cOHu6OjYwGijYiIiIjomqQxtoe3qmtnY53/oHq34TLAb6jexfd074a44GzfL2mUpEG2Z3ffI7pi+/Pdtxr4ajuf9rUtgLPKktoXqN5b2rbyR5r/7i6BjIiIiIjob93OREqaQ7Wsr7Gb5FwdbH+8b0KLiFYyExkRERERfW2BZiKpntOKiIiIiIiIaGtjnVsXRiAREREREREx8LXzTOR45l7Caqp3/I0CTrP9rz6KLSIiIiIiIgaYdpaz7tai7G3AZ6lemfGFXo0oIiIiIiIiBqx2lrM+0aL4CeB+Sff3fkgRERERERExUC3Rz/0jIiIiIiJiEdLOM5Gbtyh+K7A/cFuvRxQRXRo/ZRpDjr+uv8OIiAFm8im79ncIERHxJtHOM5E/bPpu4FlgNHBebwcUERERERERA1e3y1Ftb9/0+bDtT9s+2/arXfWVNFjSrZIGSRoiyZK+W6tfVdKrks4q30+UdEw5vlDS45IekPSopIslrd00/p5lzHc3lW8pabSkxyTdJ+k6SZvUzjFF0tjaZ+Wm/ktIOkPSBEnjJd0r6V2lbrKkVcuxJf2w1u8YSSfWvu8vaZykieU6zm+cq8Q3vOm820ma1hTbjqXuhDLOuFK+Va3fPpJOKMe7SOqQ9JCkhyWdVmt3cCl7WNI9krap1b1+XbVYri3HIyQ9U877oKQv1MrPavFzn1zuW+Mazijl75d0dyl7qH6vWmnnd6aLvh+XdHxXbbro+4356bcgJG0i6cKFfd6IiIiIiJ5qZznr0V3V2/7vLqoPAq60PVsSwF+pdnv9Vqn/NDCxi/5fs/0bVZ2PBEZJ2tj2K6V+H+AOYG/gxBLvGsCvgX1t31nKtgGGAuNLv9Ntv55ctbAXsBawqe05ktYBXm7RbhbwCUkn255ar5C0M3AUsIvtKZIGUe1ouwbwQhfnvt32XDviStqa6r5tbntWSfaWqjXZGThD0sbAWcCuth+W9Bbg4DLGbsAhwDa2p6papny1pC1t/6OLeBqusH2YpNWBiZKu6ab99s33BLgI+IztB8r92LCN8/b0dwYA29cA3cXYmW8A/9VcWH4PZXvOfI7bKdvjJa0j6R22/9bb40dERERE9JZ2NsZZoZtPV/YDflf7PhN4qDYDtxdVwtclV04H/gHsAiBpeeCDwOeoksiGw4CLGglk6X+H7au7O0/NmsBTjWTB9pO2n2/R7jWqJb1Htag7ATjG9pQyxmzbF9h+pAdx1OOZantWGWuq7b/D64nNMOA+4Fjge7YfLu1es31OGeM4qqR8aqm7jyqpO7Qngdh+GpgEvHM+rmN14KkyzmzbD7bRp8vfGUkfK7Ob90u6qfwRYa5ZUlWz2mdIulPSXyV9qpSvKem2MjM6QdK2kk4BBpeyS8ts6EOSzqG6x2+X9LUyOz1O0rdrsVwtaUyZMT64Vj5d0vdL3U16Y6b8r5I+XrvW3zP373JERERExIDTznLWb3f16ayfpKWAdW1Pbqr6FbB3md2bDfy9B/HeBzSWru4B3GD7UeA5vbEB0EalXVeOqi21HNWi/tfAx0r9DyVt1sVYZwP7SVqpqbydOFrZVnMvZx0KjKRKXh6VdI6kf6+13wx4wLaBjYExnYy7UYu6jlLeNknrAusCf+mm6ajaNTSS7NOBRyRdJekQScu0edqufmfuAN5ve7PS7thOxlgT2IZqVvOUUrYvcKPtYcB7gbG2jwdm2h5me7/SbkPg4nKODYH1gS2pkvctJH2otDvI9hbAcOBwSauU8uWA0aXuJeAk4CPAnsB3ajF2ANu2Cl7VUuQOSR2zZ0zr5BIjIiIiIvpeO8tZz+iq3vbhnVStSutlmzcA3wX+CVzR3fmbw6kd7wP8qBz/qnyfJ2mTdDewIjDS9hGluMvlrLaflLQh8OHyuVnSp23f3KLti5IuBg6nmjWbN+jqecxLqGZuv2G7q+ueZzlrGWMLqgRje+AKScfbvpBqKev1XYzXFVFtlETt37p62V5lWfAs4BDbz5Ulyp2ZZzmr7e9IuhTYiSqB2wfYro04u/qdWYfqfqxJtcT38U7GuLrMLD/YmK0E7gUukLRkqR/bSd8nbP+5HO9UPo13pC5PlVTeRpU47lnK317KnwVeKdcA1ZLqWbZflTQeGFI7z9NUy6jnYfs8ykZWS6+5fqufVURERETEQtHOctYvUs3g/J1qpmRM06czM4F5ZprK84xjgK8Cv+1hvJtRLW1chSq5O1/SZOBrVEmOqJ6Xe/21JLa3onqernmmsEu2Z9m+3vbXqJ6P26OL5j+iWla7XK3s9Thsjy+zXdcDg3sSRy2e2bZH2/5PqiW7nyxVO1HNVDbOuUUnQzzYom7zUg5VsvPWWt3bgHoSeEWZndvK9lXzcw0AtifZ/gmwA/De2mxdV326+p05EzjL9iZUz3x2Nrs5q3asMu5twIeAKcAlkg7spG/9eVgBJ5d7Mcz2erZ/Lmk7YEdga9vvpUoyG7G8WmaKAeY0YilJbf0POcvQyR8iIiIiIiIGinaSyDWpZkA+ChwALAlcY/si2xd11qk8QziokyWLPwSOs/1sO0GqcniJ5QbgU1TLC99pe4jtt1PNQG1Dtbx0hKQP1IZYtp3z1M63uaS1yvESwKbAE521t/0c1RLYz9WKTwZOK0swG+YrgZS0oaT1a0XDgCfKEtq31O7jqcA3JG3QiF1vbIz0A+D7jaRN0jBgBNB4ZnI01c+XsunN/kCrpb7zTdKuemP6cn2qpakvlGcEL+6me2e/MytRJYFQbVzUk3jeCTxt+2fAz3njjw+vltnJVm4EDirP5CJpbVWbDa0EPG97hqrdgt/fk1iKDYAJ89EvIiIiImKh6XY5a/mf9nOBc1W9YmMfqt05j7N9STfdR1Ildjc1jTmRNnbYBE6V9C2qJPDPVEskX5G0D28819bwW6odWb8kaS+qhGltqiWCU5n72bOjJO1f+75H07ObqwM/k7R0+X4P1a6nXfkh1Qxh4xr/IGk14PqSlL1AlSDcWOtznaTGa1LuokqAt5U0ttbmJKoE+UxVrwd5jep5xIOpnqt7/d7aHifpSOBySctSLUe9rtRdU+7HnZJM9Wze/rafKt2/C/xE0gNUs203AL/s5pqhStj3qH1vJE+jJM0ux+NsH0iVpJ4uaUa5jv1c7dz7DrqZgevid+ZE4H8kTaH6HXlXGzE3bAd8rfwMpgONmcjzgHGS7qPaIKkex0hJ/wbcVfLh6VQJ9w3AFyWNAx4psfTU9pSfV1c2WXslOvJS8YiIiIjoJ3pjlV03DauNa/ahSlzGAD/sbnfNsiHN0bYPWNBAY16SzgfOrz2vt0iSdCpwie1x/R1Lfyl/sLiV6hUsr3XVdvjw4e7o6Fg4gUVERETEm5KkMbaHt6prZ2Odb1PtaPkQ1QY2X+/uf3IbbN8vaZSkQbZnd98jesL25/s7ht5Qnjt9s3sHcHy7/21FRERERPSXbmciJc2heuF7Y7lho4OoXuG4ad+FFxHNMhMZEREREX1tgWYi6dkzZhEREREREbEYayeJHGz7Yaie27L9+qsSJL2fLnYtjYiIiIiIiMVLO6/4uKx2fFdT3TlERERERETEm0Y7SaQ6OW71PSIiIiIiIhZj7SSR7uS41feIiIiIiIhYjLXzTOQ6ks6gmnVsHFO+r91nkUVES+OnTGPI8df1dxgRbzqTT9m1v0OIiIgYENpJIuvv8Gt+r0DeMxAREREREfEm0u1yVtsXdfYBRvd9iAOLpMGSbpU0qHzfSNItkh6V9Jikb0lSqRsh6awWY0yWNL58HpR0kqSlS90QSTMlja19DmzqN67E8M5OYmy0a/T/QCnfU5IlvbvWdkgp+26tbFVJrzZil3SipGPK8YWSPtV0viGSJpTj7SRNa4p/x1J3gqSJJf6xkrbq5l6fWGJbr1Z2VClr+c6aWrvzJb2nqzad9Bsm6f/2tN+CknSapA8v7PNGRERERPRUO89EImlrSZ+StHr5vqmky4A7+jS6gekg4ErbsyUNBq4BTrG9AfBe4APAl9sYZ3vbmwBbAusC59XqJtkeVvtc3NRvU6oE/pvdjN/of2cp24fqZ7Z3U9u/ArvVvn8amNjGNXTm9qb4b5K0dTnH5iX+HYH/bWOs8U3xfgp4sLtOtj9vu9t2LQwDWiaRktqZuZ9fZwLH9+H4ERERERG9otskUtKpwAXAJ4HrJP0n8EfgbmD9vg1vQNoP+F053hf4k+2RALZnAIfRg2TA9nTgi8Aekt7WgzjuogfPpEpaHvgg8DnmTSJnAg/VZvf2An7dg1jasSYwtfGeUdtTbf+9jX5XA7sDSFoXmAY806iU9BNJHWWG89u18tGN65E0XdL3JD0g6c+S1ijln5Y0oZTfJmkp4DvAXmWmdK8yG3qepJHAxZJWk/RbSfeWzwfLWFtKulPS/eXfDUv5CElXS/q9pMclHSbp6NLuz42fue0ngFUk/Z8Fu80REREREX2rnZnIXYHNbO8D7ESVIG1j+8e2/9Wn0Q0wJclY1/bkUrQRMKbexvYkYHlJK7Y7ru0Xgcd5Iykf2rQcdNsW3XamSrA6M6r0vbt83wO4wfajwHOSNm9q/ytgb0nrALOBdhK8zmzbFP9QYCTwdlXLfs+R9O9tjvUi8L+SNqaaSb2iqf4E28OBTYF/l7RpizGWA/5s+73AbcAXSvn/Az5ayj9u+5VSdkWZQW2cawtgd9v7Aj8GTrf9Pqo/rJxf2jwMfMj2ZmWM/6qdf2OqPzhsCXwPmFHa3QUcWGt3H1WiPw9JB5dkuWP2jGmt71RERERExELQzvK8mY1k0fbzkh6x/VgfxzVQrQq8UPsuOn/NSU9ff1J/5+Yk28M6aTeqzKQ9TffLWafWvu8D/Kgc/6p8v69WfwPwXeCfzJuo9dTttndrLpS0BbAtsD1whaTjbV/Yxni/opo9/SiwA/AftbrPSDqY6nd5TeA9wLim/q8A15bjMcBHyvGfgAsl/Rq4sovzX2N7ZjneEXiP9PqPa0VJKwArARdJWp/qZ79krf8o2y8BL0maBvy+lI+nSn4bngbWahWA7fMoS56XXnP9vFonIiIiIvpNO0nkUEnXlGMBQ2rfsf3xPolsYJoJLFP7PhH4UL1BWXI53fZLtUSjSyUJGQI8SpWMdGV74GXgQqqll0e3Mf4qwIeBjSUZGARY0rGNNrZfkTQG+CrVDOvH2gq+B2zPpnqWc7Sk8cBnqa6jO78HTgU6bL/YuK+S3gUcA7yv/IHjQub++TS8aruReM2m/N7b/mLZ3GdXYKykYZ2c/+Xa8RLA1rWkshHLmVTJ4p6ShjD3plOzasdzat/nMPd/g8tQ/Y5FRERERAxY7SSRuzd9P60vAlkUlERlkKRlyuzspcA3JO1YNo8ZDJwB/KDdMcuziucAV5fxu0sisT1T0pHAeEkn2X6umy6fAi62fUjtvLcC2zD35jY/BG61/Wy7CXC7yjOCc2qz2MOAJ0rdycA9tq9q1bdc73FUSXbdilQJ3rQyO7sLPdgxWNJQ23cDd0v6GPB24CVghS66jaR67vXUMsYw22Opkv8ppc2IdmNosgHwP/PZNyIiIiJioeg2ibR9q6TNgKHARNsP9X1YA9pIquTrppLc7A6cKelsqhm+S4D6az1GSNqj9v395d9RqjK1JYCrqJaSNgyVNLb2/QLbZ9SDsP2UpMuBQ5v6trIPcEpT2W+pntP7fm3MibS3K+tPJf2oHP9vGb9u26b4T6J65vNMSSsDrwF/AQ4u9ZtQ7XLbKdu/alH2gKT7S8x/pVqe2hOnluWnAm4GHgD+Bhxf4j+5RZ/DgbMljaP67+c2qo2RfkC1nPVo4JYexoGkJYH1aOPdq5usvRIdeel5RERERPQTvbHKr5MG0v8D9qd6lmwr4GTbP1sIsQ1IJaE+2vYB/R3L4kLSjbY/2t9x9CdJe1K9/uRb3bUdPny4Ozq6zTUjIiIiIuabpDFlA8t5tLOcdS9gmO0Z5dm6G4A3bRJp+35JoyQNKs/4xQJ6syeQxVuolhNHRERERAxo7SSR/yrvP6Q8K9fOa0EWa7Yv6O8YYvFiO89CRkRERMQiYX52Z61/f7PtzhoREREREfGmlt1ZIyIiIiIiom1t7c66MAKJiIiIiIiIgW++n2+UdJGkn0jauDcDioiIiIiIiIFrQTbJOQu4CcirLiIiIiIiIt4kun1PZJedpbfYfq0X44mIbiy95vpe87M/6u8wIhY7k0/Ztb9DiIiIGDC6ek9ktzORku6oHV/SVH3PAsYWERERERERi5B2lrMuVzveqKlOvRjLgCdpsKRbJS0n6WFJm9TqjpV0rirflPSYpEcljZK0Ua3d9KYxR0g6qxyfKGmGpNVbtZe0hqTLJP1V0hhJd0nas0WcQyTNlDS29lmq1P1Y0pT6+z5LDJa0Q61sz1L2qfJ9tKTh5XiypFW7uY4pTedfWdKyki6VNF7SBEl3SFq+m3s+WtLfJKlWdnXzfeyk753dtemk3x6S3jM/fReEpJskvXVhnzciIiIioifaSSK7Wu86/2thF00HAVfafhk4EjinJI1rA4cAXwcOBT4AvNf2BsDJwDWSlmnzHFOBrzYXliTqauA22+va3gLYG1ink3Em2R5W+7xSEsc9gf8FPtTUfjywT+373sADbcbcyulN538BOAL4p+1NbG8MfA54tY2xXgA+CCBpZWDNdgKw/YH5CRzYA2iZREpq57U48+sS4Mt9OH5ERERExAJrJ4lcucxKfbIcf6J8Pgms1MfxDTT7Ab8DsH0D8BRwIHA6cKLt54HjgK/YnlHajQTuLH3bcQGwl6S3NZV/GHjF9rmNAttP2D6zB/FvD0wAfsLcCSPA7cCWkpYss4PrAWN7MHY71gSmNL7YfsT2rDb6/YoqqQX4BHBlo0LS8pJulnRfmeHcvVY3vfy7XZnR/E2ZQb60MbMp6RRJD0oaJ+k0SR8APg6cWmZQh5a+/yXpVuAISVuUGekxkm6UtGYZ6wuS7pX0gKTfSlq2lF+oaifjUWUW+d8lXSDpIUkX1q7zGub9uUREREREDCjtzKrcSvU/1Y3jj9Xqbuv1iAaoshx0XduTa8VHUj0X+pjtSyStCCxne1JT9w7mXQrcmelUieQRwH/WyjcC7utByEMljS3Hf7J9KFWCcjlVIvxfkpa03ZgJNNVuux+l+uPANcC7enC+ZkdJ2r8cP297e6rrGlmWyN4MXGT7sTbGuhn4maRBVMnkwcC3St2/gD1tv1iW2P5Z0jWed8eozaju4d+BPwEflPQg1czsu21b0sq2X5B0DXCt7d8AlHxzZdv/LmlJqv8Odrf9jKS9gO/xxiz1z0qfk6hmWhtJ/lup/hDwceD3VDOrnwfulTTM9ljbz0taWtIqtp+tBy/p4HLdDFpxtTZuWURERERE3+g2ibT9HwsjkEXAqlTLKl9n+++SbgGu7aav6Nmy4DOAsZJ+2OmA0tnANlSzk+9r0WSS7WG19ksB/xc4yvZLku4GdgKuq/X5FXA4VRL5VeAbXcTcndNtn1YvsD1W0rrlvDtSJVBb236om7FmA3cAewGDbU+uPyJJlRB/CJgDrA2sAfyjaYx7bD8JUJLrIcCfqZLQ8yVdR9c/xyvKvxsCGwN/LDEMopqRBti4JI8rA8sDN9b6/74kquOplvSOL7FMLLGMLe2eBtYC5koibZ8HnAfV7qxdxBkRERER0ae6TSIlrQMMsX1H+X401f8gA1xm+y99GN9AMhNo9VzjnPKhzIa9LGld23+ttdmcavYKYKakpWy/Ur6/jeo5yNeV2bDLmPv5uInAJ2ttDi0zbx1txr8zVXI4viQ/ywIzqCWRtu+RtDEw0/ajtUSt19ieTrUc9UpJc6gS2+6SSKgS3KuAE5vK9wNWA7aw/aqkybT+OdWXzc4G3mL7NUlbAjtQzXAeRjVb2MrL5V8BE21v3aLNhcAeth+QNALYrsX55zTFMoe5/ztchup3LSIiIiJiQGrnmchTqWZWGg6h+h9qA9/ug5gGpPK846A2Nsg5FThD0mAASTtSzRheVupvBfYvdYOBzwCjWozz31T3upFg3AIsI+lLtTbL9uAS9gE+b3uI7SFUS1V3ajy3V/N1FmwGslOSPtjYfbTMjL4HeKJ8v7lsUNSZ26k2Kbq8qXwl4OmSQG4PvLMH8SwPrGT7D1RLk4eVqpeAFTrp9giwmqStyxhL6o3dd1cAnipLXtt9BrYej4D/A0zuad+IiIiIiIWlnWciN7RdX+Y3w/YPASTd3jdhDVgjqRLCm7pocybV82/jJc2mWla5u+3G7NIRwE8lHU41q3Wx7XmeLbU9VdJVwFHluyXtAZwu6VjgGapk/rjugi6J4kepktLG+C+regdo/RlXbF/f3XjFuDKTCPBrYFxTff2ZSKh2PB0K/KQkS0tQzYL+VtWusesBz3V2svKM42ktqi4Ffi+pg2pJ6MNtxg9V0ve78ocBUe411aznz8rP6FNNcbxSnuk8Q9JKVP8N/YhqpvhbwN1UifF4Ok9EO7MF8Gfbr3XVaJO1V6IjL0WPiIiIiH6iefcfaWogPWj7PbXvb7P9XKu6xZ2kzYCjbR/Q37EsTsoS2oNsH93fsfQnST8GrrF9c1fthg8f7o6OdlcxR0RERET0nKQxtoe3qmtnOetLkjZofKklkO+m2kn0TcP2/cCoskto9BLbE97sCWQxobsEMiIiIiKiv7WznPU/gWslfY83XjGxBdVzc0f0VWADle0L+juGWDw1Xg8SERERETGQtfOKjxskfQI4lur1D1A9//UJ2xP6MriIiIiIiIgYWNqZiaQkiwfWyyS9XdLXbJ/aJ5FFRERERETEgNPOM5Gvk7SqpC9Jug0YTfVS94iIiIiIiHiT6HYmUtIKwJ7AvsAGVC98X9f2On0cW0RERERERAww7SxnfRq4B/gmcEd5X+GefRtWREREREREDETtJJHfAPYGfgJcJumKvg0pIroyfso0hhx/XX+HETHgTT5l1/4OISIiYrHU7TORtk+3vRXwcUDA1cBako6rvz8yIiIiIiIiFn/dJpGS/gvA9l9tf8/2JsD7gJWA6/s4vnocgyXdKmk5SQ9L2qRWd6ykc1X5pqTHJD0qaZSkjWrtpjeNOULSWeX4REkzJK3eqr2kNSRdJumvksZIuqvVsl5JS0g6Q9IESeMl3SvpXaVusqRVy7El/bDW7xhJJ9a+7y9pnKSJkh6QdL6klUvdaEnDm867naRpksbWPjuWuhPKOONK+Va1fvtIOqEc7yKpQ9JD5R6fVmt3cCl7WNI9krap1b1+XbVYrq3d42fKeR+U9IXme990HZPLfWtcwxml/P2S7i5lD9XvVSuShkiaWTvvuZJ6tJFUOyR9p3Gfe2GsX0lavzfGioiIiIjoK+0sZ92Zaknr62yPB8Y3l/exg4Arbb8s6UjgHEkfAtYCDgGGA4cCHwDea3uGpJ2AayRtZPtfbZxjKvBV4Lh6oaTGDOxFtvctZe+kmp1ttleJaVPbcyStA7zcot0s4BOSTrY9tel8OwNHAbvYniJpEPBZqt1wX+gi/ttt79Y01tbAbsDmtmeVZG+pWpOdgTMkbQycBexq+2FJbwEOLmPsRnWPt7E9VdLmwNWStrT9jy7iabjC9mElQZ8o6Zpu2m/ffE+Ai4DP2H6g3I8N2zjvJNvDyrXcAuwBXNmolPQW26+1MU6nbP+/Benf5CdU72P9Qi+OGRERERHRq9qZmRkk6a2S3tbq0+cRvmE/4HcAtm8AnqJ6d+XpwIm2n6dK/r5ie0ZpNxK4s/RtxwXAXi2u68PAK7bPbRTYfsL2mS3GWBN4yvac0u7JEluz14DzqJLFZicAx9ieUsaYbfsC24+0eR3N8Uy1PauMNdX23+H15HgYcB9V8vI92w+Xdq/ZPqeMcRzwtUZiZ/s+qqTu0J4EYvtpYBLwzvm4jtWpfuaN+/FgD877GtXvwXplBvR/JP0eGKlqZvuCMmN8v6Td4fWZ0qsl/V7S45IOk3R0afPnxu+IpAslfaoc12eah0saXY5PlHSRpJGlzSck/aDMuN4gackS6u3AjiXpjYiIiIgYkNpJIt8NjOnk09F3ob1B0lJUrxWZXCs+EvgesJrtSyStCCxne1JT9w5gI9oznSqRPKKpfCOqRKsdvwY+VpZR/lDSZl20PRvYT9JKC3C+um2blrMOBUYCb1e1vPccSf9ea78Z8IBtAxtT/Uxb2ahFXU/uKwCS1gXWBf7STdNRtWtoJNmnA49IukrSIZKW6cF5lwV2oJo9B9ga+KztD1Ml7LfYfh+wPXCqpOVKu42pXm2zJdXv2gzbmwF3Uf0BoyeGArsCuwO/BEaVpeEzSznlDw9/Ad7b4hoOVrXUuGP2jGk9PHVERERERO9pJ4l80Pa6tt/V4rNun0dYWZWmZZxlNu0WqiWAXRHgLuqb684APluS0tYDSmerek7x3nkGs5+kWmr5dWAOcLOkHVqe2H4RuBg4vItzbVKSqUmS9uriOqBazjqs9plkezqwBdXS1GeAKySNKO13Zv6fa63f11b3t162l6SxwOXAIbaf62bs7WvXcDqA7e9QLVkeSZXY3dBGjEPLef8EXGe7ca1/rMWwE3B8aTcaWAZ4R6kbZfsl288A04Dfl/LxwJA2zl93ve1XS99Btfibx3qaajn0XGyfZ3u47eGDlm3+m0NERERExMKzqCybm0n1P/fN5pQPtl+U9LKkdW3/tdZmc+DWxjiSlrL9Svn+NqrnIF9n+wVJlwFfrhVPBD5Za3NoWbbYcia2LB29Hrhe0j+pnsW7uZNr+xHVrOMvms63OVUSMx4YpmoTmsGdjNEl27OpEqTRksZTPV95IVUC1biuiVTJ5gMthniw1N1SK9u8lAM8C7yVN+5l8329wvZh8xN703VMAn4i6WfAM5JWsf1sF10m2R7Worz+jKqATzYvFVa1+dCsWtGc2vc5tP5v5zXe+MNM8+9rYznxHEmvltnfVmMtQ/X7HhERERExILUzE/nj5oLyjKT6IJ6WyjOFg9pYwngq1SYxgwFU7Zq5DXBZqb8V2L/UDQY+A4xqMc5/U20k0/if+1uAZSR9qdZm2VYBSNpc0lrleAlgU+CJLq7tOaolsJ+rFZ8MnFY25WmYrwRS0oaae8fPYcATZQntW2pJ2KnAN1Re26Jql9mjS90PgO9LWqXUDQNGAI1nJkcDB5S6QVT3uNV9nW+Sdq39zq0PzAZekLSlpIsXYOgbga80xu5m+XF3JlMl21D7o0MPbUCV0EdEREREDEjtzES+Q9K7y46dS1Mtw3sv8JqkfW3f1Lchvm4kVULY1fnOpJoRGy9pNvAPYHfbjZmdI4CfSjqcagbqYtu3NQ9SdiC9irLpjW1L2gM4XdKxVMtCX6ZpF9dideBn5V4B3EO162lXfgi8PlNn+w+SVqOayRxEtZR3AlXC03CdpFfL8V1Uz1duW5ZlNpwEPA6cqer1IK9RPXN3MPARavfS9jhVu95eXp4hNHBdqbtG0trAnZIMvATsb/up0v27VDOED1Dd1xuonvvrzohyXxveX/4dVX5+AONsH0iVpJ4uaUa5jv1sz5b0DhZs5u67VLPB40oiOZlqN9v58W3g55K+Adzd086S1gBm1u5rS5usvRIdeYl6RERERPQTvbGqrpMG0kRg45JIHQzsA+xINWNyke0t+z7M12eIjrZ9wMI43+JO0vnA+bb/3N+xLAhJpwKX2B7X37EsqLKJ0Iu2f95Vu+HDh7ujY6HsaRURERERb1KSxtge3qqunZnIV2rPb30U+FV5xu6hhfkqAtv3SxolaVA5fywA25/v7xh6g+2v9XcMvegF4JL+DiIiIiIioivtPBM5S9LGZXnl9lTLShtaPhfYV8q7EpNAxmLJ9i/KOy0jIiIiIgasdmYSjwR+A6wGnG77cQBJ/xe4v+9Ci4iIiIiIiIGm2ySyPDP37hblfwD+0BdBRURERERExMDU7XJWST+qHR/RVHdh74cUERERERERA1U7z0R+qHb82aa6TXsxloiIiIiIiBjg2kki1clxREREREREvMm0s7HOEpLeSpVwNo4byeSgPossIloaP2UaQ46/rr/DiOgXk0/Ztb9DiIiIeNNrJ4lcCRjDG4njfbU6z9s8IiIiIiIiFlfdLme1PcT2urbf1eKz7sIIclEnabCkWyUtJ+lhSZvU6o6VdK4q35T0mKRHJY2StFGt3fSmMUdIOqscnyhphqTVW7WXtIakyyT9VdIYSXdJ2rNFnEMkzZQ0tvZZqtT9WNIUSUvU2o+QZEk71Mr2LGWfKt9HSxpejidLWrWb65jSdP6VJS0r6VJJ4yVNkHSHpOW7ueejJT0i6QFJf5K0YVft54ek4ZLO6KWxdpP07d4YKyIiIiKiL7WzO+thteONumobnToIuNL2y1Tv3TynJI1rA4cAXwcOBT4AvNf2BsDJwDWSlmnzHFOBrzYXShJwNXBb+WPAFsDewDqdjDPJ9rDa55WSOO4J/C9zb7QEMB7Yp/Z9b+CBNmNu5fSm878AHAH80/YmtjcGPge82sZY+9l+L3ARcGpzpaQFWo5tu8P24QsyRs11wMclLdtL40VERERE9Il2NtY5qHZ8SV8FspjbD/gdgO0bgKeAA4HTgRNtPw8cB3zF9ozSbiRwZ+nbjguAvSS9ran8w8Arts9tFNh+wvaZPYh/e2AC8BPmThgBbge2lLRkmR1cDxjbg7HbsSYwpfHF9iO2Z/Wg/20lLiRNl/QdSXcDW0vaX9I9Zdbzp43EsrT7fpm5vUnSlmV286+SPl7abCfp2nJ8oqRjGicsM6ZDyudhSeeXsksl7VhmRx+TtGW5JgOjgd0W6E5FRERERPSxdpLIuuzO2kNlOei6tifXio8EvgesZvsSSSsCy9me1NS9A2h39nc6VSJ5RFP5Rsz9HGt3htaWkp5dyvYBLgeuAnaTtGStvYGbgI8CuwPX9OBcrRxVO/+oUnYBcFxZhnuSpPV7OObHqGZMAZYDJtjeCngW2Av4oO1hwGzeSNqXA0aXmduXgJOAj1DNyH6nh+dfD/gx1Stx3g3sC2wDHAN8o9auA9i21QCSDpbUIalj9oxpPTx9RERERETvaWdjnZXL83NLACtK+kS90vaVfRLZ4mNV4IV6ge2/S7oFuLabvqLrzYua684Axkr6YacDVonhNlSzk+9r0WRSSaga7ZcC/i9wlO2XygzeTlTLLxt+BRxOtQnTV5k7Meqp022fVi+wPVbSuuW8OwL3Stra9kPdjHWppJnAZOArpWw28NtyvAOwRRkPYDDwdKl7BbihHI8HZtl+VdJ4YEgPr+lx2+MBJE0EbrbtFmM9DazVagDb5wHnASy95vrZ0CoiIiIi+k07SeStwMfL8W1UszoNBpJEdm0m0Oq5xjnlg+0XJb0saV3bf6212Zzq/gPMlLSU7VfK97dRPQf5OtsvSLoM+HKteCLwyVqbQ8vmNh1txr8zVXI4viRaywIzqCWRtu+RtDEw0/ajpV2vsj2d6nftSklzqBLb7pLI/Ww3X+e/bM8uxwIusv31Fn1fLUtMofo5zSpxzJHU6r+b15h7Zr/+M68vvZ1T+z6Huf8bXIbq9yUiIiIiYsDqNom0/R8LI5DFle3nJQ2StIztf3XR9FTgDEmftj1T0o5UM4aHlPpbgf2BCyQNBj4DHNtinP8G7uWNn+0twH9J+pLtn5Synmzesg/weduXA0haDni8xQYwXwe6ur75JumDwIPlXi4FvIfq+UEk3QwcaHtKF0N05mbgd5JOt/10eZ50BdtPzMdYkynPM0raHHjXfIyxAdWzpxERERERA1a3SaSko7uqt/3fvRfOYmskVUJ4UxdtzgTeSjXjNxv4B7C77cbM1BHATyUdTjWDdrHt25oHsT1V0lXAUeW7Je0BnC7pWOAZ4GWqjXy6VBLFj/JGIovtlyXdwdwz0ti+vrvxinFlJhHg18C4pvqjJO1f+74HMBT4SdlpdgmqWdDfll1j1wOea/Pcc7H9oKRvAiPLWK9S7ZI7P0nkb4EDJY2lSuIfnY8xtqdKxiMiIiIiBiy9sWKvkwbSf3ZRbds93WTkTUfSZsDRtg/o71gWJ2UJ7UG2u/xDx6JA0hrAZbZ36K7t8OHD3dHR7mrkiIiIiIiekzTG9vBWde0sZ+30BeiSjlyAuN40bN8vaZSkQbXn8WIB2Z4ALPIJZPEOWrznMyIiIiJioOnpKz6aLS7/A9/nbF+QBDI6Y/te22P7O46IiIiIiO4saBKZ90ZGRERERES8iSxoEpn31UVERERERLyJtLM760u0ThZF9XL2iIiIiIiIeJNoZ2OdFRZGIBERERERETHwLehy1oiIiIiIiHgTSRIZERERERERbet2OWtEDCzjp0xjyPHX9XcYEQvd5FN27e8QIiIigsxERkRERERERA8M2CRS0mBJt0oaJGmIJEv6bq1+VUmvSjqrfD9R0jHl+EJJj0t6QNKjki6WtHbT+HuWMd/dVL6lpNGSHpN0n6TrJG1SO8cUSWNrn5Wb+i8h6QxJEySNl3SvpHeVusmSVi3HlvTDWr9jJJ1Y+76/pHGSJpbrOL9xrhLf8KbzbidpWlNsO5a6E8o440r5VrV++0g6oRzvIqlD0kOSHpZ0Wq3dwaXsYUn3SNqmVvf6ddViubYcj5D0TDnvg5K+UCs/q8XPfXK5b41rOKOUv1/S3aXsofq9aqX8zsysnfdcSb3++y7pO4373Atj/UrS+r0xVkREREREXxnIy1kPAq60PVsSwF+B3YBvlfpPAxO76P81279R1flIYJSkjW2/Uur3Ae4A9gZOBJC0BvBrYF/bd5aybYChwPjS73TbrydXLewFrAVsanuOpHWAl1u0mwV8QtLJtqfWKyTtDBwF7GJ7iqRBwGeBNYAXujj37bZ3axpra6r7trntWSXZW6rWZGfgDEkbA2cBu9p+WNJbgIPLGLsBhwDb2J4qaXPgaklb2v5HF/E0XGH7MEmrAxMlXdNN++2b7wlwEfAZ2w+U+7FhG+edZHtYuZZbgD2AKxuVkt5i+7U2xumU7f+3IP2b/AQ4FvhCL44ZEREREdGrBuxMJLAf8Lva95nAQ7UZuL2oEr4uuXI68A9gFwBJywMfBD5HlUQ2HAZc1EggS/87bF/dg7jXBJ6yPaf0f9L28y3avQacR5UsNjsBOMb2lDLGbNsX2H6kB3HU45lqe1YZa6rtvwOUBHsYcB9V8vI92w+Xdq/ZPqeMcRxVUj611N1HldQd2pNAbD8NTALeOR/XsTrwVBlntu0He3De14A7gfXKDOj/SPo9MFLScpIuKDPG90vaHV6fKb1a0u9VzWofJuno0ubP/7+9O4+Tq6rTP/55bHZEdjQgEkGIIksCzb5IxGFAUHCMA5Et48yAM4OyKCPKOIPgggJGlsGfiBFBhmUQkZEBohAEWW1CSMJOJCghDgEFQSJLeH5/3FPmUlR3V3WW7obn/XrVq+492z33dAX62+fcU5LWKOXOkzSuHNdnmrsl3VCOT5D0A0mTS5m/kfSNMuN6jaRlS1dvAj5Qgt5XKTPBPZJ6Fjz/zACGLyIiIiJi8RiSQaSk5YANbc9uyroYOKDM7i0AHu+g2alAY+nqfsA1th8Efl9m1gDeW8r15ejaUsspLfIvBT5U8k+TNKaPtv4TOFDSqk3p7fSjlV2alrNuBEwG1le1rPdsSe+rlR8D3G3bwGbAnb20+94WeT0lvW2SNgQ2BB7up+iU2j00guyJwAOSfizpcEkrdHDdlYDdWTibvANwqO33UwXs19veBhgLnCJp5VJuM+DjwLbAV4DnbY8BbgUOaff6xUbA3sC+wA+BKbY3p/rjyN4A5Q8PDwNbNle2fY7tbtvdXSs1f1wiIiIiIpaeIRlEAmvRetnmNcBfUS1FvaTDNlU7Hk8VkFLex7esUD2Dd5+k02vJE22PLq+xzXVsP0a11PLzwCvAdZJ2b9W+7T8C5wOf7rXT0uYlmJolaf8+7g+q5ayja69Ztp8DtqZamjoPuETShFJ+T+DqftrstWuAG7fSIr+etr+kacBFwOG2f99P22Nr9zARwPaJQDdVUPxxqs9CfzYq170ZuMp2415/VuvDHsBxpdwNwArAO0reFNvP2p4HPAP8T0mfAYxs4/p1V9t+qdTtqvW/ua0nqJZDR0REREQMSUP1mcj5VL/Mv4rtFyXdCXyGahbsQx20OYYqoFsTeD+wmSRT/UJvSf9K9YzlVpRltLa3K0sV9+mlzZbK0tGrgasl/R/VzOd1vRT/FtWs4/draY1+TLE9AxitahOaFTvpR60/C6gCpBskzaB6vvI8qgDqo7Vrbg3c3aKJe0ve9bW0rUo6wFPA6kDjOcY1asdQnokcSN+b7mMW8G1J3wXmSVrT9lN9VJlle3SL9PozqgI+2rxUWNXmQy/Ukl6pnb9C6387L7PwDzPNn9/GcuJXJL1UZn9btbUC1ec/IiIiImJIGpIzkeUZwq5eliyeBnyun+DhL1T5NNWzgdcA44DzbW9ge6Tt9YFHgJ2plpdOkLRjrYmVOum7pK0krVuO3wRsATzaW/kyI3Yp1fOZDV8DTi3LdhsGFEBKGtW04+do4NGyhHaZ2jieAnxB0iaNvks6puR9A/h6CcCRNBqYADSembwBOLjkdQEHAa2W+g6YpL3LM5wAG1MtZ35a1W665y9C09cCn2q03c/y4/7Mpgq2YWFw3qlN6HvDqIiIiIiIQTVUZyKhWra4M/DzeqLte2jvl+xTJH2RKgi8jWqJ5IuSxgMnN5X9EdWOrP9Ulox+XdVXgjxBNaN2Yq3s0ZIOqp3v1/Ts5jrAdyUtX87voNr1tC+nUW3q07jH/5W0NtVMZhfV0t6ZVAFPw1WSXirHt1IFwLuUZZkNX6YKkM9U9fUgL1M9c3cY1bLgv4yt7emSjgIuKs8QGriq5F1ZxuOWMnv7LHCQ7bml+klUM4R3U83sXUP13F9/Jkjar3a+fXmfImlBOZ5u+xCqIHWipOfLfRxYdu59B4s2c3cS1Wzw9BJIzqbDmeeaLwHfk/QF4PZOK6vaHXh+bVxb2ny9VenJl65HRERExCDRwlV1Q0uZETrG9sGD3ZfXI0nnAufavm2w+7IoJJ0CXGB7+mD3ZVGVTYT+aPt7fZXr7u52T0/PUupVRERERLwRSbrTdnervCE7E2n7LklTJHWVZ/piMbL9D4Pdh8XB9rGD3YfF6GnggsHuREREREREX4ZsEAlge9Jg9yFiabH9/f5LRUREREQMriG5sU5EREREREQMTQkiIyIiIiIiom0JIiMiIiIiIqJtCSIjIiIiIiKibQkiIyIiIiIiom1DenfWiHitGXOeYeRxVw12NyIW2eyT9x7sLkRERMQAZCYyIiIiIiIi2pYgcimStKKkX0jqKufvlXS9pAclPSTpi5JU8iZIOqtFG7MlzSiveyV9WdLyJW+kpPmSptVehzTVm176sEEvfWyUa9TfsaR/RJIlvbtWdmRJO6mWtpaklxp9l3SCpM+W4/MkjWu63khJM8vxbpKeaer/B0re8ZLuKf2fJmm7fsb6BElzStmZkj7c389nICTdspjaWVvSNYujrYiIiIiIJSlB5NL1CeBy2wskrQhcCZxsexNgS2BH4J/baGes7c2BbYENgXNqebNsj669zm+qtwVwA/Bv/bTfqN8IksYDvwQOaCr7a2Cf2vnHgHvauIfe3NTU/59L2qFcY6vS/w8Av22jrYm2R5c+TZL0qs+7pEVezm17x0Vto7QzD5graafF0V5ERERExJKSIHLpOhD4STn+OHCz7ckAtp8HjgCOa7cx288BnwT2k7RGB/24FViv3cKS3gzsBPw9rw0i5wP3Seou5/sDl3bQl3aMAJ60/QKA7SdtP95uZdv3AS8Da0m6QdJXJf0COFLS1mVm9k5J10oaAVDKTZR0o6T7JG0j6fIyY/zlRtuSnivvu0n6aS39LEkTyvHscs1bJfVI2qpca5akT9a6egXVZ+Q1JB1W6vYseP6Zdm89IiIiImKxSxC5lEhaDtjQ9uyS9F7gznoZ27OAN0t6S7vt2v4j8AiwcUnaqGk56C4tqu1JFbD0Zkqpe3s53w+4xvaDwO8lbdVU/mLgAElvBxYAbQd4LezS1P+NgMnA+mXZ79mS3tdJg2Xp6yvAvJK0mu33AWcAZwLjbG8NTAK+Uqv6ou1dgf9HFfz/C7AZMEHSmh3e129t7wDcBJwHjAO2B06slekBWv28sH2O7W7b3V0rrdrhpSMiIiIiFp/szrr0rAU8XTsX4F7K9pbeG9WOZ5UlnK1MkfRW4An6X876ZO18PPCtcnxxOZ9ay78GOAn4P+CS9rvd0k2292lOlLQ1VYA1FrhE0nG2z+unraMlHQQ8C+xv2+WR00YfR1EFhT8r6V3A3Fr9K8v7DOAe23NLX34NrA881cF91dt6s+1ngWcl/VnSarafpvq5rNtBmxERERERS12CyKVnPrBC7fweYNd6AUkbAs/ZfrYENf2StAowEngQ6G+KaizwJ6qZsBOBY9pof03g/cBmkkwVaFnSvzbK2H5R0p3AZ6hmWD/UVuc7YHsB1bOcN0iaARxKdR99mWj71BbpfyrvogoOd+il/gvl/ZXaceO8+d/Oy7x6Zn+Fpvx22lqB6nMSERERETFkZTnrUmL7D0CXpEZwcSGwc2330RWplld+o902y7OKZwNXlPbb6cd84CjgkDafoxwHnG97A9sjba9PtXx256ZypwGfs93J7FxbJI2StHEtaTTwaMn7mqSPDLDpB4C1y8Y9SFpW0nsH2NajwKaSlpe0KrD7ANrYBJg5wOtHRERERCwVmYlcuiZTBV8/tz1f0r7AmZL+k2qG7wKg/rUeEyTtVzvfvrxPUTVV+Sbgx1RLSRs2kjStdj7J9hn1TtieK+kiqmf86nVbGQ+c3JT2I6qNgb5ea/Me2tuV9TuSvlWOf1var9ulqf9fpgpaz5S0GtWM38PAYSV/cxYuFe1ImUEdB5xRAr9lqJbtdry7rO3fSroUmA48BNw1gC6NBa7qr9Dm661KT76kPSIiIiIGiexOH7+LgZI0BjjG9sGD3ZfXC0nX2v7rwe7H4iDpRmDf/maVu7u73dPTs5R6FRERERFvRJLutN3dKi/LWZci23dRzSJ2DXZfXi9eRwHk2sA3212WHBERERExWLKcdSmzPWmw+xBDj+159P21KxERERERQ0JmIiMiIiIiIqJtCSIjIiIiIiKibQkiIyIiIiIiom0JIiMiIiIiIqJtCSIjIiIiIiKibdmdNWKYmTHnGUYed9VgdyMWs9kn7z3YXYiIiIhoy7CdiZS0oqRfSOqSNFKSJZ1Uy19L0kuSzirnJ0j6bDk+T9Ijku6W9KCk8yWt19T+R0qb725K31bSDZIekjRV0lWSNq9dY46kabXXak313yTpDEkzJc2Q9CtJ7yx5syWtVY4t6bRavc9KOqF2fpCk6ZLuKfdxbuNapX/dTdfdTdIzTX37QMk7vrQzvaRvV6s3XtLx5XgvST2S7pN0v6RTa+UOK2n3S7pD0s61vL/cV60vPy3HEyTNK9e9V9I/1tLPavFzn13GrXEPZ5T07SXdXtLuq49VK+UzM7+Uv1vSLZJG9VWnRRst+9hm3dUk/XPtfG1J1wykrYiIiIiIpWk4z0R+Arjc9gJJAL8G9gG+WPI/BtzTR/1jbV+mqvJRwBRJm9l+seSPB34JHACcACDprcClwMdt31LSdgY2AmaUehNt/yW4amF/YF1gC9uvSHo78KcW5V4A/kbS12w/Wc+QtCdwNLCX7TmSuoBDgbcCT/dx7Zts79PU1g5U47aV7RdKsLdcrciewBmSNgPOAva2fb+kZYDDShv7AIcDO9t+UtJWwBWStrX9uz7603CJ7SMkrQPcI+nKfsqPbR4T4AfA39q+u4xHOwHhLNujyz0cDnyBahyXhtWAfwbOhup7IiXNlbST7ZuXUh8iIiIiIjo2bGcigQOBn9TO5wP31Wbg9qcK+PrkykTgd8BeAJLeDOwE/D1VENlwBPCDRgBZ6v/S9hUd9HsEMNf2K6X+Y7b/0KLcy8A5VMFis+OBz9qeU9pYYHuS7Qc66Ee9P0/afqG09aTtxwFKgD0amAr8K/AV2/eXci/bPru08TmqoPzJkjeVKqj7l046YvsJYBawwQDuYx1gbmlnge17O6z/FuAP8NoZRkk/lbRbOf47VbPXv6D6jDTKbCTptjKzfKKk52p5x5b06ZK+VJJPBjYqM6GnlLQrqD7XERERERFD1rAMIiUtB2xoe3ZT1sXAAWV2bwHweAfNTgUaS1f3A66x/SDw+zKzBvDeUq4vR9eWWk5pkX8p8KGSf5qkMX209Z/AgZJWbUpvpx+t7NK0nHUjYDKwfgmMzpb0vlr5McDdtg1sBtzZS7vvbZHXU9LbJmlDYEPg4X6KTqndQyPIngg8IOnHkg6XtEIbl2wEcbOAY4Bv9tO/EcCXqILHvwI2rWWfDpxuextqnztJewAbA9tSBeRbS9oVOI4yE2r72FK8B9ill2sfVpYS9yx4/pk2bi0iIiIiYskYlkEksBatl21eQ/XL/Xjgkg7bVO14PFVASnkf37JC9QzefZJOryVPLIHBaNtjm+vYfoxqqeXngVeA6yTt3qp9238Ezgc+3Wunpc0bgZCk/fu4P6iWs46uvWbZfg7Ymmpp6jzgEkkTSvk9gav7abPXrgFu3EqL/Hra/pKmARcBh9v+fT9tj63dw0QA2ycC3VRB8cepPgv9aQRxG1EtaT6nn/LbATfYnleWPdc/YzsA/12O/6uWvkd53cXCP1Rs3Ev7T1AtdX4N2+fY7rbd3bVS898UIiIiIiKWnuEaRM4HXjPTVH6xvxP4DPCjDtscQ7Ucdk3g/cC5kmYDx1IFOaJ6xrIxK4nt7aiewezot3rbL9i+usxAfZVq5rM336JaVrtyLe0v/bA9ozzXdzWwYif9qPVnge0bbP8H1ZLdj5asPaiCssY1t+6liXtb5G1V0gGeAlav5a0B1J9pvKQEc9vZ/vFA7gGgBMXfBnYHtiw/y3ZdCexajl/m1f826p+1VgFxXwR8rRb0vsv293opuwLVZzsiIiIiYsgalkFkeYawq5cli6cBn7P9VDttqfJpqmcDrwHGAefb3sD2SNvrA48AO1MtL50gacdaEyt10ndJW0latxy/CdgCeLS38mVW7lKqQLLha8CpZdluw4ACSEmjJNVnxkYDj5YltMvUxvEU4AuSNmn0XdIxJe8bwNcbQZuk0cAEyqYxwA3AwSWvCzgIaLXUd8Ak7V0Cfahm+hYAT6vaTff8NprYmep5TIDZwOhyj+tTLUUFuB3YTdKakpal2ryp4TYWBt/152ivBT5RnrNF0nplA6FngVWa+rAJMLONvkZEREREDJrhvDvrZKpf/H9eT7R9D33vytpwiqQvUgWBt1EtkXxR0niqTU/qfkS1I+s/lSWjX1f1lSBPUM2onVgre7Skg2rn+zU9u7kO8F1Jy5fzO6h2Pe3LaVQzhI17/F9JawNXl6Dsaarg49panaskvVSOb6UKgHcpy0YbvkwVIJ+p6utBXqZ6HvEwqmXBfxlb29MlHQVcJGklqhm5q0relWU8bpFkqgDpINtzS/WTgG9LuptqZu4a4If93DNUAft+tfPty/sUSQvK8XTbh1AFqRMlPV/u48Cyc+876H12b6MyHgJeBP6hpN9cxmUG1bhOLfc5V9VXh9xKtYnPVKCr1DkK+KGkz5RxeabUmSzpPcCtJcZ9rozNLEk3S5oJNGalx5a6ERERERFDlqo9U4afsiHNMbYPHuy+vB5JOhc41/Ztg92XRVF2Pr3A9vQlfJ2VgPm2LekAYLztfTts40Zg31526/2L7u5u9/T0LEJvIyIiIiL6JulO292t8obtTKTtuyRNkdRle0H/NaITtv+h/1JDX23n0yVta+CssqT2aarvMW1bmVn+Zn8BZERERETEYBu2QSSA7UmD3YcIANs3AVsuQv15VN8TGRERERExpA3LjXUiIiIiIiJicCSIjIiIiIiIiLYliIyIiIiIiIi2JYiMiIiIiIiItiWIjIiIiIiIiLYliIyIiIiIiIi2Deuv+Ih4I5ox5xlGHnfVYHfjdWn2yXsPdhciIiIihrzMRA5TklaU9AtJXZJGSrKkT9Xyz5I0oRyfJ+kRSdPK6xZVnpS0eikzorSxc62NeZLWbLruhJLeaOv8Wt7dki5qKn+epOclrVJLO71ca61y/lx5HylpZot7PU/SuHJ8g6QHate/rKSPKnnTJN0n6Zw2xnBBKX+3pKmSduyvTlP93ST9tJM6TfW/UDteTtKNkvKHnYiIiIgY0hJEDl+fAC63vaCcPwEcKWm5Xsofa3t0ee1o28DtwA4lf0fgrvKOpFHAk7afatHWJbW2Dinl30P1edpV0spN5R8G9i3l3gSMBeYM4J4bDqxdf1xJOwOYWNLeA5zZRjvzS/ktgc8DX1uEPg3EX4JI2y8C1wH7L+U+RERERER0JEHk8HUg8JPa+TyqIOTQDtq4mRI0lvdv8uqg8pYO2vo4cAEwGfhwU95FLAyOdivXfbmDttsxAniscWJ7Rof13wL8AV47w9g0q7unpPsl/RL4m1qZtSX9rMxofkfSo7WZ1oMk3VFmPb9TZo9PBlYsaReWZq6g+rlGRERERAxZCSKHoTLbuKHt2U1ZJwOfkdTVotoptSWgjaDlFhYGkdtSBTHrl/MdqYK9VvavtfV3jTTgEqqAcXxT+YeAtcvS2fHAxf3dYz8urF3/lJI2Ebhe0tWSjpa0WhvtNIK4+4FzgZP6KixpBeC7wIeAXYC31bL/A7je9lbAj4F3lDrvoRqbnWyPBhZQzaQex8KZ0EbgOBPYpo1+R0REREQMmjx/NTytBTzdnGj7EUl3UM0KNjvW9mVNaXcAY8ry02VtPyfp15LeRRVEntbL9S+xfUTjRNI2wDzbj0p6DJgkaXXbf6jVuRw4ANgOOLy92+zVgbZ76gm2vy/pWmBPqqWzh0va0vYLfbQzvwR2SNoBOF/SZn2UfzfwiO2HSp0fAoeVvJ2Bj5S+XCOpce+7A1sDv5IEsCLV0uPXsL1A0ouSVrH9bD1P0mGNa3W9Ze0+uhgRERERsWRlJnJ4mg+s0EveV4HP0cbP1vbzVM8rfgKYWpJvAz4IrAM80GZ/xgPvljQbmEW1NPSjTWUupprp+5ntV9pstyO2H7c9yfa+VMtl+woIm+veShWcr13q1sevPtbupQn1kf6D2jOco2yf0EdXlgf+3KJ/59jutt3dtdKqfVSPiIiIiFiyEkQOQ2WGr6ssr2zOux+4F9inzeZuBo4Cbi3ntwJHAreVzXf6VDbK+Riwhe2RtkdSzQS+akmr7d8AxwNnt9mvjpRnFZctx28D1gTmSFpP0nVt1H830AU8BTwKbCppeUmrUs0mAtwPvFPSRuW8fo+/BP62tLUHsHpJvw4YJ2mdkreGpA1K3kuNPpe8NalmdF/q8PYjIiIiIpaaBJHD12SqJZStfAV4e1Na/ZnIabVdXG8GNmRhEDm11G13U51dgTm267ut3kgVhI2oF7T9Hduz+mlvlKTHaq+PtShTfyby5yVtD2CmpLuBa6mW7/6OasOd3jbxaTwTOY3qec5DbS+w/VvgUmA6cCHVrrXY/jPVktKrysY6j9ba+hKwh6SpwF7AXOBZ2/cC/wZMljQd+FnpE8A5wPTaM6pjgf/tZ3wiIiIiIgaV2phsiiFI0hjgGNsHD3ZfhjJJRwC/sX3lEr7O8sAC2y+X5yu/3XjesoM2Lgc+b7vPZcTd3d3u6enpq0hERERExCKRdKft7lZ52VhnmLJ9l6Qpkrpq3xUZTWyftZQu9Q7g0rK890XgHzupXGaGr+gvgIyIiIiIGGwJIocx25MGuw9RKTu2jlmE+i8C5y++HkVERERELBl5JjIiIiIiIiLaliAyIiIiIiIi2pYgMiIiIiIiItqWIDIiIiIiIiLaliAyIiIiIiIi2pYgMiIiIiIiItqWr/iIGGZmzHmGkcddNdjdGBJmn7z3YHchIiIi4g0nM5ERERERERHRtgSRS5CkFSX9QlKXpJGSLOlTtfyzJE0ox+dJekTStPK6RZUnJa1eyowobexca2OepDWbrjuhpDfaOr+Wd7eki5rKnyfpeUmr1NJOL9daq5w/V95HSprZ4l7PkzSuHN8g6YHa9S8r6aNK3jRJ90k6p40xtKQLaufLlHv7aT/1uiWd0V/7vdQ9StJKA6k7UJLWlnTN0rxmRERERMRAJIhcsj4BXG57QTl/AjhS0nK9lD/W9ujy2tG2gduBHUr+jsBd5R1Jo4AnbT/Voq1Lam0dUsq/h+pnvquklZvKPwzsW8q9CRgLzBnAPTccWLv+uJJ2BjCxpL0HOLONdv4EbCZpxXL+V+30y3aP7U8PqOdwFNAyiJTUNcA2+2R7HjBX0k5Lov2IiIiIiMUlQeSSdSDwk9r5POA64NAO2riZEjSW92/y6qDylg7a+jhwATAZ+HBT3kXA/uV4t3Ldlztoux0jgMcaJ7ZntFnvaqDx8Nt4qr4CIGnbMmt7V3kfVdJ3a8xWSjpB0qQyC/prSZ8u6StLuqrMzs6UtH/JWxeYImlKKfecpBMl3Q7sIOkgSXeUGdXvNAJLSd+W1CPpHklfqvVxtqSvSrq15G8l6VpJsyR9snafV1B9ZiIiIiIihqwEkUtImW3c0PbspqyTgc/0MqN1Sm0J6IUl7RYWBpHbUgUa65fzHamCvVb2r7X1d4004BKqIGx8U/mHgLXL0tnxwMX93WM/Lqxd/5SSNhG4XtLVko6WtFqbbV0MHCBpBWALqtnZhvuBXW2PAf4d+Govbbwb+GuqMfwPScsCewKP297S9mbANbbPAB4HxtoeW+quDMy0vR3wFNU47mR7NLCAhYHf8ba7Sx/fJ2mL2vV/a3sH4CbgPGAcsD1wYq1MD7BLq85LOqwEoD0Lnn+mt3GKiIiIiFjisjvrkrMW8HRzou1HJN1BNSvY7FjblzWl3QGMKctPl7X9XJlNexdVEHlaL9e/xPYRjRNJ2wDzbD8q6TFgkqTVbf+hVudy4ABgO+Dw9m6zVwfa7qkn2P6+pGupgrd9gcMlbWn7hb4asj1d0kiq4PZ/m7JXBX4gaWPAwLK9NHNVuc4Lkp4A3grMAE6V9HXgp7Zv6qXuAuBH5Xh3YGvgV5IAVqRapgzwt5IOo/p3NQLYFJhe8q4s7zOAN9t+FnhW0p8lrWb76dLOur2MwTnAOQDLj9jYvfQzIiIiImKJy0zkkjMfWKGXvK8Cn6ON8bf9PNXzip8Appbk24APAusAD7TZn/HAuyXNBmYBbwE+2lTmYuAk4Ge2X2mz3Y7Yftz2JNv7Ui2X3azNqlcCp1JbylqcBEwpM4kfovcxrweqC4BlbD9IFRDOAL4m6d97qfvn2nOtAn5Qe95zlO0TJL0T+Cywu+0tgKua+tK4/itNfXmFhX/MWYHqcxMRERERMWQliFxCygxfV1mC2Zx3P3AvsE+bzd1MtdnLreX8VuBI4Lay+U6fykY5HwO2sD3S9kiqmcBXLWm1/RvgeODsNvvVEUl7lmWkSHobsCYwR9J6kq7rp/ok4MQWz1GuysKNdiZ02J91gedt/5AqQN2qZD0LrNJLteuAcZLWKW2sIWkDqqD8T8Azkt4K7NVJX4pNgNfsfBsRERERMZRkOeuSNRnYGfh5i7yvUO20WneKpH+rnW9r+0WqIPJIFgaRU4G3A+e22Y9dgTm267ua3ghsKmlEvaDt77TR3qiyJLbh6BZlLpTUmFV70vYHgD2A0yX9uaQfa/t3krrpZxMf248Bp7fI+gbVctZjgOvb6Hvd5lRj/grwEvBPJf0c4GpJc2vPRTb6cW/5GU0uwflLwL/Yvk3SXcA9wK/p/VnVvoylmsHsu9PrrUrPyXv3VywiIiIiYolQGxNZMUCSxgDH2D54sPsylEk6AviN7Sv7Lfw6JulGYN+m51Rfo7u72z09PX0ViYiIiIhYJJLuLJtGvkZmIpcg23dJmiKpq/ZMXTSxfdZg92GwSVob+GZ/AWRERERExGBLELmE2Z402H2Ioc/2PKqvb4mIiIiIGNKysU5ERERERES0LUFkREREREREtC1BZERERERERLQtQWRERERERES0LUFkREREREREtC27s0YMMzPmPMPI464a7G50bPbJew92FyIiIiJiMchMZERERERERLQtQeQQJGlFSb+Q1CVppCRL+lQt/yxJE8rxeZIekTStvG5R5UlJq5cyI0obO9famCdpzabrTijpjbbOr+XdLemipvLnSXpe0iq1tNPLtdYq58+V95GSZra41/MkjSvHN0h6oHb9y0r6qJI3TdJ9ks5pYwwXlPIzJf23pJX6q9MpSZ+UdMhiautUSe9fHG1FRERERCxJCSKHpk8Al9teUM6fAI6UtFwv5Y+1Pbq8drRt4HZgh5K/I3BXeUfSKOBJ20+1aOuSWluHlPLvofqs7Cpp5abyDwP7lnJvAsYCcwZwzw0H1q4/rqSdAUwsae8Bzmyjnfml/GbAi8An65mSuhahjwDY/n+2z++/ZFvOBI5bTG1FRERERCwxCSKHpgOBn9TO5wHXAYd20MbNlKCxvH+TVweVt3TQ1seBC4DJwIeb8i4C9i/Hu5XrvtxB2+0YATzWOLE9o8P6NwHvkrSbpCmS/guYUWZ6T5H0K0nTJR0OUMr9QtKlkh6UdLKkAyXdIWmGpI1KuRMkfbYc3yCpuxyvJWl2OZ4g6QpJ/1NmjI+QdIykuyTdJmmNck+PAmtKetuiDVVERERExJKVIHKIKbONG9qe3ZR1MvCZXmbQTqktAb2wpN3CwiByW+AKYP1yviNVsNfK/rW2/q6RBlxCFTCObyr/ELB2WTo7Hri4v3vsx4W1659S0iYC10u6WtLRklZrtzFJywB7AY3Ac1vgeNubAn8PPGN7G2Ab4B8lvbOU2xI4EtgcOBjYxPa2wLnAp+jMZlSB+LbAV4DnbY8BbgXqy2GnAjv1ch+HSeqR1LPg+Wc6vHxERERExOKT3VmHnrWAp5sTbT8i6Q6qYKTZsbYva0q7AxhTlp8ua/s5Sb+W9C6qIPK0Xq5/ie0jGieStgHm2X5U0mPAJEmr2/5Drc7lwAHAdsDh7d1mrw603VNPsP19SdcCe1ItnT1c0pa2X+ijnRUlTSvHNwHfo7rvO2w/UtL3ALZoPJMJrApsTLX89Ve25wJImkU1CwtVMDq2w3uaYvtZ4FlJzwD/U2tri1q5J4B1WzVg+xzgHIDlR2zsDq8fEREREbHYJIgceuYDK/SS91XgMuDG/hqx/bykh6mer5xakm8DPgisAzzQZn/GA+9uLM8E3gJ8lGpGruHico0f2H5FUptNt8/248AkqiB2JtXs3p19VJlve3Q9ofTrT/Uk4FO2r20qtxtQD1BfqZ2/Qut/Ny+zcGa/+efXblsrUP38IyIiIiKGrCxnHWLKDF+XpNcEkrbvB+4F9mmzuZuBo6iWTVLejwRuK5vv9KlslPMxYAvbI22PpJoJfNWSVtu/AY4Hzm6zXx2RtKekZcvx24A1gTmS1pN03SI0fS3wT7W2N2mxcVC7ZgNbl+NxfZTryybAa3awjYiIiIgYSjITOTRNBnYGft4i7ytUO63WnSLp32rn29p+kSqIPJKFQeRU4O28ehaxL7sCc2zXd1u9EdhU0oh6QdvfaaO9UWVJbMPRLcpcKKkxG/ek7Q9QLTs9XdKfS/qxtn9XNrJZlE18zgVGAlNVTVPOA/YbYFunApdKOhi4vtPKJZB9F9DTX9nN11uVnpP37ryHERERERGLgdqYkIqlTNIY4BjbBw92X4YySUcAv7F95WD3ZVFJ+giwle0v9le2u7vbPT39xpoREREREQMm6U7b3a3yMhM5BNm+q3wVRVftuyKjie2zBrsPi9Ey9L7ZUURERETEkJEgcoiyPWmw+xBLj+3/Huw+RERERES0IxvrRERERERERNvyTGTEMCPpWdr/ipZ4tbWAJwe7E8NQxm3gMnYDl7EbuIzdwGXsBi5jN3BDdew2sL12q4wsZ40Yfh7o7SHn6Juknoxd5zJuA5exG7iM3cBl7AYuYzdwGbuBG45jl+WsERERERER0bYEkREREREREdG2BJERw885g92BYSxjNzAZt4HL2A1cxm7gMnYDl7EbuIzdwA27scvGOhEREREREdG2zERGRERERERE2xJERkRERERERNsSREYME5L2lPSApIclHTfY/RkKJE2S9ISkmbW0NST9TNJD5X31Wt7ny/g9IOmva+lbS5pR8s6QpKV9L0uTpPUlTZF0n6R7JB1Z0jN2/ZC0gqQ7JN1dxu5LJT1j1yZJXZLukvTTcp6xa4Ok2eWep0nqKWkZuzZIWk3SZZLuL//d2yFj1z9Jo8rnrfH6o6SjMnb9k3R0+X/ETEkXlf93vL7GzXZeeeU1xF9AFzAL2BBYDrgb2HSw+zXYL2BXYCtgZi3tG8Bx5fg44OvleNMybssD7yzj2VXy7gB2AARcDew12Pe2hMdtBLBVOV4FeLCMT8au/7ET8OZyvCxwO7B9xq6jMTwG+C/gp+U8Y9feuM0G1mpKy9i1N3Y/AP6hHC8HrJax63gMu4DfARtk7Podq/WAR4AVy/mlwITX27hlJjJieNgWeNj2r22/CFwM7DvIfRp0tm8Eft+UvC/VLwyU9/1q6RfbfsH2I8DDwLaSRgBvsX2rq/9in1+r87pke67tqeX4WeA+qv/pZez64cpz5XTZ8jIZu7ZIejuwN3BuLTljN3AZu35IegvVHxy/B2D7RdtPk7Hr1O7ALNuPkrFrxzLAipKWAVYCHud1Nm4JIiOGh/WA39bOHytp8VpvtT0XqmAJWKek9zaG65Xj5vQ3BEkjgTFUM2oZuzaU5ZjTgCeAn9nO2LXvW8C/Aq/U0jJ27TEwWdKdkg4raRm7/m0IzAO+X5ZRnytpZTJ2nToAuKgcZ+z6YHsOcCrwG2Au8IztybzOxi1BZMTw0GoNfL6fpzO9jeEbdmwlvRn4EXCU7T/2VbRF2ht27GwvsD0aeDvVX4s366N4xq6QtA/whO07263SIu0NOXbFTra3AvYC/kXSrn2UzdgttAzVYw/ftj0G+BPVUsLeZOyaSFoO+DDw3/0VbZH2hhu78qzjvlRLU9cFVpZ0UF9VWqQN+XFLEBkxPDwGrF87fzvV0oh4rf8rS0Ao70+U9N7G8LFy3Jz+uiZpWaoA8kLbl5fkjF0HypK4G4A9ydi1Yyfgw5JmUy3Jf7+kH5Kxa4vtx8v7E8CPqR5zyNj17zHgsbJiAOAyqqAyY9e+vYCptv+vnGfs+vYB4BHb82y/BFwO7MjrbNwSREYMD78CNpb0zvIXwQOAKwe5T0PVlcCh5fhQ4Ce19AMkLS/pncDGwB1lScmzkrYvu54dUqvzulTu83vAfba/WcvK2PVD0tqSVivHK1L9snA/Gbt+2f687bfbHkn137DrbR9Exq5fklaWtErjGNgDmEnGrl+2fwf8VtKokrQ7cC8Zu06MZ+FSVsjY9ec3wPaSVir3uzvV3gOvr3FbWjv45JVXXov2Aj5ItYvmLOD4we7PUHhR/U9tLvAS1V/s/h5YE7gOeKi8r1Erf3wZvweo7XAGdFP9QjYLOAvQYN/bEh63namWxEwHppXXBzN2bY3dFsBdZexmAv9e0jN2nY3jbizcnTVj1/94bUi1e+PdwD2N/wdk7Noev9FAT/l3ewWwesau7bFbCXgKWLWWlrHrf9y+RPUHxpnABVQ7r76uxk2lgxERERERERH9ynLWiIiIiIiIaFuCyIiIiIiIiGhbgsiIiIiIiIhoW4LIiIiIiIiIaFuCyIiIiIiIiGhbgsiIiIiIiIhoW4LIiIiIiIiIaNv/B63BzIKyO508AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "unique_cust.sort_values().plot.barh(figsize=(12,7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "9e138a12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Values of each group\n",
    "ncust_bars1 = unique_cust[unique_cust.index.get_level_values(\"PREMIUM_CUSTOMER\") == \"Budget\"]\n",
    "ncust_bars2 = unique_cust[unique_cust.index.get_level_values(\"PREMIUM_CUSTOMER\") == \"Mainstream\"]\n",
    "ncust_bars3 = unique_cust[unique_cust.index.get_level_values(\"PREMIUM_CUSTOMER\") == \"Premium\"]\n",
    " \n",
    "ncust_bars1_text = (ncust_bars1 / sum(unique_cust)).apply(\"{:.1%}\".format)\n",
    "ncust_bars2_text = (ncust_bars2 / sum(unique_cust)).apply(\"{:.1%}\".format)\n",
    "ncust_bars3_text = (ncust_bars3 / sum(unique_cust)).apply(\"{:.1%}\".format)\n",
    " \n",
    "# # Names of group and bar width\n",
    "#names = unique_cust.index.get_level_values(\"LIFESTAGE\").unique()\n",
    "\n",
    "# # The position of the bars on the x-axis\n",
    "#r = np.arange(len(names))\n",
    "\n",
    "plt.figure(figsize=(13,5)) \n",
    "\n",
    "# # Create brown bars\n",
    "budget_bar = plt.barh(r, ncust_bars1, edgecolor='grey', height=1, label=\"Budget\")\n",
    "# # Create green bars (middle), on top of the firs ones\n",
    "mains_bar = plt.barh(r, ncust_bars2, left=ncust_bars1, edgecolor='grey', height=1, label=\"Mainstream\")\n",
    "# # Create green bars (top)\n",
    "prem_bar = plt.barh(r, ncust_bars3, left=ncust_bars2, edgecolor='grey', height=1, label=\"Premium\")\n",
    "\n",
    "for i in range(7):\n",
    "    budget_width = budget_bar[i].get_width()\n",
    "    budget_main_width = budget_width + mains_bar[i].get_width()\n",
    "    plt.text(budget_width/2, i, ncust_bars1_text[i], va='center', ha='center', size=8)\n",
    "    plt.text(budget_width + mains_bar[i].get_width()/2, i, ncust_bars2_text[i], va='center', ha='center', size=8)\n",
    "    plt.text(budget_main_width + prem_bar[i].get_width()/2, i, ncust_bars3_text[i], va='center', ha='center', size=8)\n",
    "    \n",
    "# Custom X axis\n",
    "plt.yticks(r, names)\n",
    "plt.ylabel(\"LIFESTAGE\")\n",
    "plt.xlabel(\"UNIQUE CUSTOMERS\")\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "\n",
    "plt.title(\"Unique Customers per Lifestage\")\n",
    "\n",
    "plt.savefig(\"lifestage_customers.png\", bbox_inches=\"tight\")\n",
    "\n",
    "# # Show graphic\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9202d43d",
   "metadata": {},
   "source": [
    "The high sales amount by segment \"Young Singles/Couples - Mainstream\" and \"Retirees - Mainstream\" are due to their large number of unique customers, but not for the \"Older - Budget\" segment. Next we'll explore if the \"Older - Budget\" segment has:\n",
    "\n",
    "High Frequency of Purchase and, Average Sales per Customer compared to the other segment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "98abbc93",
   "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></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">OLDER FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>5.031438</td>\n",
       "      <td>2831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>4.954011</td>\n",
       "      <td>4675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>4.923009</td>\n",
       "      <td>2273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">YOUNG FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>4.760269</td>\n",
       "      <td>4017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>4.752569</td>\n",
       "      <td>2433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mainstream</th>\n",
       "      <td>4.731305</td>\n",
       "      <td>2728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">OLDER SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>3.737684</td>\n",
       "      <td>4750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>3.734429</td>\n",
       "      <td>4929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mainstream</th>\n",
       "      <td>3.715619</td>\n",
       "      <td>4930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>3.555090</td>\n",
       "      <td>3340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">RETIREES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>3.412887</td>\n",
       "      <td>4454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>3.382231</td>\n",
       "      <td>3872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>3.379679</td>\n",
       "      <td>2431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>3.337766</td>\n",
       "      <td>1504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>3.313166</td>\n",
       "      <td>6479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">NEW FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>2.738516</td>\n",
       "      <td>849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>2.702381</td>\n",
       "      <td>588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>2.702338</td>\n",
       "      <td>1112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>2.578388</td>\n",
       "      <td>8088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>2.445621</td>\n",
       "      <td>3779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Premium</th>\n",
       "      <td>2.440171</td>\n",
       "      <td>2574</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             mean  count\n",
       "LIFESTAGE              PREMIUM_CUSTOMER                 \n",
       "OLDER FAMILIES         Mainstream        5.031438   2831\n",
       "                       Budget            4.954011   4675\n",
       "                       Premium           4.923009   2273\n",
       "YOUNG FAMILIES         Budget            4.760269   4017\n",
       "                       Premium           4.752569   2433\n",
       "                       Mainstream        4.731305   2728\n",
       "OLDER SINGLES/COUPLES  Premium           3.737684   4750\n",
       "                       Budget            3.734429   4929\n",
       "                       Mainstream        3.715619   4930\n",
       "MIDAGE SINGLES/COUPLES Mainstream        3.555090   3340\n",
       "RETIREES               Budget            3.412887   4454\n",
       "                       Premium           3.382231   3872\n",
       "MIDAGE SINGLES/COUPLES Premium           3.379679   2431\n",
       "                       Budget            3.337766   1504\n",
       "RETIREES               Mainstream        3.313166   6479\n",
       "NEW FAMILIES           Mainstream        2.738516    849\n",
       "                       Premium           2.702381    588\n",
       "                       Budget            2.702338   1112\n",
       "YOUNG SINGLES/COUPLES  Mainstream        2.578388   8088\n",
       "                       Budget            2.445621   3779\n",
       "                       Premium           2.440171   2574"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "freq_per_cust = merged_data.groupby([\"LYLTY_CARD_NBR\", \"LIFESTAGE\", \"PREMIUM_CUSTOMER\"]).count()[\"DATE\"]\n",
    "freq_per_cust.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"]).agg([\"mean\", \"count\"]).sort_values(ascending=False, by=\"mean\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f7fecd7",
   "metadata": {},
   "source": [
    "The above table describes the \"Average frequency of Purchase per segment\" and \"Unique customer per segment\". The top three most frequent purchase is contributed by the \"Older Families\" lifestage segment. We can see now that the \"Older - Budget\" segment contributes to high sales partly because of the combination of:\n",
    "\n",
    "High Frequency of Purchase and, Fairly high unique number of customer in the segment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "82ba0575",
   "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></th>\n",
       "      <th>sum</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIFESTAGE</th>\n",
       "      <th>PREMIUM_CUSTOMER</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>90803.85</td>\n",
       "      <td>7.647284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>157621.60</td>\n",
       "      <td>7.558339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>97646.05</td>\n",
       "      <td>7.456174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>132263.15</td>\n",
       "      <td>7.449766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>113147.80</td>\n",
       "      <td>7.443445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER SINGLES/COUPLES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>136769.80</td>\n",
       "      <td>7.430315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">NEW FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>17013.90</td>\n",
       "      <td>7.317806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>21928.45</td>\n",
       "      <td>7.297321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>139345.85</td>\n",
       "      <td>7.287201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER SINGLES/COUPLES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>133393.80</td>\n",
       "      <td>7.282116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Budget</th>\n",
       "      <td>168363.25</td>\n",
       "      <td>7.269570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>84025.50</td>\n",
       "      <td>7.266756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>103445.55</td>\n",
       "      <td>7.262395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIREES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>155677.05</td>\n",
       "      <td>7.252262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEW FAMILIES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>11491.10</td>\n",
       "      <td>7.231655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDER FAMILIES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>80658.40</td>\n",
       "      <td>7.208079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG FAMILIES</th>\n",
       "      <th>Mainstream</th>\n",
       "      <td>92788.75</td>\n",
       "      <td>7.189025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">MIDAGE SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>58432.65</td>\n",
       "      <td>7.112056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>35514.80</td>\n",
       "      <td>7.074661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">YOUNG SINGLES/COUPLES</th>\n",
       "      <th>Premium</th>\n",
       "      <td>41642.10</td>\n",
       "      <td>6.629852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Budget</th>\n",
       "      <td>61141.60</td>\n",
       "      <td>6.615624</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               sum      mean\n",
       "LIFESTAGE              PREMIUM_CUSTOMER                     \n",
       "MIDAGE SINGLES/COUPLES Mainstream         90803.85  7.647284\n",
       "YOUNG SINGLES/COUPLES  Mainstream        157621.60  7.558339\n",
       "RETIREES               Premium            97646.05  7.456174\n",
       "OLDER SINGLES/COUPLES  Premium           132263.15  7.449766\n",
       "RETIREES               Budget            113147.80  7.443445\n",
       "OLDER SINGLES/COUPLES  Budget            136769.80  7.430315\n",
       "NEW FAMILIES           Mainstream         17013.90  7.317806\n",
       "                       Budget             21928.45  7.297321\n",
       "YOUNG FAMILIES         Budget            139345.85  7.287201\n",
       "OLDER SINGLES/COUPLES  Mainstream        133393.80  7.282116\n",
       "OLDER FAMILIES         Budget            168363.25  7.269570\n",
       "YOUNG FAMILIES         Premium            84025.50  7.266756\n",
       "OLDER FAMILIES         Mainstream        103445.55  7.262395\n",
       "RETIREES               Mainstream        155677.05  7.252262\n",
       "NEW FAMILIES           Premium            11491.10  7.231655\n",
       "OLDER FAMILIES         Premium            80658.40  7.208079\n",
       "YOUNG FAMILIES         Mainstream         92788.75  7.189025\n",
       "MIDAGE SINGLES/COUPLES Premium            58432.65  7.112056\n",
       "                       Budget             35514.80  7.074661\n",
       "YOUNG SINGLES/COUPLES  Premium            41642.10  6.629852\n",
       "                       Budget             61141.60  6.615624"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_sales.sort_values(ascending=False, by=\"mean\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81cbfe6c",
   "metadata": {},
   "source": [
    "Highest average spending per purchase are contributed by the Midage and Young \"Singles/Couples\". The difference between their Mainstream and Non-Mainstream group might seem insignificant (7.6 vs 6.6), but we'll find out by examining if the difference is statistically significant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "eb02dba2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.8542040107534844e-281\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from scipy.stats import ttest_ind\n",
    "mainstream = merged_data[\"PREMIUM_CUSTOMER\"] == \"Mainstream\"\n",
    "young_midage = (merged_data[\"LIFESTAGE\"] == \"MIDAGE SINGLES/COUPLES\") | (merged_data[\"LIFESTAGE\"] == \"YOUNG SINGLES/COUPLES\")\n",
    "\n",
    "budget_premium = (merged_data[\"PREMIUM_CUSTOMER\"] == \"Budget\") | (merged_data[\"PREMIUM_CUSTOMER\"] == \"Premium\")\n",
    "\n",
    "a = merged_data[young_midage & mainstream][\"TOT_SALES\"]\n",
    "b = merged_data[young_midage & budget_premium][\"TOT_SALES\"]\n",
    "stat, pval = ttest_ind(a.values, b.values, equal_var=False)\n",
    "\n",
    "print(pval)\n",
    "pval < 0.0000001"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40ee2e0c",
   "metadata": {},
   "source": [
    "P-Value is close to 0. There is a statistically significant difference to the Total Sales between the \"Mainstream Young Midage\" segment to the \"Budget and Premium Young Midage\" segment.\n",
    "\n",
    "Next, let's look examine what brand of chips the top 3 segments contributing to Total Sales are buying."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "bb9c6d82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LIFESTAGE               PREMIUM_CUSTOMER\n",
       "MIDAGE SINGLES/COUPLES  Budget              Kettle\n",
       "YOUNG FAMILIES          Premium             Kettle\n",
       "                        Mainstream          Kettle\n",
       "                        Budget              Kettle\n",
       "RETIREES                Premium             Kettle\n",
       "                        Mainstream          Kettle\n",
       "                        Budget              Kettle\n",
       "OLDER SINGLES/COUPLES   Premium             Kettle\n",
       "YOUNG SINGLES/COUPLES   Mainstream          Kettle\n",
       "OLDER SINGLES/COUPLES   Mainstream          Kettle\n",
       "OLDER FAMILIES          Mainstream          Kettle\n",
       "                        Budget              Kettle\n",
       "NEW FAMILIES            Premium             Kettle\n",
       "                        Mainstream          Kettle\n",
       "                        Budget              Kettle\n",
       "MIDAGE SINGLES/COUPLES  Premium             Kettle\n",
       "                        Mainstream          Kettle\n",
       "OLDER SINGLES/COUPLES   Budget              Kettle\n",
       "YOUNG SINGLES/COUPLES   Premium             Kettle\n",
       "OLDER FAMILIES          Premium             Smiths\n",
       "YOUNG SINGLES/COUPLES   Budget              Smiths\n",
       "Name: Cleaned_Brand_Names, dtype: object"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"])[\"Cleaned_Brand_Names\"].agg(pd.Series.mode).sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "773f1e09",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG SINGLES/COUPLES - Premium ==========\n",
      "Kettle     838\n",
      "Smiths     826\n",
      "Doritos    570\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG SINGLES/COUPLES - Budget ==========\n",
      "Smiths     1245\n",
      "Kettle     1211\n",
      "Doritos     899\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG SINGLES/COUPLES - Mainstream ==========\n",
      "Kettle      3844\n",
      "Doritos     2541\n",
      "Pringles    2315\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV4AAABVCAYAAAABm4xtAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAK1klEQVR4nO3de7Bd4xnH8e/PEREiSUl0UrfTKOOSZoJTU6KaYloOU/4wzR/M1Iw2bUlRYzpxGdX+0QZTFFVCGTSYcemNuqQtg6jKidyRiog2YmTUFKmUiKd/rPfIynH2cc7Ze797n53fZ2bPXnvttdb75LXPY+13rf0+igjMzCyfbRodgJnZ1saJ18wsMydeM7PMnHjNzDJz4jUzy2zbRgdQL2PHjo329vZGh2FmLWbBggVvRMS4ao7Rsom3vb2drq6uRodhZi1G0ivVHsNDDWZmmTnxmpll5sRrZpZZy47xLn31LdpnPtDoMGwrtXrW8Y0OwZrYJ57xStokaZGkZZLulrRDhe2eGmwQkk6TdO1g9zczG0r6M9SwISImR8RE4H3gu+U3JbUBRMThdYjPzKzlDHSM9wngc5KmSnpU0h3AUgBJ69PzVEmPSbpH0guS5khSeq8zrXtS0tWS7u/ZgKRxku6VND89pqT1X05n3oskLZS0U1X/cjOzBun3GK+kbYHjgIfSqkOBiRHxci+bHwQcCKwF5gFTJHUBNwBHRsTLku6s0NQvgCsj4klJewIPA/sD5wFnRsQ8SSOB//U3djOzZtKfxDtC0qK0/ATwa+Bw4JkKSZf03hqAtG87sB5YVdrnTmB6L/seAxyQTpIBRqWz23nAFZLmAPd1H79M0vTuY7aNquqHJWZmddOfxLshIiaXV6Sk+N8+9nmvtLwptaMK2/a0DXBYRGzosX6WpAeATuBpScdExAvlDSJiNjAbYPj4fTzDu5k1pZz38b4ATJDUnl5Pq7DdI8CM7heSJqfnvSNiaURcCnQB+9UvVDOz+smWeNMZ7BnAQ5KeBF4H3upl07OADklLJD3H5rsozkm3tC0GNgAP5ojbzKzWlLPmmqSREbE+3eXwS+DFiLiyHm11dHSEJ8kxs1qTtCAiOqo5Ru6fDH87XWxbDoymuMvBzGyrkvUnw+nsti5nuGZmQ4UnyTEzy8yJ18wsMydeM7PMnHjNzDJz4jUzy8yJ18wsM1egMGtCrmDR2gZ8xluqSLFc0mJJ50oa0HEkfUbSPWl5sqTOgcZhZjZUDeaM96PZyiTtCtxB8Su0H/VnZ0nbRsRa4OS0ajLQAfxpELGYmQ05VY3xRsQ6ivlvZ6iwvaRbJC1NVSK+Ah/VVLtb0h+BRyS1pwlvtgN+AkxLZ9HTJO0s6XdpkpynJU1Kx3AFCjNrCVWP8UbEqjTUsCtwalr3eUn7USTZfdOmhwGTIuLN7qkhI+J9SRcDHRExA0DSNcDCiDhJ0lHAbRRnxa5AYWYtoVZ3NXRPcn4EcDtAmqT8FaA78c6NiDf7cazyMf4K7CJpNJsrUJwFjImIDz4WhDRdUpekrk3v9jbjpJlZ41WdeCVNoKgysY6+q0z0VbFii0P2si4iYhbwLWAERQWKj02EHhGzI6IjIjradhjdz+bMzPKqKvFKGgdcD1wbxcS+jwOnpPf2BfYEVnzCYd4ByuO15WNMBd6IiLddgcLMWsVgxni7i18OAz6gGBa4Ir13HXC9pKXpvdMi4r1S4crePArMTMf8GXAJcIukJcC7wDfTdueki3WbgOdwBQozG6KyVqDIyRUozKwehmIFCjOzrZ4Tr5lZZk68ZmaZOfGamWXmxGtmlpkTr5lZZk68ZmaZOfGamWXmChRmttVqVKWPmp7xSlpfWu6U9KKkPfvY/oLS8hhJZ5Ret0taVsv4zMyaQV2GGiQdDVwDHBsR/+xj0wtKy2OAMypsZ2bWMmqeeCV9CbgROD4iXkrrTpX0TKoecYOkNkmzSBPuSJoDzAL2Tq8v73HMNkmXS5qfKlN8p9Zxm5nlUusx3uHA74GpaSJ0JO0PTAOmRMRGSdcBp0TETEkzSvXb2oGJPV53Ox14KyK+IGk4ME/SIxHxco3jNzOru1on3o3AUxSJ8uy07mjgEGB+mh5yBMWk6QPxVWCSpO4CmaOBfYAtEq+k6RQ14GgbNW4Q4ZuZ1V+tE++HwDeAP0u6ICJ+SlFR4taIOL+K4wr4fkQ83NdGETEbmA0wfPw+rTnfpZkNeTUf442Id4ETgFMknQ78BTg5lYInVRHeK22+UdKwtNyzEkXZw8D3ureVtK+kHWsdu5lZDnW5qyEVtTwWuIhiSOAiiorDS4C5wPi06WxgiaQ5EfFvirHbZT0vrgE3UVSdeDbdYnYDLXwPspm1NlegMDMbAFegMDMbgpx4zcwyc+I1M8vMidfMLLOWvbgm6R1gRaPjSMYCbzQ6CJonDmieWJolDmieWJolDmjOWPaKiKp+odXKt2StqPbKY61I6mqGWJolDmieWJolDmieWJolDmjdWDzUYGaWmROvmVlmrZx4Zzc6gJJmiaVZ4oDmiaVZ4oDmiaVZ4oAWjaVlL66ZmTWrVj7jNTNrSk68ZmaZtWTilXSspBWSVkqamaG91ZKWprJFXWndzpLmpoKfcyV9qrT9+Sm2FZK+VmXbN0taVy4MOpi2JR2S/g0rJV2tNGt9lXFcIunV1C+LJHVmiGMPSY9Kel7ScklnN7BPKsWStV8kba+i9NbiFMePG9gnlWLJ/llJx2iTtFDS/Vn7JCJa6gG0AS8BE4DtgMXAAXVuczUwtse6y4CZaXkmcGlaPiDFNBz4bIq1rYq2jwQOBpZV0zbwDHAYxaTzDwLH1SCOS4Dzetm2nnGMBw5OyzsB/0jtNaJPKsWStV/SPiPT8jDg78AXG9QnlWLJ/llJxzgXuAO4P+ffTiue8R4KrIyIVRHxPnAXcGID4jgRuDUt3wqcVFp/V0S8F0XNuJUUMQ9KRDwOvFlN25LGA6Mi4m9RfJJuK+1TTRyV1DOO1yLi2bT8DvA8sBuN6ZNKsVRSl1iisD69HJYeQWP6pFIsldQtFkm7A8dTzPddbq/ufdKKiXc34F+l12vo+8NeC0Ex0fsCFXXfAD4dEa9B8QcI7JoxvoG2vVtarkdMM1RUhr659LUtSxwqCqYeRHFW1dA+6RELZO6X9JV6EUW9w7kR0bA+qRAL5P+sXAX8kKJkWbcsfdKKibe38ZV63zM3JSIOBo4DzpR0ZB/bNiK+T2q7XjH9CtgbmAy8Bvw8VxySRgL3AudExNt9bdqAWLL3S0RsiqKC9+4UZ2oT+wq5XnH0EUvWPpF0ArAuIhb0d5daxtGKiXcNsEfp9e7A2no2GBFr0/M64LcUQwevp68hpOfuyso54hto22vSck1jiojX0x/Zh8CNbB5SqWscKmrz3QvMiYj70uqG9ElvsTSqX1Lb/wEeoyjN1dDPSTmWBvTJFODrklZTDEceJek35OqTgQ5GN/uDYuKfVRQD4N0X1w6sY3s7AjuVlp+i+FBfzpaD9Jel5QPZcpB+FVVcXEvHbGfLi1oDbhuYT3GRo/sCQWcN4hhfWv4BxRhZXeNI+90GXNVjffY+6SOWrP0CjAPGpOURwBMUBWkb0SeVYsn+WSm1N5XNF9ey9EldklGjH0AnxRXkl4AL69zWhPQfZDGwvLs9YBeKCssvpuedS/tcmGJbwSCuxPZo/06Kr2YbKf7ve/pg2gY6gGXpvWtJv2qsMo7bgaXAEuAPPf646hXHERRf9ZYAi9Kjs0F9UimWrP0CTAIWpvaWARcP9jNagz6pFEv2z0rpOFPZnHiz9Il/MmxmllkrjvGamTU1J14zs8yceM3MMnPiNTPLzInXzCwzJ14zs8yceM3MMvs/jlA5LcDJ+mAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== MIDAGE SINGLES/COUPLES - Premium ==========\n",
      "Kettle     1206\n",
      "Smiths      986\n",
      "Doritos     837\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== MIDAGE SINGLES/COUPLES - Budget ==========\n",
      "Kettle     713\n",
      "Smiths     633\n",
      "Doritos    533\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== MIDAGE SINGLES/COUPLES - Mainstream ==========\n",
      "Kettle     2136\n",
      "Smiths     1337\n",
      "Doritos    1291\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== NEW FAMILIES - Premium ==========\n",
      "Kettle      247\n",
      "Doritos     167\n",
      "Pringles    165\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== NEW FAMILIES - Budget ==========\n",
      "Kettle     510\n",
      "Doritos    343\n",
      "Smiths     341\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== NEW FAMILIES - Mainstream ==========\n",
      "Kettle     414\n",
      "Doritos    274\n",
      "Smiths     254\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER FAMILIES - Premium ==========\n",
      "Smiths     1515\n",
      "Kettle     1512\n",
      "Doritos    1065\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER FAMILIES - Budget ==========\n",
      "Kettle     3320\n",
      "Smiths     3093\n",
      "Doritos    2351\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER FAMILIES - Mainstream ==========\n",
      "Kettle     2019\n",
      "Smiths     1835\n",
      "Doritos    1449\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER SINGLES/COUPLES - Premium ==========\n",
      "Kettle     2947\n",
      "Smiths     2042\n",
      "Doritos    1958\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER SINGLES/COUPLES - Budget ==========\n",
      "Kettle     3065\n",
      "Smiths     2098\n",
      "Doritos    1954\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER SINGLES/COUPLES - Mainstream ==========\n",
      "Kettle     2835\n",
      "Smiths     2180\n",
      "Doritos    2008\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== RETIREES - Premium ==========\n",
      "Kettle     2216\n",
      "Smiths     1458\n",
      "Doritos    1409\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== RETIREES - Budget ==========\n",
      "Kettle     2592\n",
      "Doritos    1742\n",
      "Smiths     1679\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== RETIREES - Mainstream ==========\n",
      "Kettle     3386\n",
      "Smiths     2476\n",
      "Doritos    2320\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG FAMILIES - Premium ==========\n",
      "Kettle     1745\n",
      "Smiths     1442\n",
      "Doritos    1129\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG FAMILIES - Budget ==========\n",
      "Kettle     2743\n",
      "Smiths     2459\n",
      "Doritos    1996\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG FAMILIES - Mainstream ==========\n",
      "Kettle     1789\n",
      "Smiths     1772\n",
      "Doritos    1309\n",
      "Name: Cleaned_Brand_Names, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for stage in merged_data[\"LIFESTAGE\"].unique():\n",
    "    for prem in merged_data[\"PREMIUM_CUSTOMER\"].unique():\n",
    "        print('==========',stage, '-', prem,'==========')\n",
    "        summary = merged_data[(merged_data[\"LIFESTAGE\"] == stage) & (merged_data[\"PREMIUM_CUSTOMER\"] == prem)][\"Cleaned_Brand_Names\"].value_counts().head(3)\n",
    "        print(summary)\n",
    "        plt.figure()\n",
    "        summary.plot.barh(figsize=(5,1))\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da6ad4bb",
   "metadata": {},
   "source": [
    "Every segment had Kettle as the most purchased brand. Every segment except \"YOUNG SINGLES/COUPLES Mainstream\" had Smiths as their second most purchased brand. \"YOUNG SINGLES/COUPLES Mainstream\" had Doritos as their second most purchased brand.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "6ccfcf95",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting mlxtend\n",
      "  Downloading mlxtend-0.21.0-py2.py3-none-any.whl (1.3 MB)\n",
      "Requirement already satisfied: pandas>=0.24.2 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from mlxtend) (1.4.2)\n",
      "Requirement already satisfied: setuptools in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from mlxtend) (61.2.0)\n",
      "Requirement already satisfied: joblib>=0.13.2 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from mlxtend) (1.1.0)\n",
      "Requirement already satisfied: numpy>=1.16.2 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from mlxtend) (1.21.5)\n",
      "Requirement already satisfied: scipy>=1.2.1 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from mlxtend) (1.7.3)\n",
      "Requirement already satisfied: matplotlib>=3.0.0 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from mlxtend) (3.5.1)\n",
      "Requirement already satisfied: scikit-learn>=1.0.2 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from mlxtend) (1.0.2)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from matplotlib>=3.0.0->mlxtend) (3.0.4)\n",
      "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from matplotlib>=3.0.0->mlxtend) (9.0.1)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from matplotlib>=3.0.0->mlxtend) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from matplotlib>=3.0.0->mlxtend) (4.25.0)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from matplotlib>=3.0.0->mlxtend) (21.3)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from matplotlib>=3.0.0->mlxtend) (2.8.2)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from matplotlib>=3.0.0->mlxtend) (1.3.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from pandas>=0.24.2->mlxtend) (2021.3)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from python-dateutil>=2.7->matplotlib>=3.0.0->mlxtend) (1.16.0)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\users\\alboc\\anaconda3\\lib\\site-packages (from scikit-learn>=1.0.2->mlxtend) (2.2.0)\n",
      "Installing collected packages: mlxtend\n",
      "Successfully installed mlxtend-0.21.0\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install mlxtend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "83e05002",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "20ca7bbd",
   "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>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(OLDER FAMILIES - Budget)</td>\n",
       "      <td>(Smiths)</td>\n",
       "      <td>0.087451</td>\n",
       "      <td>0.120162</td>\n",
       "      <td>0.011679</td>\n",
       "      <td>0.133549</td>\n",
       "      <td>1.111409</td>\n",
       "      <td>0.001171</td>\n",
       "      <td>1.015451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(OLDER SINGLES/COUPLES - Budget)</td>\n",
       "      <td>(Kettle)</td>\n",
       "      <td>0.069504</td>\n",
       "      <td>0.155901</td>\n",
       "      <td>0.011573</td>\n",
       "      <td>0.166513</td>\n",
       "      <td>1.068064</td>\n",
       "      <td>0.000738</td>\n",
       "      <td>1.012731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>(OLDER SINGLES/COUPLES - Premium)</td>\n",
       "      <td>(Kettle)</td>\n",
       "      <td>0.067038</td>\n",
       "      <td>0.155901</td>\n",
       "      <td>0.011128</td>\n",
       "      <td>0.165991</td>\n",
       "      <td>1.064716</td>\n",
       "      <td>0.000676</td>\n",
       "      <td>1.012097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(RETIREES - Mainstream)</td>\n",
       "      <td>(Kettle)</td>\n",
       "      <td>0.081055</td>\n",
       "      <td>0.155901</td>\n",
       "      <td>0.012785</td>\n",
       "      <td>0.157738</td>\n",
       "      <td>1.011779</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>1.002180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>(YOUNG SINGLES/COUPLES - Mainstream)</td>\n",
       "      <td>(Kettle)</td>\n",
       "      <td>0.078744</td>\n",
       "      <td>0.155901</td>\n",
       "      <td>0.014515</td>\n",
       "      <td>0.184329</td>\n",
       "      <td>1.182344</td>\n",
       "      <td>0.002239</td>\n",
       "      <td>1.034852</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            antecedents consequents  antecedent support  \\\n",
       "0             (OLDER FAMILIES - Budget)    (Smiths)            0.087451   \n",
       "2      (OLDER SINGLES/COUPLES - Budget)    (Kettle)            0.069504   \n",
       "5     (OLDER SINGLES/COUPLES - Premium)    (Kettle)            0.067038   \n",
       "6               (RETIREES - Mainstream)    (Kettle)            0.081055   \n",
       "9  (YOUNG SINGLES/COUPLES - Mainstream)    (Kettle)            0.078744   \n",
       "\n",
       "   consequent support   support  confidence      lift  leverage  conviction  \n",
       "0            0.120162  0.011679    0.133549  1.111409  0.001171    1.015451  \n",
       "2            0.155901  0.011573    0.166513  1.068064  0.000738    1.012731  \n",
       "5            0.155901  0.011128    0.165991  1.064716  0.000676    1.012097  \n",
       "6            0.155901  0.012785    0.157738  1.011779  0.000149    1.002180  \n",
       "9            0.155901  0.014515    0.184329  1.182344  0.002239    1.034852  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from mlxtend.frequent_patterns import apriori\n",
    "from mlxtend.frequent_patterns import association_rules\n",
    "\n",
    "temp = merged_data.reset_index().rename(columns = {\"index\": \"transaction\"})\n",
    "temp[\"Segment\"] = temp[\"LIFESTAGE\"] + ' - ' + temp['PREMIUM_CUSTOMER']\n",
    "segment_brand_encode = pd.concat([pd.get_dummies(temp[\"Segment\"]), pd.get_dummies(temp[\"Cleaned_Brand_Names\"])], axis=1)\n",
    "\n",
    "frequent_sets = apriori(segment_brand_encode, min_support=0.01, use_colnames=True)\n",
    "rules = association_rules(frequent_sets, metric=\"lift\", min_threshold=1)\n",
    "\n",
    "set_temp = temp[\"Segment\"].unique()\n",
    "rules[rules[\"antecedents\"].apply(lambda x: list(x)).apply(lambda x: x in set_temp)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77957e38",
   "metadata": {},
   "source": [
    "By looking at our a-priori analysis, we can conclude that Kettle is the brand of choice for most segment.\n",
    "\n",
    "Next, we'll find out the pack size preferences of different segments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "bfdc3297",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG SINGLES/COUPLES - Premium ==========\n",
      "134.0     537\n",
      "150.0     961\n",
      "175.0    1587\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG SINGLES/COUPLES - Budget ==========\n",
      "134.0     832\n",
      "150.0    1439\n",
      "175.0    2262\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG SINGLES/COUPLES - Mainstream ==========\n",
      "134.0    2315\n",
      "150.0    3159\n",
      "175.0    4928\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== MIDAGE SINGLES/COUPLES - Premium ==========\n",
      "134.0     781\n",
      "150.0    1285\n",
      "175.0    2034\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== MIDAGE SINGLES/COUPLES - Budget ==========\n",
      "134.0     449\n",
      "150.0     821\n",
      "175.0    1256\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== MIDAGE SINGLES/COUPLES - Mainstream ==========\n",
      "134.0    1159\n",
      "150.0    1819\n",
      "175.0    2912\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== NEW FAMILIES - Premium ==========\n",
      "134.0    165\n",
      "150.0    245\n",
      "175.0    371\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== NEW FAMILIES - Budget ==========\n",
      "134.0    309\n",
      "150.0    448\n",
      "175.0    763\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAVIAAABVCAYAAAAbp2zjAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAJH0lEQVR4nO3de4xcdRnG8e/jApWWu4um0OK2pjYphiy4QRAhyEXaagA1akmImGAqCSSiMdpKghBjgnjBP4wQxEujWKilQlM1lOAtMUbcpRe20LUUFrpcWi6xWDUGy+sf5zfp7HaGljkz85sZnk8y2TNn5pzz9Ozpu3PmzLw/RQRmZta4t+QOYGbW7VxIzcxKciE1MyvJhdTMrCQXUjOzkg7JHeCN6O/vj4GBgdwxzKzHjIyMvBgRxze6fFcV0oGBAYaHh3PHMLMeI+mpMsv71N7MrCQXUjOzklxIzcxK6qr3SB95ZjcDy36dO4aZdbDxmz7c9m0e8BWppB9L2iVptGre3ZI2ptu4pI1p/oCk/1Q9dluddR4n6QFJ29LPY5v2LzIza7ODObX/KbCwekZEfCoiBiNiELgHWFP18PbKYxFxVZ11LgMejIh5wIPpvplZVzpgIY2IPwEv13pMkoBPAivf4HYvAVak6RXApW9weTOzjlH2YtPZwM6I2FY1b46kDZL+KOnsOsu9IyKeA0g/314yh5lZNmUvNl3G5FejzwEnRcRLkt4L3Cvp5Ih4pdENSFoKLAXoO6rhLx6YmbVMw69IJR0CfAy4uzIvIv4bES+l6RFgO/DuGovvlDQzrWcmsKvediLi9ogYioihvulHNxrXzKxlypzaXwBsjYiJygxJx0vqS9NzgXnAEzWWXQtckaavAO4rkcPMLKuD+fjTSuAvwHxJE5KuTA8tYf+LTOcAmyVtAlYDV0XEy2k9d0gaSs+7CbhQ0jbgwnTfzKwrqZvGbBoaGgo3LTGzZpM0EhFDB35mbf6KqJlZSS6kZmYluZCamZXkQmpmVpILqZlZSS6kZmYluZCamZXkQmpmVpI75JvVkaPTunWnRjvk3yDpmapO+IurHlsu6XFJY5IuqrNOd8g3s57RUIf85JaqTvi/AZC0gOI7+CenZX5QaWIyhTvkm1nPKNUhv4ZLgLtSO70ngceB0+s8zx3yzawnlLnYdI2kzenUv3JqfiKwo+o5E2neVO6Qb2Y9o9FCeivwLmCQoiv+d9J81XhuqfZSkpZKGpY0vPffu8usysysJRoqpBGxMyL2RsRrwA/Zd/o+Acyueuos4Nkaq3CHfDPrGQ0V0koRTD4KVK7orwWWSJomaQ5Fh/yHaqzCHfLNrGcc8HOkqUP+uUC/pAnga8C5kgYpTtvHgc8BRMQWSauAR4H/AVdHxN60njuA2yJimKIj/qrUbf9p4BPN/WeZmbWPO+Sb2ZueO+SbmWXmQmpmVpILqZlZSS6kZmYluZCamZXkQmpmVpILqZlZSS6kZmYluUO+tYw7zNubRaMd8r+eWuhtlLRe0glTljlJ0h5JX6qzTnfIN7Oe0WiH/G9FxCkRMQisA66f8vgtwG9fZ53ukG9mPaOhDvkR8UrV3RlU9RyVdCnwBLDldVbrDvlm1jMafo9U0jeATwO7gQ+meTOArwAXAjVP65NJHfIluUO+mXWthq/aR8R1ETEbuBO4Js2+kWJQvD3NCAfukG9mna8ZH3/6BfDxNP0+4GZJ48C1wFclXVNjGXfIN7Oe0dCpvaR5EbEt3b0Y2AoQEWdXPecGYE9EfL/GKiod8m/CHfLNrMs12iF/saT5wGvAU8BVB7Eed8g3s57kDvlm9qbnDvlmZpm5kJqZleRCamZWkgupmVlJXXWxSdI/gbHcOZJ+4MXcIZJOydIpOcBZ6nGW2uZHxJGNLtxVbfSAsTJX1ppJ0rCzdGYOcJZ6nKU2SaU+DuRTezOzklxIzcxK6rZCenvuAFWcZX+dkgOcpR5nqa1Ulq662GRm1om67RWpmVnHcSE1MyupKwqppIWSxiQ9Lqnl4zvVGfCv7oB9kpanbGOSLmpyltmSfi/pMUlbJH0+Vx5Jb5X0kKRNKcuNubKkdfdJ2iBpXeYc45IeSYNBDmfOcoyk1ZK2pmPmzEzHyvy0Pyq3VyRdm3G/fCEds6OSVqZjuXlZIqKjb0AfsB2YCxwGbAIWtHib5wCnAaNV824GlqXpZcA30/SClGkaMCdl7WtilpnAaWn6SODvaZttzwMIOCJNHwr8FTgj4775IkVj8XWZf0fjQP+UebmyrAA+m6YPA47JlaUqUx/wPPDOTMfticCTwOHp/irgM83M0tQd1oobcCZwf9X95cDyNmx3gMmFdAyYmaZnUnw5YL88wP3AmS3MdR/FmFhZ8wDTgYcpRkVoexZgFsUItOexr5Bm2SfULqQ59slRqWAod5Yp2/8Q8OeM++VEYAdwHMWXkNalTE3L0g2n9pWdUDGR5rXbpAH7gMqAfW3LJ2kAOJXilWCWPOl0eiPF8DAPRESuLN8DvkzRXLwi1+8ogPWSRiQtzZhlLvAC8JP0lscdKgakzH3sLgFWpum2Z4mIZ4BvUzSRfw7YHRHrm5mlGwqpaszrpM9stSWfpCOAe4BrY/Jw2G3NExF7I2KQ4hXh6ZLe0+4skj4C7IqIkYNdpBU5qpwVEacBi4CrJZ2TKcshFG9J3RoRpwL/ojhlzZGl2IB0GMVwRL880FNblSW993kJxWn6CcAMSZc3M0s3FNIJYHbV/VnAsxly1Buwr+X5JB1KUUTvjIg1ufMARMQ/gD8ACzNkOQu4WMUgi3cB50n6eYYcAETEs+nnLuBXwOmZskwAE+ksAWA1RWHNeawsAh6OiJ3pfo4sFwBPRsQLEfEqsAZ4fzOzdEMh/RswT9Kc9NdtCcXgee1WGbAPJg/YtxZYImmapDnAPOChZm1UkoAfAY9FxHdz5pF0vKRj0vThFAfo1nZniYjlETErIgYojoffRcTl7c4BIGmGpCMr0xTvvY3myBIRzwM7VIynBnA+8GiOLFUuY99pfWWb7c7yNHCGpOnp/9P5wGNNzdLsN5ZbcQMWU1yt3g5c14btraR4L+VVir9OVwJvo7i4sS39PK7q+delbGPAoiZn+QDFacVmYGO6Lc6RBzgF2JCyjALXp/lZ9k1a/7nsu9iUY5/MpbjCuwnYUjk+Mx4vg8Bw+h3dCxybMct04CXg6Kp5ubLcSPFHfxT4GcUV+aZl8VdEzcxK6oZTezOzjuZCamZWkgupmVlJLqRmZiW5kJqZleRCamZWkgupmVlJ/wfiAvkNMgtkVgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== NEW FAMILIES - Mainstream ==========\n",
      "134.0    224\n",
      "150.0    384\n",
      "175.0    579\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER FAMILIES - Premium ==========\n",
      "134.0    1014\n",
      "150.0    1750\n",
      "175.0    2747\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER FAMILIES - Budget ==========\n",
      "134.0    1996\n",
      "150.0    3708\n",
      "175.0    5662\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER FAMILIES - Mainstream ==========\n",
      "134.0    1234\n",
      "150.0    2261\n",
      "175.0    3489\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER SINGLES/COUPLES - Premium ==========\n",
      "134.0    1744\n",
      "150.0    2854\n",
      "175.0    4382\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER SINGLES/COUPLES - Budget ==========\n",
      "134.0    1843\n",
      "150.0    2899\n",
      "175.0    4535\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== OLDER SINGLES/COUPLES - Mainstream ==========\n",
      "134.0    1720\n",
      "150.0    2875\n",
      "175.0    4422\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== RETIREES - Premium ==========\n",
      "134.0    1331\n",
      "150.0    2015\n",
      "175.0    3232\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== RETIREES - Budget ==========\n",
      "134.0    1517\n",
      "150.0    2381\n",
      "175.0    3768\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== RETIREES - Mainstream ==========\n",
      "134.0    2103\n",
      "150.0    3415\n",
      "175.0    5187\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG FAMILIES - Premium ==========\n",
      "134.0    1007\n",
      "150.0    1832\n",
      "175.0    2926\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG FAMILIES - Budget ==========\n",
      "134.0    1674\n",
      "150.0    2981\n",
      "175.0    4800\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "========== YOUNG FAMILIES - Mainstream ==========\n",
      "134.0    1148\n",
      "150.0    2101\n",
      "175.0    3087\n",
      "Name: Pack_Size, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUkAAABVCAYAAADE6Rb8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAIfUlEQVR4nO3db4xcVRnH8e/PpVQtoOJWU9vitmQlKYasZYMYbYMJlVITCxq1voEXJLUJTeQFicUmWGJMKgZJDBECSESDLURQG/8kkMY/b4h1V7b/LOtuyyLbNm2AWNpoUNvHF/eMnS53bruz8+de+vskk7lz7r1nnzl0HubMnXmOIgIzM8v3jm4HYGZWZk6SZmYFnCTNzAo4SZqZFXCSNDMrcEG3A5iO3t7e6Ovr63YYZvY2Mzw8/GpEzM3bV6kk2dfXx9DQULfDMLO3GUkvN9rn6baZWQEnSTOzAk6SZmYFKvWZ5O6Dx+jb8Otuh2FmJTax+bMt7e+s7yQlPSbpqKQ9dW1PShpJtwlJI6m9T9K/6vY91KDPSyU9J2ks3b+vZc/IzKyFzmW6/SNgZX1DRHw5IgYiYgB4Gnimbvf+2r6IWNegzw3A9ojoB7anx2ZmpXPWJBkRfwRez9snScCXgC3T/LurgcfT9uPATdM838ysI2Z64WYZcCQixuraFkl6QdIfJC1rcN4HI+IwQLr/wAzjMDNri5leuPkKZ76LPAxcFhGvSboa+IWkKyPijWb/gKS1wFqAnktyvxBvZtY2Tb+TlHQB8HngyVpbRLwZEa+l7WFgP/CRnNOPSJqX+pkHHG30dyLi4YgYjIjBnne/p9lwzcyaMpPp9vXAixExWWuQNFdST9peDPQDB3LO3QbcmrZvBX45gzjMzNrmXL4CtAV4HrhC0qSk29KuNbz1gs1yYJekncDPgHUR8Xrq51FJg+m4zcAKSWPAivTYzKx0VKU1bgYHB8MFLsys1SQNR8Rg3j7/LNHMrICTpJlZASdJM7MCTpJmZgWcJM3MCjhJmpkVcJI0MyvgJGlmVsCVyc26qNVVtK31mq1MvknSwboK5Kvq9t0laVzSqKQbGvTpyuRmVglNVSZP7q+rQP4bAElLyH7TfWU65we1ghdTuDK5mVXCjCqT51gNbE0l014CxoFrGhznyuRmVnozuXCzXtKuNB2vTZfnA6/UHTOZ2qZyZXIzq4Rmk+SDwOXAAFk18vtSu3KOnVGZIUlrJQ1JGjr5z2Mz6crMbNqaSpIRcSQiTkbEKeARTk+pJ4GFdYcuAA7ldOHK5GZWCU0lyVqCS24Gale+twFrJM2WtIisMvmOnC5cmdzMKuGs35NMlcmvA3olTQLfBK6TNEA2lZ4AvgoQEXslPQX8FfgvcHtEnEz9PAo8FBFDZJXIn0pVzv8OfLG1T8vMrDVcmdzMznuuTG5m1iQnSTOzAk6SZmYFnCTNzAo4SZqZFXCSNDMr4CRpZlbASdLMrIArk1tTXFHbzhfNVib/ViqTNiLpWUkfmnLOZZJOSLqzQZ+uTG5mldBsZfLvRsRVETEA/Aq4e8r++4HfFvTpyuRmVglNVSaPiDfqHs6hrmakpJuAA8Degm5dmdzMKqHpzyQlfRu4BTgGfDq1zQG+DqwAcqfayRmVySW5MrmZlVLTV7cjYmNELASeANan5nvIFgg70YrgwJXJzay7WvEVoJ8CX0jbHwfulTQB3AF8Q9L6nHNcmdzMKqGp6bak/ogYSw8/B7wIEBHL6o7ZBJyIiAdyuqhVJt+MK5ObWYk1W5l8laQrgFPAy8C6c+jHlcnNrHJcmdzMznuuTG5m1iQnSTOzAk6SZmYFnCTNzApU6sKNpOPAaLfjOEe9wKvdDuIcOdb2cKzt0Y5YPxwRc/N2VKpUGjDa6ApU2Ugacqyt51jbw7E25um2mVkBJ0kzswJVS5IPdzuAaXCs7eFY28OxNlCpCzdmZp1WtXeSZmYd5SRpZlagEklS0kpJo5LGJZViPRxJE5J2p8XQhlJbwwXOJN2V4h+VdEObY8tbvG3asUm6Oj3HcUnfl6QOxbpJ0sE0tiOSVpUk1oWSfidpn6S9kr6W2ks3tgWxlm5sJb1T0g5JO1Os96T2coxrRJT6BvQA+4HFwIXATmBJCeKaAHqntN0LbEjbG4DvpO0lKe7ZwKL0fHraGNtyYCmwZyaxATuATwAiW9jtxg7Fugm4M+fYbsc6D1iati8G/pZiKt3YFsRaurFN/V6UtmcBfwKuLcu4VuGd5DXAeEQciIh/A1vJFhIro0YLnK0GtkbEmxHxEjBO9rzaInIWb5tubMoqxl8SEc9H9q/vx7RhwbYGsTbS7VgPR8Rf0vZxYB8wnxKObUGsjXQz1ojTS77MSregJONahSQ5H3il7vEkxf+xOyWAZyUNS1qb2s5Y4AyoLXBWhucw3djmp+2p7Z2yXtna7o/VTbNKE6ukPuBjZO96Sj22U2KFEo6tpB5JI2RLuTwXEaUZ1yokybzPFMrwvaVPRsRS4EbgdknLC44t63OAxrF1M+YHgcuBAeAwcF9qL0Wski4CngbuiDOXV37LoTltHY03J9ZSjm1EnIyIAWAB2bvCjxYc3tFYq5AkJ4GFdY8XAIe6FMv/RcShdH8U+DnZ9LnRAmdleA7TjW0ybU9tb7uIOJJeNKeARzj90UTXY5U0iyzpPBERz6TmUo5tXqxlHtsU3z+A3wMrKcm4ViFJ/hnol7RI0oXAGrKFxLpG0hxJF9e2gc8Aezi9wBmcucDZNmCNpNmSFgH9ZB8wd9K0YkvTm+OSrk1XCG+hQwu21V4Yyc1kY9v1WFPfPwT2RcT36naVbmwbxVrGsZU0V9J70/a7gOvJFhcsx7i28ipVu27AKrKrc/uBjSWIZzHZ1bWdwN5aTMD7ge3AWLq/tO6cjSn+Udpw5XVKfFvIplL/Ifu/623NxAYMkr2I9gMPkH6h1YFYfwLsBnalF8S8ksT6KbLp2y5gJN1WlXFsC2It3dgCVwEvpJj2AHc3+3pqR6z+WaKZWYEqTLfNzLrGSdLMrICTpJlZASdJM7MCTpJmZgWcJM3MCjhJmpkV+B8NyT/nKOlYJwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "merged_pack = pd.concat([merged_data, pack_sizes.rename(\"Pack_Size\")], axis=1)\n",
    "\n",
    "for stage in merged_data[\"LIFESTAGE\"].unique():\n",
    "    for prem in merged_data[\"PREMIUM_CUSTOMER\"].unique():\n",
    "        print('==========',stage, '-', prem,'==========')\n",
    "        summary = merged_pack[(merged_pack[\"LIFESTAGE\"] == stage) & (merged_pack[\"PREMIUM_CUSTOMER\"] == prem)][\"Pack_Size\"].value_counts().head(3).sort_index()\n",
    "        print(summary)\n",
    "        plt.figure()\n",
    "        summary.plot.barh(figsize=(5,1))\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "bec2911d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LIFESTAGE               PREMIUM_CUSTOMER\n",
       "OLDER FAMILIES          Mainstream          9.804309\n",
       "                        Budget              9.639572\n",
       "                        Premium             9.578091\n",
       "YOUNG FAMILIES          Budget              9.238486\n",
       "                        Premium             9.209207\n",
       "                        Mainstream          9.180352\n",
       "OLDER SINGLES/COUPLES   Premium             7.154947\n",
       "                        Budget              7.145466\n",
       "                        Mainstream          7.098783\n",
       "MIDAGE SINGLES/COUPLES  Mainstream          6.796108\n",
       "RETIREES                Budget              6.458015\n",
       "                        Premium             6.426653\n",
       "MIDAGE SINGLES/COUPLES  Premium             6.386672\n",
       "                        Budget              6.313830\n",
       "RETIREES                Mainstream          6.253743\n",
       "NEW FAMILIES            Mainstream          5.087161\n",
       "                        Premium             5.028912\n",
       "                        Budget              5.009892\n",
       "YOUNG SINGLES/COUPLES   Mainstream          4.776459\n",
       "                        Budget              4.411485\n",
       "                        Premium             4.402098\n",
       "dtype: float64"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(temp.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"])[\"PROD_QTY\"].sum() / temp.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"])[\"LYLTY_CARD_NBR\"].nunique()).sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "3e6618f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(temp.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"])[\"PROD_QTY\"].sum() / temp.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"])[\"LYLTY_CARD_NBR\"].nunique()).unstack().plot.bar(figsize=(15,4), rot=0)\n",
    "plt.legend(loc=\"center left\", bbox_to_anchor=(1.0, 0.5))\n",
    "plt.savefig(\"Average purchase quantity per segment.png\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "86fce8c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Segment\n",
       "YOUNG SINGLES/COUPLES - Mainstream     4.071485\n",
       "MIDAGE SINGLES/COUPLES - Mainstream    4.000101\n",
       "RETIREES - Budget                      3.924883\n",
       "RETIREES - Premium                     3.921323\n",
       "NEW FAMILIES - Budget                  3.919251\n",
       "NEW FAMILIES - Mainstream              3.916581\n",
       "OLDER SINGLES/COUPLES - Premium        3.887220\n",
       "OLDER SINGLES/COUPLES - Budget         3.877022\n",
       "NEW FAMILIES - Premium                 3.871743\n",
       "RETIREES - Mainstream                  3.833343\n",
       "OLDER SINGLES/COUPLES - Mainstream     3.803800\n",
       "YOUNG FAMILIES - Budget                3.753659\n",
       "MIDAGE SINGLES/COUPLES - Premium       3.752915\n",
       "YOUNG FAMILIES - Premium               3.752402\n",
       "OLDER FAMILIES - Budget                3.733344\n",
       "MIDAGE SINGLES/COUPLES - Budget        3.728496\n",
       "OLDER FAMILIES - Mainstream            3.727383\n",
       "YOUNG FAMILIES - Mainstream            3.707097\n",
       "OLDER FAMILIES - Premium               3.704625\n",
       "YOUNG SINGLES/COUPLES - Premium        3.645518\n",
       "YOUNG SINGLES/COUPLES - Budget         3.637681\n",
       "Name: Unit_Price, dtype: float64"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Average chips price per transaction by segments\n",
    "temp[\"Unit_Price\"] = temp[\"TOT_SALES\"] / temp[\"PROD_QTY\"]\n",
    "temp.groupby([\"Segment\"]).mean()[\"Unit_Price\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "eff56227",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1f096b74ee0>"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp.groupby([\"LIFESTAGE\", \"PREMIUM_CUSTOMER\"]).mean()[\"Unit_Price\"].unstack().plot.bar(figsize=(15,4), rot=0)\n",
    "plt.legend(loc=\"center left\", bbox_to_anchor=(1,0.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "79739a87",
   "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>Segment</th>\n",
       "      <th>Cleaned_Brand_Names</th>\n",
       "      <th>TOT_SALES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Kettle</td>\n",
       "      <td>35423.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Doritos</td>\n",
       "      <td>21705.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Pringles</td>\n",
       "      <td>16006.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Smiths</td>\n",
       "      <td>15265.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Infuzions</td>\n",
       "      <td>8749.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Old</td>\n",
       "      <td>8180.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Twisties</td>\n",
       "      <td>7539.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Tostitos</td>\n",
       "      <td>7238.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Thins</td>\n",
       "      <td>7217.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Cobs</td>\n",
       "      <td>6144.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>RRD</td>\n",
       "      <td>4958.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Tyrrells</td>\n",
       "      <td>4800.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Grain Waves</td>\n",
       "      <td>4201.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Cheezels</td>\n",
       "      <td>3318.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Natural Chip Co</td>\n",
       "      <td>2130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Woolworths</td>\n",
       "      <td>1929.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Cheetos</td>\n",
       "      <td>898.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>CCs</td>\n",
       "      <td>850.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>383</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>French</td>\n",
       "      <td>429.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Sunbites</td>\n",
       "      <td>391.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>YOUNG SINGLES/COUPLES - Mainstream</td>\n",
       "      <td>Burger</td>\n",
       "      <td>243.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Segment Cleaned_Brand_Names  TOT_SALES\n",
       "0    YOUNG SINGLES/COUPLES - Mainstream              Kettle    35423.6\n",
       "8    YOUNG SINGLES/COUPLES - Mainstream             Doritos    21705.9\n",
       "23   YOUNG SINGLES/COUPLES - Mainstream            Pringles    16006.2\n",
       "24   YOUNG SINGLES/COUPLES - Mainstream              Smiths    15265.7\n",
       "55   YOUNG SINGLES/COUPLES - Mainstream           Infuzions     8749.4\n",
       "59   YOUNG SINGLES/COUPLES - Mainstream                 Old     8180.4\n",
       "65   YOUNG SINGLES/COUPLES - Mainstream            Twisties     7539.8\n",
       "73   YOUNG SINGLES/COUPLES - Mainstream            Tostitos     7238.0\n",
       "74   YOUNG SINGLES/COUPLES - Mainstream               Thins     7217.1\n",
       "92   YOUNG SINGLES/COUPLES - Mainstream                Cobs     6144.6\n",
       "124  YOUNG SINGLES/COUPLES - Mainstream                 RRD     4958.1\n",
       "129  YOUNG SINGLES/COUPLES - Mainstream            Tyrrells     4800.6\n",
       "148  YOUNG SINGLES/COUPLES - Mainstream         Grain Waves     4201.0\n",
       "189  YOUNG SINGLES/COUPLES - Mainstream            Cheezels     3318.3\n",
       "246  YOUNG SINGLES/COUPLES - Mainstream     Natural Chip Co     2130.0\n",
       "258  YOUNG SINGLES/COUPLES - Mainstream          Woolworths     1929.8\n",
       "318  YOUNG SINGLES/COUPLES - Mainstream             Cheetos      898.8\n",
       "327  YOUNG SINGLES/COUPLES - Mainstream                 CCs      850.5\n",
       "383  YOUNG SINGLES/COUPLES - Mainstream              French      429.0\n",
       "393  YOUNG SINGLES/COUPLES - Mainstream            Sunbites      391.0\n",
       "415  YOUNG SINGLES/COUPLES - Mainstream              Burger      243.8"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z = temp.groupby([\"Segment\", \"Cleaned_Brand_Names\"]).sum()[\"TOT_SALES\"].sort_values(ascending=False).reset_index()\n",
    "z[z[\"Segment\"] == \"YOUNG SINGLES/COUPLES - Mainstream\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7b9cc17",
   "metadata": {},
   "source": [
    "# Trends and Insights :\n",
    "\n",
    "\n",
    "Top 3 total sales contributor segment are\n",
    "\n",
    "-Older families (Budget) $156,864\n",
    "\n",
    "-Young Singles/Couples (Mainstream) $147,582\n",
    "\n",
    "-Retirees (Mainstream) $145,169\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "1.Young Singles/Couples (Mainstream) has the highest population, followed by Retirees (Mainstream). Which explains their high total sales.\n",
    "\n",
    "2.Despite Older Families not having the highest population, they have the highest frequency of purchase, which contributes to their high total sales.\n",
    "\n",
    "3.Older Families followed by Young Families has the highest average quantity of chips bought per purchase.\n",
    "\n",
    "4.The Mainstream category of the \"Young and Midage Singles/Couples\" have the highest spending of chips per purchase. And the difference to the non-Mainstream \"Young and Midage Singles/Couples\" are statistically significant.\n",
    "\n",
    "5.Chips brand Kettle is dominating every segment as the most purchased brand.\n",
    "\n",
    "6.Observing the 2nd most purchased brand, \"Young and Midage Singles/Couples\" is the only segment with a different preference (Doritos) as compared to others' (Smiths).\n",
    "\n",
    "7.Most frequent chip size purchased is 175gr followed by the 150gr chip size for all segments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf52e827",
   "metadata": {},
   "outputs": [],
   "source": [
    "Views and Recommendations:\n",
    "Older Families:\n",
    "Focus on the Budget segment. Strength: Frequent purchase. We can give promotions that encourages more frequency of purchase. Strength: High quantity of chips purchased per visit. We can give promotions that encourage them to buy more quantity of chips per purchase.\n",
    "\n",
    "Young Singles/Couples:\n",
    "Focus on the Mainstream segment. This segment is the only segment that had Doritos as their 2nd most purchased brand (after Kettle). To specifically target this segment it might be a good idea to collaborate with Doritos merchant to do some branding promotion catered to \"Young Singles/Couples - Mainstream\" segment. Strength: Population quantity. We can spend more effort on making sure our promotions reach them, and it reaches them frequently.\n",
    "\n",
    "Retirees:\n",
    "Focus on the Mainstream segment. Strength: Population quantity. Again, since their population quantity is the contributor to the high total sales, we should spend more effort on making sure our promotions reaches as many of them as possible and frequent.\n",
    "\n",
    "General:\n",
    "All segments has Kettle as the most frequently purchased brand, and 175gr (regardless of brand) followed by 150gr as the preferred chip size. When promoting chips in general to all segments it is good to take advantage of these two points."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}