1. Problem Definition & EDA.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Business Problem Definition\n",
    "\n",
    "This EDA notebook examines financial and operational performance of the grocer from historical montly sales data. \n",
    "\n",
    "Products and product categories are examined and operation changes are recommended based on historical data and industry competative dynamics. \n",
    "\n",
    "For a complete write up, including the analysis of strategic alternatives and specific recommendations, please see the **PPT** presentation. \n",
    "\n",
    "For complete PPT presentation please see https://www.dropbox.com/s/ezenffm4bbrutar/grocer.pdf?dl=0\n",
    "\n",
    "\n",
    "### Business Objectives\n",
    "#### Short term objectives - focus on business understanding\n",
    "- Time frame < 1 year\n",
    "- Make mom & pop management comprehend the competitive landscape\n",
    "- Communicate insights from sales data and adopt industry best practice in sourcing, inventory management etc…\n",
    "- Find defensible market positioning amid worsening competitive environment\n",
    "\n",
    "#### Medium term objectives - business transformation\n",
    "- Time frame 1 - 2 years\n",
    "- Execute on repositioning\n",
    "- Adopt industry best practices\n",
    "- Use data as competitive advantage\n",
    "\n",
    "\n",
    "### Summary of Recommendations (Taken from PPT)\n",
    "\n",
    "<img src=\"static_assets/recommendation.PNG\" alt=\"Drawing\" style=\"width: 700px;\"/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "__author__ = \"Victor Xu\"\n",
    "__email__ = \"victor.c.xu@gmail.com\"\n",
    "__website__ = \"victorxu.me\"\n",
    "\n",
    "__powerpoint_presentation__ = \"https://www.dropbox.com/s/ezenffm4bbrutar/grocer.pdf?dl=0\"\n",
    "__write_up__ = \"coming soon\"\n",
    "\n",
    "__copyright__ = \"Copyright 2019, Victor Xu\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from src.data_loader import load_monthly_data "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load the Data & Cleaning\n",
    "\n",
    "**Data Files**\n",
    "\n",
    "monthly_sale_by_sku.csv\n",
    "\n",
    "    Monthly sales data with SKU number, products groups, names, amount sold, cost of goods sold, and contribution margin. \n",
    "    Data from year 2018. Products group in English, products names in Polish.\n",
    "    \n",
    "    Original file name from Kaggle is Sale1.csv. File is renamed but data is not altered.\n",
    "\n",
    "Setting up the dataframe containing monthly sales data, including sku, cost of goods sold (COGS), contribution margin etc..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "abr_month = ['jan', 'feb', 'mar', 'apr', 'may', 'jun', 'jul',\n",
    "            'aug', 'sep', 'oct', 'nov', 'dec']\n",
    "\n",
    "monthly = load_monthly_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examine the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "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>sku</th>\n",
       "      <th>group</th>\n",
       "      <th>name</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit_cogs</th>\n",
       "      <th>agg_cogs</th>\n",
       "      <th>unit_revenue</th>\n",
       "      <th>gross_margin</th>\n",
       "      <th>unit_contribution</th>\n",
       "      <th>agg_dollar_contribution</th>\n",
       "      <th>share_of_margin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>5307</td>\n",
       "      <td>chemistry</td>\n",
       "      <td>patyczki bella 200</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.77</td>\n",
       "      <td>1.77</td>\n",
       "      <td>2.57</td>\n",
       "      <td>31.13</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>5986</td>\n",
       "      <td>chemistry</td>\n",
       "      <td>ace 1 l</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.20</td>\n",
       "      <td>5.68</td>\n",
       "      <td>43.66</td>\n",
       "      <td>2.48</td>\n",
       "      <td>2.48</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>399</td>\n",
       "      <td>dairy_chesse</td>\n",
       "      <td>almette czosnek niedzwiedzi 150gr</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.68</td>\n",
       "      <td>10.72</td>\n",
       "      <td>3.80</td>\n",
       "      <td>29.47</td>\n",
       "      <td>1.12</td>\n",
       "      <td>4.48</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>2246</td>\n",
       "      <td>dairy_chesse</td>\n",
       "      <td>almette jogurtowy 150g hochland</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.68</td>\n",
       "      <td>10.72</td>\n",
       "      <td>3.80</td>\n",
       "      <td>29.47</td>\n",
       "      <td>1.12</td>\n",
       "      <td>4.48</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>2247</td>\n",
       "      <td>dairy_chesse</td>\n",
       "      <td>almette ogorek/ziola 150g</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.68</td>\n",
       "      <td>10.72</td>\n",
       "      <td>2.85</td>\n",
       "      <td>5.96</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date   sku         group                               name  quantity  \\\n",
       "0 2018-01-01  5307     chemistry                 patyczki bella 200       1.0   \n",
       "1 2018-01-01  5986     chemistry                            ace 1 l       1.0   \n",
       "2 2018-01-01   399  dairy_chesse  almette czosnek niedzwiedzi 150gr       4.0   \n",
       "3 2018-01-01  2246  dairy_chesse    almette jogurtowy 150g hochland       4.0   \n",
       "4 2018-01-01  2247  dairy_chesse          almette ogorek/ziola 150g       4.0   \n",
       "\n",
       "  unit_cogs  agg_cogs  unit_revenue  gross_margin  unit_contribution  \\\n",
       "0      1.77      1.77          2.57         31.13               0.80   \n",
       "1       3.2      3.20          5.68         43.66               2.48   \n",
       "2      2.68     10.72          3.80         29.47               1.12   \n",
       "3      2.68     10.72          3.80         29.47               1.12   \n",
       "4      2.68     10.72          2.85          5.96               0.17   \n",
       "\n",
       "   agg_dollar_contribution  share_of_margin  \n",
       "0                     0.80             0.01  \n",
       "1                     2.48             0.03  \n",
       "2                     4.48             0.05  \n",
       "3                     4.48             0.05  \n",
       "4                     0.68             0.01  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use .info() to see lengths and dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 23180 entries, 0 to 23179\n",
      "Data columns (total 12 columns):\n",
      "date                       23180 non-null datetime64[ns]\n",
      "sku                        23180 non-null int64\n",
      "group                      23180 non-null object\n",
      "name                       23180 non-null object\n",
      "quantity                   23180 non-null float64\n",
      "unit_cogs                  23180 non-null object\n",
      "agg_cogs                   23180 non-null float64\n",
      "unit_revenue               23180 non-null float64\n",
      "gross_margin               23180 non-null float64\n",
      "unit_contribution          23180 non-null float64\n",
      "agg_dollar_contribution    23180 non-null float64\n",
      "share_of_margin            23180 non-null float64\n",
      "dtypes: datetime64[ns](1), float64(7), int64(1), object(3)\n",
      "memory usage: 2.1+ MB\n"
     ]
    }
   ],
   "source": [
    "monthly.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice unit_cogs are strings, lets convert it to float"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop empty rows\n",
    "idx_to_drop = monthly.unit_cogs[monthly.unit_cogs.str.len() == 0].index\n",
    "monthly = monthly.drop(idx_to_drop)\n",
    "\n",
    "# Convert to numeric\n",
    "monthly.unit_cogs =  monthly.unit_cogs.astype('float')\n",
    "\n",
    "# Add aggregate revenue column\n",
    "monthly['agg_rev'] = monthly['quantity'] * monthly['unit_revenue']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check N/A and duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date                       0\n",
       "sku                        0\n",
       "group                      0\n",
       "name                       0\n",
       "quantity                   0\n",
       "unit_cogs                  0\n",
       "agg_cogs                   0\n",
       "unit_revenue               0\n",
       "gross_margin               0\n",
       "unit_contribution          0\n",
       "agg_dollar_contribution    0\n",
       "share_of_margin            0\n",
       "agg_rev                    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Identify numerical and categorical variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['date', 'sku', 'group', 'name', 'quantity', 'unit_cogs', 'agg_cogs',\n",
       "       'unit_revenue', 'gross_margin', 'unit_contribution',\n",
       "       'agg_dollar_contribution', 'share_of_margin', 'agg_rev'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "categorical_cols = ['group']\n",
    "numeric_cols = list(monthly.columns)\n",
    "numeric_cols.remove('group')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summarize numerical and categorical variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>group</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>23179</td>\n",
       "      <td>23179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>36</td>\n",
       "      <td>5134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>sweets</td>\n",
       "      <td>surowka kubek</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>2298</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         group           name\n",
       "count    23179          23179\n",
       "unique      36           5134\n",
       "top     sweets  surowka kubek\n",
       "freq      2298             33"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly.describe(include = ['O'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>sku</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit_cogs</th>\n",
       "      <th>agg_cogs</th>\n",
       "      <th>unit_revenue</th>\n",
       "      <th>gross_margin</th>\n",
       "      <th>unit_contribution</th>\n",
       "      <th>agg_dollar_contribution</th>\n",
       "      <th>share_of_margin</th>\n",
       "      <th>agg_rev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "      <td>23179.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8324.591311</td>\n",
       "      <td>15.968032</td>\n",
       "      <td>3.541709</td>\n",
       "      <td>36.778366</td>\n",
       "      <td>4.652397</td>\n",
       "      <td>27.387402</td>\n",
       "      <td>1.110765</td>\n",
       "      <td>9.371015</td>\n",
       "      <td>0.054190</td>\n",
       "      <td>46.152207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5508.196842</td>\n",
       "      <td>82.681034</td>\n",
       "      <td>5.311516</td>\n",
       "      <td>132.472751</td>\n",
       "      <td>6.073310</td>\n",
       "      <td>12.780918</td>\n",
       "      <td>1.267469</td>\n",
       "      <td>25.659092</td>\n",
       "      <td>0.149611</td>\n",
       "      <td>151.355747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.030000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>-228.990000</td>\n",
       "      <td>-13.080000</td>\n",
       "      <td>-712.850000</td>\n",
       "      <td>-3.180000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3857.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.295000</td>\n",
       "      <td>4.040000</td>\n",
       "      <td>1.840000</td>\n",
       "      <td>23.310000</td>\n",
       "      <td>0.510000</td>\n",
       "      <td>1.540000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>5.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7928.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.180000</td>\n",
       "      <td>9.050000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>28.460000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>3.480000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>12.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>11418.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>3.700000</td>\n",
       "      <td>21.500000</td>\n",
       "      <td>4.870000</td>\n",
       "      <td>32.950000</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>8.120000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>29.880000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>19952.000000</td>\n",
       "      <td>2735.000000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>3397.470000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>99.910000</td>\n",
       "      <td>27.660000</td>\n",
       "      <td>710.940000</td>\n",
       "      <td>4.330000</td>\n",
       "      <td>3929.440000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                sku      quantity     unit_cogs      agg_cogs  unit_revenue  \\\n",
       "count  23179.000000  23179.000000  23179.000000  23179.000000  23179.000000   \n",
       "mean    8324.591311     15.968032      3.541709     36.778366      4.652397   \n",
       "std     5508.196842     82.681034      5.311516    132.472751      6.073310   \n",
       "min        2.000000      0.030000      0.010000      0.010000      0.100000   \n",
       "25%     3857.000000      2.000000      1.295000      4.040000      1.840000   \n",
       "50%     7928.000000      4.000000      2.180000      9.050000      3.060000   \n",
       "75%    11418.000000     11.000000      3.700000     21.500000      4.870000   \n",
       "max    19952.000000   2735.000000    500.000000   3397.470000    500.000000   \n",
       "\n",
       "       gross_margin  unit_contribution  agg_dollar_contribution  \\\n",
       "count  23179.000000       23179.000000             23179.000000   \n",
       "mean      27.387402           1.110765                 9.371015   \n",
       "std       12.780918           1.267469                25.659092   \n",
       "min     -228.990000         -13.080000              -712.850000   \n",
       "25%       23.310000           0.510000                 1.540000   \n",
       "50%       28.460000           0.800000                 3.480000   \n",
       "75%       32.950000           1.280000                 8.120000   \n",
       "max       99.910000          27.660000               710.940000   \n",
       "\n",
       "       share_of_margin       agg_rev  \n",
       "count     23179.000000  23179.000000  \n",
       "mean          0.054190     46.152207  \n",
       "std           0.149611    151.355747  \n",
       "min          -3.180000      0.100000  \n",
       "25%           0.010000      5.700000  \n",
       "50%           0.020000     12.850000  \n",
       "75%           0.050000     29.880000  \n",
       "max           4.330000   3929.440000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly.describe(include = [np.number])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing product categories and their dollar contribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Getting the full list of categories and the number of skus within each category\n",
    "category_sku_count = monthly[['sku','group']].drop_duplicates().groupby('group').count().sort_values(by='sku', ascending=False)\n",
    "category_annual_contribution = monthly[['group','agg_dollar_contribution']].drop_duplicates().groupby('group').sum().sort_values(by='agg_dollar_contribution', ascending=False)\n",
    "category_sku_annual_contrib = category_sku_count.join(category_annual_contribution)\n",
    "\n",
    "# calculating aggregate dollar revenue\n",
    "monthly['agg_revenue'] = monthly['quantity'] * monthly['unit_revenue']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = list(category_sku_annual_contrib.index)\n",
    "x = np.arange(len(labels))\n",
    "width = .35\n",
    "\n",
    "fig, ax1 = plt.subplots(figsize=(17,6))\n",
    "ax1.bar(x - width/2, category_sku_count.sku, width, color=['orange'])\n",
    "ax2 = ax1.twinx()\n",
    "ax2.bar(x+ width/2, category_annual_contribution.agg_dollar_contribution, width)\n",
    "\n",
    "ax1.legend(['SKU'])\n",
    "ax2.legend(['Contribution'],loc=2)\n",
    "\n",
    "ax1.set_ylabel('# of SKUs')\n",
    "ax2.set_ylabel('Aggregate Annual Contribution (PLN)')\n",
    "\n",
    "ax1.set_xticks(x)\n",
    "ax1.set_xticklabels(labels, minor=False, rotation=90);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Defining Some Helper Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_mom_growth(df):\n",
    "    \"\"\"Get the month over month growth rate for input data\"\"\"\n",
    "    \n",
    "    growth_df = df / df.shift(1, axis=1) - 1\n",
    "    return growth_df.iloc[:,1:]\n",
    "\n",
    "\n",
    "def top_n_cat_by_contrib_idx(n):\n",
    "    \"\"\"Returns sorted n largest product categories index (pd.Int64Index) by annual aggregate revenue\"\"\"\n",
    "    \n",
    "    return category_contribution_by_month.sum(axis=1).sort_values(ascending=False).iloc[:n].index\n",
    "\n",
    "\n",
    "def ma(df, n):\n",
    "    \"\"\"Returns a moving average dataframe based on given period\"\"\"\n",
    "    \n",
    "    return df.rolling(window=n, axis=1).mean().iloc[:,n-1:]\n",
    "\n",
    "\n",
    "def cat_by_month(value, aggfunc='sum'):\n",
    "    \"\"\"Returns df aggregated on value (fn parameter). Returned df has product categories as rows \n",
    "    and month of year as columns\"\"\"\n",
    "    \n",
    "    df = monthly.pivot_table(value, index='group', columns=['date'], aggfunc=aggfunc)\n",
    "    df = df.fillna(0)\n",
    "    df.columns = abr_month\n",
    "    return df\n",
    "\n",
    "\n",
    "# These functions have some dependent dataframes\n",
    "category_contribution_by_month = cat_by_month('agg_revenue') - cat_by_month('agg_cogs')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Understanding Fresh Produce Business Dynamics\n",
    "\n",
    "Motivation:\n",
    "- Estimate the financial value of keeping the fresh produce section\n",
    "\n",
    "Limitations & Assumptions:\n",
    "- Due to the limitations of the dataset; specifically, the lack of receipt level data, it is difficult to accurately estimate how much sales lift fresh produce crates.\n",
    "- Equally unfortunate, we don't have financial statements for the store, and therefore we can't know for sure if produce is a loss leader, but it most likely is due to industry competitive dynamics and the store profile.\n",
    "\n",
    "Result:\n",
    "- Not strongly correlated with any major categories\n",
    "- Maximum sales lift ~25% of total sales, ~ 15% is probably realistic since grocery is likely a loss leader and not all correlated sales are attributable to groceries.\n",
    "- Will build a new attribution model when receipt level data becomes available\n",
    "\n",
    "How:\n",
    "- The method we use will set a upper limit on Produce's sales lift, by counting anything that is positively correlated with fresh produce sales.\n",
    "\n",
    "\n",
    "### Visualizing Grocery Sales Correlation /w Other Categories\n",
    "\n",
    "We will only visualize the top 17 categories since they account more than ~90% of all sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x1296 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1, axs = plt.subplots(4, 4, figsize=(18,18), sharex=False)\n",
    "i=0\n",
    "\n",
    "monthly_items_sold_by_category = cat_by_month('sku','count').T\n",
    "monthly_items_sold_by_category = monthly_items_sold_by_category[list(top_n_cat_by_contrib_idx(17))]\n",
    "\n",
    "categories_ex_vegetables = list(monthly_items_sold_by_category.columns.values)\n",
    "categories_ex_vegetables.remove('vegetables')\n",
    "\n",
    "# Plotting the subplots\n",
    "for row in range(9):\n",
    "    for col in range(4):\n",
    "        try:\n",
    "            cat = categories_ex_vegetables[i]\n",
    "            i += 1\n",
    "\n",
    "            x = monthly_items_sold_by_category.vegetables.values\n",
    "            y = monthly_items_sold_by_category[cat].values\n",
    "            sns.regplot(x=x, y=y, ax=axs[row][col])\n",
    "            axs[row][col].title.set_text(cat)\n",
    "            \n",
    "            if col == 0:\n",
    "                axs[row][col].set_ylabel('# of Items Sold')\n",
    "                \n",
    "            if row == 3:\n",
    "                axs[row][col].set_xlabel('# of Grocery Items Sold')            \n",
    "        except IndexError:\n",
    "            # Done\n",
    "            break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Again with a heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12, 9))\n",
    "\n",
    "product_categories = list(monthly_items_sold_by_category.columns.values)\n",
    "sns.heatmap(monthly_items_sold_by_category[list(top_n_cat_by_contrib_idx(10))].corr(), \n",
    "            cmap=sns.color_palette(\"RdBu_r\",50)[::-1], \n",
    "            annot=True)\n",
    "\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Estimating Grocery Sales Lift\n",
    "The ceiling sales lift is calculaed by multiplying the r^2 between fresh produce and the other category by the total dollar contribution of the other category. That is, we will attribute all correlated sales as produce's sales lift. Realistically sales lift should be much lower than this ceiling figure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>group</th>\n",
       "      <th>vegetables</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>vegetables</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beer</th>\n",
       "      <td>0.726198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sweets</th>\n",
       "      <td>0.652850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drink_juice</th>\n",
       "      <td>0.650581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ice_creams_frozen</th>\n",
       "      <td>0.574229</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "group              vegetables\n",
       "group                        \n",
       "vegetables           1.000000\n",
       "beer                 0.726198\n",
       "sweets               0.652850\n",
       "drink_juice          0.650581\n",
       "ice_creams_frozen    0.574229"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Making the sales correlation matrix between groceries and other categories\n",
    "corr_df = pd.DataFrame(np.corrcoef(monthly_items_sold_by_category.values, rowvar=False), columns = monthly_items_sold_by_category.columns)\n",
    "corr_df.index = monthly_items_sold_by_category.columns\n",
    "corr_df = corr_df[['vegetables']].sort_values('vegetables', ascending=False)\n",
    "\n",
    "corr_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max estimated lift is 34.9% counting fresh produce sales, and 24.9% without.\n"
     ]
    }
   ],
   "source": [
    "# Aggregate dollar contribution by category\n",
    "contribution_by_category = monthly[['group','agg_dollar_contribution']].groupby(by='group').sum()\n",
    "contribution_by_category = contribution_by_category.sort_values(by='agg_dollar_contribution', ascending=False)\n",
    "contribution_by_category = contribution_by_category.join(corr_df)\n",
    "contribution_by_category = contribution_by_category.rename(columns={'vegetables':'corr_w_vegetables'})\n",
    "\n",
    "# Maximum estimated financial impact by counting everything correlated with grocery sales as sales lift\n",
    "contribution_by_category['max_est_fin_impact'] = contribution_by_category['agg_dollar_contribution'] * contribution_by_category['corr_w_vegetables']\n",
    "\n",
    "# Measuring the category's importance by calculating its share of total store's contribution pool\n",
    "contribution_by_category['cat_total_contrib_share'] =  contribution_by_category['agg_dollar_contribution'] / contribution_by_category['agg_dollar_contribution'].sum()\n",
    "\n",
    "# Contribution counted as sales lift as a percentage of total store's contribution\n",
    "contribution_by_category['lift_contrib_share'] =  contribution_by_category['max_est_fin_impact'] / contribution_by_category['agg_dollar_contribution'].sum()\n",
    "\n",
    "max_lift = contribution_by_category.loc[contribution_by_category['lift_contrib_share'] > 0, 'lift_contrib_share'].sum()\n",
    "\n",
    "print(\"Max estimated lift is {0:.1f}% counting fresh produce sales, and {1:.1f}% without.\".format(max_lift * 100, (max_lift - .1) * 100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "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>agg_dollar_contribution</th>\n",
       "      <th>corr_w_vegetables</th>\n",
       "      <th>max_est_fin_impact</th>\n",
       "      <th>cat_total_contrib_share</th>\n",
       "      <th>lift_contrib_share</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>vegetables</th>\n",
       "      <td>22401.82</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>22401.820000</td>\n",
       "      <td>0.103134</td>\n",
       "      <td>0.103134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beer</th>\n",
       "      <td>22460.91</td>\n",
       "      <td>0.726198</td>\n",
       "      <td>16311.074200</td>\n",
       "      <td>0.103406</td>\n",
       "      <td>0.075093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drink_juice</th>\n",
       "      <td>17633.21</td>\n",
       "      <td>0.650581</td>\n",
       "      <td>11471.839433</td>\n",
       "      <td>0.081180</td>\n",
       "      <td>0.052814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sweets</th>\n",
       "      <td>14134.36</td>\n",
       "      <td>0.652850</td>\n",
       "      <td>9227.616352</td>\n",
       "      <td>0.065072</td>\n",
       "      <td>0.042482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ice_creams_frozen</th>\n",
       "      <td>11277.78</td>\n",
       "      <td>0.574229</td>\n",
       "      <td>6476.029963</td>\n",
       "      <td>0.051921</td>\n",
       "      <td>0.029814</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   agg_dollar_contribution  corr_w_vegetables  \\\n",
       "group                                                           \n",
       "vegetables                        22401.82           1.000000   \n",
       "beer                              22460.91           0.726198   \n",
       "drink_juice                       17633.21           0.650581   \n",
       "sweets                            14134.36           0.652850   \n",
       "ice_creams_frozen                 11277.78           0.574229   \n",
       "\n",
       "                   max_est_fin_impact  cat_total_contrib_share  \\\n",
       "group                                                            \n",
       "vegetables               22401.820000                 0.103134   \n",
       "beer                     16311.074200                 0.103406   \n",
       "drink_juice              11471.839433                 0.081180   \n",
       "sweets                    9227.616352                 0.065072   \n",
       "ice_creams_frozen         6476.029963                 0.051921   \n",
       "\n",
       "                   lift_contrib_share  \n",
       "group                                  \n",
       "vegetables                   0.103134  \n",
       "beer                         0.075093  \n",
       "drink_juice                  0.052814  \n",
       "sweets                       0.042482  \n",
       "ice_creams_frozen            0.029814  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Looking at the dataframe containing sales lift data\n",
    "contribution_by_category.sort_values('max_est_fin_impact', ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sales Trends, Best Performing Categories & SKUs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SKUs sold Vs. Revenue\n",
    "\n",
    "Results:\n",
    "- Total revenue highly correlated with number of items sold, with the exception of December. Consumers were trading up during December and not other time of year. This could be due to the Christmas Holidays."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grabbing data for skus sold and revenue per month\n",
    "monthly_aggregate_skus_sold = cat_by_month('quantity').sum(axis=0)\n",
    "monthly_aggregate_revenue = cat_by_month('agg_revenue').sum(axis=0)\n",
    "monthly_aggregate_revenue.index = monthly_aggregate_skus_sold.index\n",
    "\n",
    "# plotting side by side\n",
    "rev_sku_fig = plt.figure(figsize=(12,6))\n",
    "ax1 = rev_sku_fig.add_subplot(111)\n",
    "ax1.plot(monthly_aggregate_skus_sold)\n",
    "ax1.set_ylabel('# of Items Sold')\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(monthly_aggregate_revenue, 'r-')\n",
    "ax2.set_ylabel('Monthly Revenue (PLN)')\n",
    "\n",
    "ax1.set_title(\"# of Items Sold and Monthly Revenue\")\n",
    "\n",
    "ax1.legend(['Items Sold'])\n",
    "ax2.legend(['Monthly Rev'],loc=2)\n",
    "\n",
    "for tl in ax2.get_yticklabels():\n",
    "    tl.set_color('r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finding Under-Performing Categories\n",
    "\n",
    "### How many SKUs can we drop and still keep 90% of our revenue? How much cash can we raise by selling stock?\n",
    "\n",
    "Result:\n",
    "- We can drop 60% of our total SKUs and still keep 90% of our total revenue\n",
    "- Generate $14,000 PLN via stock liqudiation\n",
    "- Cash and freed up space can be used to upgrade/renovate store\n",
    "\n",
    "\n",
    "- **Biggest non-performing categories are**\n",
    "    - Household chemicals (chemistry)\n",
    "    - General\n",
    "    - Wine\n",
    "    - Sweets\n",
    "    - Bulk cookies\n",
    "  \n",
    "  \n",
    "- ** Categories that has expansion potential **\n",
    "    - Bread\n",
    "    - Vodka / Spirits\n",
    "    - Beer\n",
    "    - Cigarettes\n",
    "\n",
    "Implication:\n",
    "- Lots of excess shelf space in the store, which gives us the opportunity to dramatically adjust the store layout, product display, and to introduce new product categories etc...\n",
    "\n",
    "Assumptions:\n",
    "- 35% discount on retail when liquidating stock\n",
    "- 5 items in stock per SKU"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Making a Product Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "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>group</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sku</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5307</th>\n",
       "      <td>chemistry</td>\n",
       "      <td>patyczki bella 200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5986</th>\n",
       "      <td>chemistry</td>\n",
       "      <td>ace 1 l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>dairy_chesse</td>\n",
       "      <td>almette czosnek niedzwiedzi 150gr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2246</th>\n",
       "      <td>dairy_chesse</td>\n",
       "      <td>almette jogurtowy 150g hochland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2247</th>\n",
       "      <td>dairy_chesse</td>\n",
       "      <td>almette ogorek/ziola 150g</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             group                               name\n",
       "sku                                                  \n",
       "5307     chemistry                 patyczki bella 200\n",
       "5986     chemistry                            ace 1 l\n",
       "399   dairy_chesse  almette czosnek niedzwiedzi 150gr\n",
       "2246  dairy_chesse    almette jogurtowy 150g hochland\n",
       "2247  dairy_chesse          almette ogorek/ziola 150g"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Products, a df conaining SKU, product group and product name\n",
    "products = monthly[['group','sku','name']].drop_duplicates().set_index('sku')\n",
    "products.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cumulative Revenue by nth Top Performing SKUs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "monthly_sku_revenue = monthly[['date','sku','agg_revenue']].pivot_table('agg_revenue', index='sku', columns='date')\n",
    "monthly_sku_revenue = monthly_sku_revenue.fillna(0)\n",
    "monthly_sku_revenue.columns = abr_month\n",
    "monthly_sku_revenue['annual_total'] = monthly_sku_revenue.sum(axis=1)\n",
    "monthly_sku_revenue = monthly_sku_revenue.sort_values('annual_total', ascending=False)\n",
    "\n",
    "# Calculating each SKU's share of overall revenue\n",
    "product_performance = monthly_sku_revenue.join(products)\n",
    "product_performance['rev_share'] = product_performance['annual_total'] / product_performance['annual_total'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 5277 SKUs sold by the store within the last yr, but many also has not made a sale in months\n"
     ]
    }
   ],
   "source": [
    "# Sort by most performent SKU based on annual contribution and calculating cumulative revenue\n",
    "product_performance['cumulative_rev'] = product_performance['rev_share']\n",
    "\n",
    "cumulative_revenue_share = 0.0\n",
    "for idx, row in product_performance.iterrows():\n",
    "    product_performance.loc[idx,'cumulative_rev'] = cumulative_revenue_share + row['rev_share']\n",
    "    cumulative_revenue_share += row['rev_share']\n",
    "    \n",
    "# Making a pricing table to hold product pricing information\n",
    "pricing = monthly[['sku','unit_cogs','unit_revenue']]\n",
    "# In case there are multiple prices for a single SKU, we'll take the mean\n",
    "pricing = pricing.groupby('sku').mean()\n",
    "\n",
    "# Joining dfs together\n",
    "product_performance = product_performance.join(pricing)\n",
    "print(f'there are {product_performance.shape[0]} SKUs sold by the store within the last yr, \\\n",
    "but many also has not made a sale in months')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "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>jan</th>\n",
       "      <th>feb</th>\n",
       "      <th>mar</th>\n",
       "      <th>apr</th>\n",
       "      <th>may</th>\n",
       "      <th>jun</th>\n",
       "      <th>jul</th>\n",
       "      <th>aug</th>\n",
       "      <th>sep</th>\n",
       "      <th>oct</th>\n",
       "      <th>nov</th>\n",
       "      <th>dec</th>\n",
       "      <th>annual_total</th>\n",
       "      <th>group</th>\n",
       "      <th>name</th>\n",
       "      <th>rev_share</th>\n",
       "      <th>cumulative_rev</th>\n",
       "      <th>unit_cogs</th>\n",
       "      <th>unit_revenue</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sku</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>1955.20</td>\n",
       "      <td>2088.1700</td>\n",
       "      <td>3087.980</td>\n",
       "      <td>3372.84</td>\n",
       "      <td>3898.96</td>\n",
       "      <td>3760.41</td>\n",
       "      <td>3867.99</td>\n",
       "      <td>3929.4400</td>\n",
       "      <td>3127.91</td>\n",
       "      <td>1805.27</td>\n",
       "      <td>2127.580</td>\n",
       "      <td>1681.690</td>\n",
       "      <td>34703.4400</td>\n",
       "      <td>beer</td>\n",
       "      <td>piwo zubr 0_5l butelka</td>\n",
       "      <td>0.032440</td>\n",
       "      <td>0.032440</td>\n",
       "      <td>1.3800</td>\n",
       "      <td>1.637500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>2625.48</td>\n",
       "      <td>2384.2800</td>\n",
       "      <td>2737.260</td>\n",
       "      <td>2081.82</td>\n",
       "      <td>2872.80</td>\n",
       "      <td>2537.04</td>\n",
       "      <td>3177.20</td>\n",
       "      <td>3458.9100</td>\n",
       "      <td>3339.84</td>\n",
       "      <td>3167.80</td>\n",
       "      <td>2988.120</td>\n",
       "      <td>2974.790</td>\n",
       "      <td>34345.3400</td>\n",
       "      <td>dairy_chesse</td>\n",
       "      <td>gos.maslo 250g gostyn</td>\n",
       "      <td>0.032106</td>\n",
       "      <td>0.064546</td>\n",
       "      <td>6.3750</td>\n",
       "      <td>6.645000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8934</th>\n",
       "      <td>1524.39</td>\n",
       "      <td>1559.7600</td>\n",
       "      <td>1737.310</td>\n",
       "      <td>1684.38</td>\n",
       "      <td>1742.00</td>\n",
       "      <td>1749.37</td>\n",
       "      <td>1810.34</td>\n",
       "      <td>1832.4500</td>\n",
       "      <td>1933.33</td>\n",
       "      <td>1866.59</td>\n",
       "      <td>1886.470</td>\n",
       "      <td>1915.580</td>\n",
       "      <td>21241.9700</td>\n",
       "      <td>bread</td>\n",
       "      <td>bulka mala/kajzerka__</td>\n",
       "      <td>0.019857</td>\n",
       "      <td>0.084403</td>\n",
       "      <td>0.5325</td>\n",
       "      <td>0.678333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14233</th>\n",
       "      <td>2079.77</td>\n",
       "      <td>1221.0000</td>\n",
       "      <td>1994.300</td>\n",
       "      <td>1664.63</td>\n",
       "      <td>1461.13</td>\n",
       "      <td>1359.38</td>\n",
       "      <td>1615.79</td>\n",
       "      <td>1575.0900</td>\n",
       "      <td>1815.22</td>\n",
       "      <td>1302.40</td>\n",
       "      <td>879.120</td>\n",
       "      <td>647.130</td>\n",
       "      <td>17614.9600</td>\n",
       "      <td>phones_adjustments</td>\n",
       "      <td>pompka simplus 5 zl</td>\n",
       "      <td>0.016466</td>\n",
       "      <td>0.100869</td>\n",
       "      <td>3.8275</td>\n",
       "      <td>4.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1179.57</td>\n",
       "      <td>1180.2462</td>\n",
       "      <td>1474.095</td>\n",
       "      <td>1333.20</td>\n",
       "      <td>1380.16</td>\n",
       "      <td>1418.04</td>\n",
       "      <td>1532.16</td>\n",
       "      <td>1476.2305</td>\n",
       "      <td>1602.12</td>\n",
       "      <td>1525.68</td>\n",
       "      <td>1344.335</td>\n",
       "      <td>1310.531</td>\n",
       "      <td>16756.3677</td>\n",
       "      <td>bread</td>\n",
       "      <td>c chleb krojony 0_6 kg</td>\n",
       "      <td>0.015664</td>\n",
       "      <td>0.116533</td>\n",
       "      <td>2.6000</td>\n",
       "      <td>3.050833</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           jan        feb       mar      apr      may      jun      jul  \\\n",
       "sku                                                                       \n",
       "304    1955.20  2088.1700  3087.980  3372.84  3898.96  3760.41  3867.99   \n",
       "374    2625.48  2384.2800  2737.260  2081.82  2872.80  2537.04  3177.20   \n",
       "8934   1524.39  1559.7600  1737.310  1684.38  1742.00  1749.37  1810.34   \n",
       "14233  2079.77  1221.0000  1994.300  1664.63  1461.13  1359.38  1615.79   \n",
       "3      1179.57  1180.2462  1474.095  1333.20  1380.16  1418.04  1532.16   \n",
       "\n",
       "             aug      sep      oct       nov       dec  annual_total  \\\n",
       "sku                                                                    \n",
       "304    3929.4400  3127.91  1805.27  2127.580  1681.690    34703.4400   \n",
       "374    3458.9100  3339.84  3167.80  2988.120  2974.790    34345.3400   \n",
       "8934   1832.4500  1933.33  1866.59  1886.470  1915.580    21241.9700   \n",
       "14233  1575.0900  1815.22  1302.40   879.120   647.130    17614.9600   \n",
       "3      1476.2305  1602.12  1525.68  1344.335  1310.531    16756.3677   \n",
       "\n",
       "                    group                    name  rev_share  cumulative_rev  \\\n",
       "sku                                                                            \n",
       "304                  beer  piwo zubr 0_5l butelka   0.032440        0.032440   \n",
       "374          dairy_chesse   gos.maslo 250g gostyn   0.032106        0.064546   \n",
       "8934                bread   bulka mala/kajzerka__   0.019857        0.084403   \n",
       "14233  phones_adjustments     pompka simplus 5 zl   0.016466        0.100869   \n",
       "3                   bread  c chleb krojony 0_6 kg   0.015664        0.116533   \n",
       "\n",
       "       unit_cogs  unit_revenue  \n",
       "sku                             \n",
       "304       1.3800      1.637500  \n",
       "374       6.3750      6.645000  \n",
       "8934      0.5325      0.678333  \n",
       "14233     3.8275      4.070000  \n",
       "3         2.6000      3.050833  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "product_performance.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting Cumulative Revenue\n",
    "cumulative_revenue = pd.DataFrame(product_performance['cumulative_rev'].values)\n",
    "\n",
    "plt.figure(figsize=(9,5))\n",
    "plt.plot(cumulative_revenue.values)\n",
    "plt.title('Cumulative Revenue by nth Top SKUs')\n",
    "plt.xlabel(\"n'th SKUs\")\n",
    "plt.ylabel(\"Cumulative Revenue as % of Total\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Dropping Underperforming SKUs & Assess Financial Impact\n",
    "#### 90% of Store's Revenue is made by ~ 40% of SKUs, 50% by ~10% of SKUs\n",
    "- There are about 4k active SKUs\n",
    "- This means we can strip many underperforming products and do something else with the space we have. We will also be able to raise some capital through the sale of inventory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def get_sku_status(df, n_months, active=True):\n",
    "    \"\"\"Returns the index of active or inactive SKUs. A inactive SKU is one that has not made a\n",
    "    sale in the last n_months.\n",
    "    \n",
    "    Args:\n",
    "        df: df\n",
    "            product dataframe containing product sku, cumulative revenue, unit cogs, and unit revenue\n",
    "        \n",
    "        n_months: int\n",
    "            A SKU that has not made a sale in n_months will be marked as inactive\n",
    "            \n",
    "        active: bool\n",
    "            Returns active SKU indexes when set to True, returns inactive SKU indexes when False\n",
    "            \n",
    "    \n",
    "    Returns:\n",
    "        idx: pd.Int64Index\n",
    "            Pandas Row Index of active or inactive SKUs\n",
    "    \"\"\"\n",
    "    start_month = abr_month[-n_months]\n",
    "    df['rev_last_n_months'] = df.loc[:, start_month:\"dec\"].sum(axis=1)\n",
    "    \n",
    "    if active:\n",
    "        return df[df['rev_last_n_months'] > 0].index\n",
    "    \n",
    "    else:\n",
    "        return df[df['rev_last_n_months'] <= 0].index\n",
    "    \n",
    "\n",
    "\n",
    "def working_capital_used_by_underperfoming_products(df, rev_to_keep, liquidation_discount, inventory_per_sku):\n",
    "    \"\"\"Calculate the amount of working capital used by non-performent SKUs, and the amount of capital\n",
    "    that can be released from liduidating these non-performent SKUs. You can specify the amount of\n",
    "    revenues you wish to retain. (IE, find the long tail SKUs that constitues the latst 10% of revenue)\n",
    "    \n",
    "    Args:\n",
    "        df: df\n",
    "            product dataframe containing product sku, culative revenue, unit cogs, and unit revenue\n",
    "            \n",
    "        rev_to_keep: float \n",
    "            Amount of revenue to *keep*, ranges from 0 to 1, 1 being keeping all revenue and not \n",
    "            dropping any skus. Similarily, 0 being keeping no revenue and dropping all SKUs\n",
    "        \n",
    "        liquidation_discount: float\n",
    "            A discount (0 to 1) applied to retail price to clear inventory. It is used to calcualte\n",
    "            amount of capital that can be freed up via inventory liquidation\n",
    "    \n",
    "    Returns:\n",
    "        working_cap_invested: float\n",
    "            Amount of working capital invested in non-performent SKUs\n",
    "        \n",
    "        working_cap_freed: float\n",
    "            Amount of working capital to be freed by liquidating stock at liquidation discount\n",
    "            \n",
    "        num_skus_dropped: int\n",
    "            Number of SKUs dropped\n",
    "            \n",
    "        idx_skus_dropped: df.Int64Index\n",
    "            dataframe index of SKUs that will be dropped\n",
    "            \n",
    "    \"\"\"    \n",
    "    # Get a list of active SKUs (SKU that made sales in last 3 months)\n",
    "    active_skus_idx = get_sku_status(df, 3, active=True)\n",
    "    df = df.loc[active_skus_idx,:].copy()\n",
    "    \n",
    "    active_skus = df.shape[0]\n",
    "    \n",
    "    # Calculating working capital and liquidation value\n",
    "    df['working_cap'] = df['unit_cogs'] * inventory_per_sku\n",
    "    df['liquidation_cf'] = df['unit_revenue'] * liquidation_discount * inventory_per_sku\n",
    "    \n",
    "    # return totals for given revene share to keep\n",
    "    df_to_liquidate = df[df['cumulative_rev'] >= rev_to_keep]\n",
    "    total_wc = df_to_liquidate['working_cap'].sum()\n",
    "    total_liquidation_cf = df_to_liquidate['liquidation_cf'].sum()\n",
    "    \n",
    "    num_skus_dropped = df_to_liquidate.shape[0]\n",
    "    num_skus_dropped_frac = num_skus_dropped / active_skus * 100\n",
    "    \n",
    "    idx_skus_dropped = df_to_liquidate.index\n",
    "    \n",
    "    print(\"Total working capital invested in SKUs to be liquidated is ${0:.0f} PLN\".format(total_wc))\n",
    "    print(\"Total amount of cash generated from liquidating underperforming SKUs is ${0:.0f} PLN\".format(total_liquidation_cf))\n",
    "    print(\"Total number of active SKUs to be dropped from store is {0:.0f}, representing {1:.0f}% of your SKUs\".format(num_skus_dropped, num_skus_dropped_frac))\n",
    "    \n",
    "    return total_wc, total_liquidation_cf, num_skus_dropped, idx_skus_dropped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total working capital invested in SKUs to be liquidated is $29350 PLN\n",
      "Total amount of cash generated from liquidating underperforming SKUs is $14014 PLN\n",
      "Total number of active SKUs to be dropped from store is 1736, representing 60% of your SKUs\n"
     ]
    }
   ],
   "source": [
    "_, _, _, idx_skus_dropped = working_capital_used_by_underperfoming_products(product_performance, .9, 0.35, 5);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def explore_dropped_sku_categories(product_performance, idx_skus_dropped, n_months):\n",
    "    \"\"\"\n",
    "    Calculates number of SKUs to be dropped in each product category and compare it to the total\n",
    "    number of SKUs in that produce category\n",
    "    \n",
    "    Args:\n",
    "        product_performance: df\n",
    "            product dataframe containing product sku, culative revenue, unit cogs, and unit revenue\n",
    "            \n",
    "        idx_skus_dropped: pd.Int64Index\n",
    "            index conaining skus to be dropped\n",
    "            \n",
    "        n_months: int\n",
    "            Threshold in months used in marking a item as inactive. Every SKU that has made \n",
    "            a sale in the last n_months are considered active, and as such, is assumed to be\n",
    "            currently in inventory. Active SKUs are counted towards category SKU total. Inactive\n",
    "            SKUs are not.\n",
    "            \n",
    "    \"\"\"\n",
    "    skus_dropped = product_performance.loc[idx_skus_dropped,:].groupby('group').count()\n",
    "    skus_dropped = pd.DataFrame(skus_dropped.name.sort_values(ascending=False))\n",
    "    skus_dropped.columns = ['skus_dropped']\n",
    "    \n",
    "    active_skus_idx = get_sku_status(product_performance, 3, active=True)\n",
    "    active_skus = product_performance.loc[active_skus_idx,:]\n",
    "\n",
    "    # Count the categories\n",
    "    active_skus_per_category = active_skus.groupby('group').count()\n",
    "    active_skus_per_category = pd.DataFrame(active_skus_per_category.name)\n",
    "    active_skus_per_category.columns = ['cat_total']\n",
    "\n",
    "    # Join the dfs and normalize\n",
    "    df = skus_dropped.join(active_skus_per_category)\n",
    "    df['frac_dropped'] = df.skus_dropped / df.cat_total\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "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>skus_dropped</th>\n",
       "      <th>cat_total</th>\n",
       "      <th>frac_dropped</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>article_of_household</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>socks_thights</th>\n",
       "      <td>21</td>\n",
       "      <td>24</td>\n",
       "      <td>0.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>general</th>\n",
       "      <td>124</td>\n",
       "      <td>142</td>\n",
       "      <td>0.873239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chemistry</th>\n",
       "      <td>312</td>\n",
       "      <td>362</td>\n",
       "      <td>0.861878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>art._hygienic</th>\n",
       "      <td>15</td>\n",
       "      <td>18</td>\n",
       "      <td>0.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spices</th>\n",
       "      <td>75</td>\n",
       "      <td>92</td>\n",
       "      <td>0.815217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wine_alcohol 18%</th>\n",
       "      <td>40</td>\n",
       "      <td>51</td>\n",
       "      <td>0.784314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>occasional</th>\n",
       "      <td>22</td>\n",
       "      <td>29</td>\n",
       "      <td>0.758621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fish</th>\n",
       "      <td>47</td>\n",
       "      <td>63</td>\n",
       "      <td>0.746032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cookies_bulk</th>\n",
       "      <td>30</td>\n",
       "      <td>41</td>\n",
       "      <td>0.731707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>canned_pate</th>\n",
       "      <td>35</td>\n",
       "      <td>49</td>\n",
       "      <td>0.714286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>coffee tea</th>\n",
       "      <td>45</td>\n",
       "      <td>65</td>\n",
       "      <td>0.692308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pet's food</th>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lunch dining dishes</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sweets</th>\n",
       "      <td>209</td>\n",
       "      <td>317</td>\n",
       "      <td>0.659306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>general_food</th>\n",
       "      <td>154</td>\n",
       "      <td>238</td>\n",
       "      <td>0.647059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>groats_rice_pasta</th>\n",
       "      <td>53</td>\n",
       "      <td>82</td>\n",
       "      <td>0.646341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sauce</th>\n",
       "      <td>66</td>\n",
       "      <td>114</td>\n",
       "      <td>0.578947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tablets</th>\n",
       "      <td>17</td>\n",
       "      <td>32</td>\n",
       "      <td>0.531250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chewing_gum_lolipops</th>\n",
       "      <td>17</td>\n",
       "      <td>32</td>\n",
       "      <td>0.531250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dairy_chesse</th>\n",
       "      <td>140</td>\n",
       "      <td>269</td>\n",
       "      <td>0.520446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>packages</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drink_juice</th>\n",
       "      <td>103</td>\n",
       "      <td>225</td>\n",
       "      <td>0.457778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vegetables</th>\n",
       "      <td>48</td>\n",
       "      <td>108</td>\n",
       "      <td>0.444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ice_creams_frozen</th>\n",
       "      <td>46</td>\n",
       "      <td>106</td>\n",
       "      <td>0.433962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chips_flakes</th>\n",
       "      <td>19</td>\n",
       "      <td>47</td>\n",
       "      <td>0.404255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oils</th>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>0.388889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>meat</th>\n",
       "      <td>15</td>\n",
       "      <td>45</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vodka_alcohol</th>\n",
       "      <td>23</td>\n",
       "      <td>77</td>\n",
       "      <td>0.298701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beer</th>\n",
       "      <td>26</td>\n",
       "      <td>95</td>\n",
       "      <td>0.273684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dishes_for_children</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cigarettes</th>\n",
       "      <td>11</td>\n",
       "      <td>79</td>\n",
       "      <td>0.139241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bread</th>\n",
       "      <td>3</td>\n",
       "      <td>41</td>\n",
       "      <td>0.073171</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      skus_dropped  cat_total  frac_dropped\n",
       "group                                                      \n",
       "article_of_household             3          3      1.000000\n",
       "socks_thights                   21         24      0.875000\n",
       "general                        124        142      0.873239\n",
       "chemistry                      312        362      0.861878\n",
       "art._hygienic                   15         18      0.833333\n",
       "spices                          75         92      0.815217\n",
       "wine_alcohol 18%                40         51      0.784314\n",
       "occasional                      22         29      0.758621\n",
       "fish                            47         63      0.746032\n",
       "cookies_bulk                    30         41      0.731707\n",
       "canned_pate                     35         49      0.714286\n",
       "coffee tea                      45         65      0.692308\n",
       "pet's food                       6          9      0.666667\n",
       "lunch dining dishes              2          3      0.666667\n",
       "sweets                         209        317      0.659306\n",
       "general_food                   154        238      0.647059\n",
       "groats_rice_pasta               53         82      0.646341\n",
       "sauce                           66        114      0.578947\n",
       "tablets                         17         32      0.531250\n",
       "chewing_gum_lolipops            17         32      0.531250\n",
       "dairy_chesse                   140        269      0.520446\n",
       "packages                         1          2      0.500000\n",
       "drink_juice                    103        225      0.457778\n",
       "vegetables                      48        108      0.444444\n",
       "ice_creams_frozen               46        106      0.433962\n",
       "chips_flakes                    19         47      0.404255\n",
       "oils                             7         18      0.388889\n",
       "meat                            15         45      0.333333\n",
       "vodka_alcohol                   23         77      0.298701\n",
       "beer                            26         95      0.273684\n",
       "dishes_for_children              1          4      0.250000\n",
       "cigarettes                      11         79      0.139241\n",
       "bread                            3         41      0.073171"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "explore_dropped_sku_categories(product_performance, idx_skus_dropped, 3).sort_values('frac_dropped', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Understanding Sales Trend\n",
    "\n",
    "Goal:\n",
    "- Understand the reasons behind the current sales trend\n",
    "- Figure out which categories are well positioned for growth, and which look the least favorable\n",
    "\n",
    "Implication\n",
    "- In the winter months you can exploit the fact that people don't want to hop into the car and go to the large supermarkets, and increase price on staple categories such as fresh produce, cheese, and bread.\n",
    "- Generally speaking you should increase the margins on produce, the data suggests it has low price elasticity.\n",
    "- Consider expanding drink and beer selection during the summer months, and perhaps run more promotions during winter months to counter cyclicality\n",
    "\n",
    "How:\n",
    "- By examing the changes in the following statistics for each product category. We'll use median for all statistics because this dataset has many outliers\n",
    "    - Median selling price (are customers switching to lower end products?)\n",
    "    - median contribution margin (absorbing the cost increase? Change in pricing power?)\n",
    "    - Total volume (Are people trading up/down or not buying at all?)\n",
    "    \n",
    "    \n",
    "Results:\n",
    "#### First look at store level performance\n",
    "\n",
    "- There is significant margin expansion in the second half of the year, thanks to\n",
    "    - Fresh produce\n",
    "    - Cheese\n",
    "    \n",
    "    \n",
    "- Margin has been weighted down by\n",
    "    - Bread\n",
    "\n",
    "#### Category Specific Trends\n",
    "**Revenue Trends**\n",
    "- **Fresh produce has relative low price elasticity** so the data suggest you do have some pricing power here, likely due to the store's convinence factor. You can explore upping your margins while closely monitoring sales volume.\n",
    "- All categories are cyclical\n",
    "- Drop in revenue towards the second half of the year was largely due to slowing sales of drink_juice and beer.\n",
    "- This dataset exhibits strong cyclicality trends in your significant categories. Beer ad drink_juice's seasonality trends are dragging down store's revenue generation in colder months.\n",
    "\n",
    "**Product Rotation**\n",
    "- It is difficult to advise on product rotation when all the categories exhibit the same seasonality trends, that is, universaly lower sales during winter months. As such, it is critical that the new market positioning incorporates products that sells well during winter months. Alternatively, you can have a strong and differentiated positioning selling a consumer staple that shows strong demand throughout the year.\n",
    "\n",
    "**Seasonal Product Categories**\n",
    "\n",
    "sorted most seasonal to lease\n",
    "- Drinks and Juice\n",
    "- Beer\n",
    "- Sweets\n",
    "- Cigarettes\n",
    "- Diary and Cheese\n",
    "- Fresh produce\n",
    "- Vodka & Spirit\n",
    "- Bread\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "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>quantity</th>\n",
       "      <th>agg_rev</th>\n",
       "      <th>agg_dollar_contribution</th>\n",
       "      <th>gross_margin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>25932.62</td>\n",
       "      <td>76619.8083</td>\n",
       "      <td>13573.27</td>\n",
       "      <td>0.177151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-01</th>\n",
       "      <td>24259.68</td>\n",
       "      <td>70786.7168</td>\n",
       "      <td>13631.43</td>\n",
       "      <td>0.192570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01</th>\n",
       "      <td>30612.37</td>\n",
       "      <td>87977.7103</td>\n",
       "      <td>17478.31</td>\n",
       "      <td>0.198667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-01</th>\n",
       "      <td>28329.33</td>\n",
       "      <td>81604.0676</td>\n",
       "      <td>16242.70</td>\n",
       "      <td>0.199043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-01</th>\n",
       "      <td>32561.19</td>\n",
       "      <td>97341.7113</td>\n",
       "      <td>20251.11</td>\n",
       "      <td>0.208041</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            quantity     agg_rev  agg_dollar_contribution  gross_margin\n",
       "date                                                                   \n",
       "2018-01-01  25932.62  76619.8083                 13573.27      0.177151\n",
       "2018-02-01  24259.68  70786.7168                 13631.43      0.192570\n",
       "2018-03-01  30612.37  87977.7103                 17478.31      0.198667\n",
       "2018-04-01  28329.33  81604.0676                 16242.70      0.199043\n",
       "2018-05-01  32561.19  97341.7113                 20251.11      0.208041"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "store_by_month = monthly[['date','quantity','agg_rev', 'agg_dollar_contribution']].groupby('date').sum()\n",
    "store_by_month['gross_margin'] = store_by_month['agg_dollar_contribution'] / store_by_month['agg_rev']\n",
    "store_by_month.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "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": [
    "# Loser look at margins\n",
    "store_by_month['gross_margin'].plot()\n",
    "plt.ylabel('Margin')\n",
    "plt.title(\"Store Wide Margin by Month\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Margin Analysis by Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": false
   },
   "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>jan</th>\n",
       "      <th>feb</th>\n",
       "      <th>mar</th>\n",
       "      <th>apr</th>\n",
       "      <th>may</th>\n",
       "      <th>jun</th>\n",
       "      <th>jul</th>\n",
       "      <th>aug</th>\n",
       "      <th>sep</th>\n",
       "      <th>oct</th>\n",
       "      <th>nov</th>\n",
       "      <th>dec</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>art._hygienic</th>\n",
       "      <td>0.341443</td>\n",
       "      <td>0.343337</td>\n",
       "      <td>0.341121</td>\n",
       "      <td>0.327369</td>\n",
       "      <td>0.321437</td>\n",
       "      <td>0.303039</td>\n",
       "      <td>0.354008</td>\n",
       "      <td>0.346140</td>\n",
       "      <td>0.330587</td>\n",
       "      <td>0.329996</td>\n",
       "      <td>0.289881</td>\n",
       "      <td>0.294395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>article_of_household</th>\n",
       "      <td>0.327703</td>\n",
       "      <td>0.335938</td>\n",
       "      <td>0.320499</td>\n",
       "      <td>0.365095</td>\n",
       "      <td>0.338048</td>\n",
       "      <td>0.322581</td>\n",
       "      <td>0.351254</td>\n",
       "      <td>0.301887</td>\n",
       "      <td>0.306569</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.317125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beer</th>\n",
       "      <td>0.228322</td>\n",
       "      <td>0.225629</td>\n",
       "      <td>0.216091</td>\n",
       "      <td>0.228100</td>\n",
       "      <td>0.215018</td>\n",
       "      <td>0.208671</td>\n",
       "      <td>0.208062</td>\n",
       "      <td>0.238731</td>\n",
       "      <td>0.224334</td>\n",
       "      <td>0.224656</td>\n",
       "      <td>0.212278</td>\n",
       "      <td>0.220428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bread</th>\n",
       "      <td>0.146066</td>\n",
       "      <td>0.185999</td>\n",
       "      <td>0.210260</td>\n",
       "      <td>0.208756</td>\n",
       "      <td>0.223266</td>\n",
       "      <td>0.218959</td>\n",
       "      <td>0.180553</td>\n",
       "      <td>0.182606</td>\n",
       "      <td>0.200194</td>\n",
       "      <td>0.178734</td>\n",
       "      <td>0.168410</td>\n",
       "      <td>0.178313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>canned_pate</th>\n",
       "      <td>0.265463</td>\n",
       "      <td>0.259811</td>\n",
       "      <td>0.252850</td>\n",
       "      <td>0.279858</td>\n",
       "      <td>0.289549</td>\n",
       "      <td>0.277049</td>\n",
       "      <td>0.279122</td>\n",
       "      <td>0.266056</td>\n",
       "      <td>0.268516</td>\n",
       "      <td>0.265583</td>\n",
       "      <td>0.269575</td>\n",
       "      <td>0.244895</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           jan       feb       mar       apr       may  \\\n",
       "group                                                                    \n",
       "art._hygienic         0.341443  0.343337  0.341121  0.327369  0.321437   \n",
       "article_of_household  0.327703  0.335938  0.320499  0.365095  0.338048   \n",
       "beer                  0.228322  0.225629  0.216091  0.228100  0.215018   \n",
       "bread                 0.146066  0.185999  0.210260  0.208756  0.223266   \n",
       "canned_pate           0.265463  0.259811  0.252850  0.279858  0.289549   \n",
       "\n",
       "                           jun       jul       aug       sep       oct  \\\n",
       "group                                                                    \n",
       "art._hygienic         0.303039  0.354008  0.346140  0.330587  0.329996   \n",
       "article_of_household  0.322581  0.351254  0.301887  0.306569       NaN   \n",
       "beer                  0.208671  0.208062  0.238731  0.224334  0.224656   \n",
       "bread                 0.218959  0.180553  0.182606  0.200194  0.178734   \n",
       "canned_pate           0.277049  0.279122  0.266056  0.268516  0.265583   \n",
       "\n",
       "                           nov       dec  \n",
       "group                                     \n",
       "art._hygienic         0.289881  0.294395  \n",
       "article_of_household       NaN  0.317125  \n",
       "beer                  0.212278  0.220428  \n",
       "bread                 0.168410  0.178313  \n",
       "canned_pate           0.269575  0.244895  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Contribution magin for each category, broek down by months\n",
    "# Contribution margin = 1 - aggregate_cogs / aggregate_revenue\n",
    "category_contribution_margin_by_month = 1 - cat_by_month('agg_cogs') / cat_by_month('agg_revenue')\n",
    "\n",
    "# Store baseline performance\n",
    "store_baseline_margin = 1 - cat_by_month('agg_cogs').sum() / cat_by_month('agg_revenue').sum()\n",
    "\n",
    "category_contribution_margin_by_month.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# We want to subtract category growth by baseline store level performance to see which category is \n",
    "# Over performing, and which category is underperforming relative to baseline.\n",
    "\n",
    "# Pandas doesn't support broadcasting so we'll make the df ourselves\n",
    "base_row = pd.DataFrame(store_baseline_margin).T\n",
    "to_append = []\n",
    "for idx in list(category_contribution_margin_by_month.index):\n",
    "    to_append.append(base_row.rename({0:idx}))\n",
    "\n",
    "broadcasted_baseline_margin = pd.concat(to_append)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Month over month margin change\n",
    "category_margin_performance = get_mom_growth(category_contribution_margin_by_month)\n",
    "category_margin_performance = category_margin_performance.sort_values('jun', ascending=False).loc[top_n_cat_by_contrib_idx(8),:]\n",
    "\n",
    "# Month over month margin change over baseline (store wide m/m margin change)\n",
    "category_margin_performance_over_baseline = get_mom_growth(category_contribution_margin_by_month) - get_mom_growth(broadcasted_baseline_margin)\n",
    "category_margin_performance_over_baseline = category_margin_performance_over_baseline.sort_values('jun', ascending=False).loc[top_n_cat_by_contrib_idx(7),:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Using 3 month moving average to smooth out the volatility a bit more and make the trend more appearant\n",
    "\n",
    "fig, ax = plt.subplots(1, figsize=(12,6))\n",
    "ma(category_margin_performance_over_baseline, 3).T.plot(ax=ax)\n",
    "ax.set_title(\"M/M Category Contribution Margin Change, 3 Month Moving Average\")\n",
    "ax.grid(axis='y')\n",
    "ax.set_xticklabels(category_margin_performance.T.index[1:]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Seems like the positive margin expansion has been casued by the margin expansion of fresh produce\n",
    "# Explore more by looking at volume change\n",
    "category_quantity_performance = get_mom_growth(cat_by_month('quantity')).loc[top_n_cat_by_contrib_idx(8),:]\n",
    "\n",
    "fig, ax = plt.subplots(1, figsize=(12,6))\n",
    "ma(category_quantity_performance, 3).T.plot(ax=ax)\n",
    "ax.set_title(\"M/M Category Volume Change, 3 Month Moving Average\")\n",
    "ax.grid(axis='y')\n",
    "ax.set_xticklabels(category_quantity_performance.T.index[1:]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SKU Analysis\n",
    "\n",
    "Goal:\n",
    "- Find the best performing and upcoming product SKUs and use them to drive cash flow generation and foot traffic to the store.\n",
    "\n",
    "### Anchor Products / Highest Performing SKUs\n",
    "Anchor products are high performence products that generates the bulk of store's free cash flow. Make sure these products are displayed in the middle of the isle, where people are most likely to notice and buy them. Also, spread them around the store to drive foot traffic evenly throughout the store, with the goal of getting the customer to take a whole tour of the store before leaving. \n",
    "\n",
    "Results:\n",
    "- See output below\n",
    "\n",
    "### High Growth Products\n",
    "Results:\n",
    "- See output below"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Product Rotation: Getting the best performing SKU for each quarter of the year\n",
    "You can then use this to advise on product rotation throughout the year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_best_product_for_quarter(q, top_n=200):\n",
    "    \"\"\"Get a list of best performing products for a given quarter\n",
    "    \n",
    "    Args:\n",
    "        q: int\n",
    "            Quarter of the year, 1 to 4\n",
    "            1: Start of Jan - end of Mar\n",
    "            2: Start of Apr - end of Jun\n",
    "            3: Start of Jul - end of Sept\n",
    "            4: Start of Oct - end of Dec\n",
    "        \n",
    "        top_n: int\n",
    "            Get up to top nth SKU\n",
    "    \n",
    "    Returns:\n",
    "        df: DataFrame\n",
    "            df containg best performing SKUs\n",
    "    \"\"\"\n",
    "    df = product_performance.copy()\n",
    "    df['q1_contrib'] = df.loc[:,'jan':'mar'].sum(axis=1)\n",
    "    df['q2_contrib'] = df.loc[:,'apr':'jun'].sum(axis=1)\n",
    "    df['q3_contrib'] = df.loc[:,'jul':'sep'].sum(axis=1)\n",
    "    df['q4_contrib'] = df.loc[:,'oct':'dec'].sum(axis=1)\n",
    "    \n",
    "    quarters = {1:'q1_contrib', 2:'q2_contrib', 3:'q3_contrib', 4:'q4_contrib'}\n",
    "    \n",
    "    quarter = quarters[q]\n",
    "    \n",
    "    return df.sort_values(quarter, ascending=False).iloc[:top_n,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "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>jan</th>\n",
       "      <th>feb</th>\n",
       "      <th>mar</th>\n",
       "      <th>apr</th>\n",
       "      <th>may</th>\n",
       "      <th>jun</th>\n",
       "      <th>jul</th>\n",
       "      <th>aug</th>\n",
       "      <th>sep</th>\n",
       "      <th>oct</th>\n",
       "      <th>...</th>\n",
       "      <th>name</th>\n",
       "      <th>rev_share</th>\n",
       "      <th>cumulative_rev</th>\n",
       "      <th>unit_cogs</th>\n",
       "      <th>unit_revenue</th>\n",
       "      <th>rev_last_n_months</th>\n",
       "      <th>q1_contrib</th>\n",
       "      <th>q2_contrib</th>\n",
       "      <th>q3_contrib</th>\n",
       "      <th>q4_contrib</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sku</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>2625.48</td>\n",
       "      <td>2384.2800</td>\n",
       "      <td>2737.260</td>\n",
       "      <td>2081.82</td>\n",
       "      <td>2872.80</td>\n",
       "      <td>2537.04</td>\n",
       "      <td>3177.20</td>\n",
       "      <td>3458.9100</td>\n",
       "      <td>3339.84</td>\n",
       "      <td>3167.80</td>\n",
       "      <td>...</td>\n",
       "      <td>gos.maslo 250g gostyn</td>\n",
       "      <td>0.032106</td>\n",
       "      <td>0.064546</td>\n",
       "      <td>6.3750</td>\n",
       "      <td>6.645000</td>\n",
       "      <td>9130.710</td>\n",
       "      <td>7747.0200</td>\n",
       "      <td>7491.66</td>\n",
       "      <td>9975.9500</td>\n",
       "      <td>9130.710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>1955.20</td>\n",
       "      <td>2088.1700</td>\n",
       "      <td>3087.980</td>\n",
       "      <td>3372.84</td>\n",
       "      <td>3898.96</td>\n",
       "      <td>3760.41</td>\n",
       "      <td>3867.99</td>\n",
       "      <td>3929.4400</td>\n",
       "      <td>3127.91</td>\n",
       "      <td>1805.27</td>\n",
       "      <td>...</td>\n",
       "      <td>piwo zubr 0_5l butelka</td>\n",
       "      <td>0.032440</td>\n",
       "      <td>0.032440</td>\n",
       "      <td>1.3800</td>\n",
       "      <td>1.637500</td>\n",
       "      <td>5614.540</td>\n",
       "      <td>7131.3500</td>\n",
       "      <td>11032.21</td>\n",
       "      <td>10925.3400</td>\n",
       "      <td>5614.540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14233</th>\n",
       "      <td>2079.77</td>\n",
       "      <td>1221.0000</td>\n",
       "      <td>1994.300</td>\n",
       "      <td>1664.63</td>\n",
       "      <td>1461.13</td>\n",
       "      <td>1359.38</td>\n",
       "      <td>1615.79</td>\n",
       "      <td>1575.0900</td>\n",
       "      <td>1815.22</td>\n",
       "      <td>1302.40</td>\n",
       "      <td>...</td>\n",
       "      <td>pompka simplus 5 zl</td>\n",
       "      <td>0.016466</td>\n",
       "      <td>0.100869</td>\n",
       "      <td>3.8275</td>\n",
       "      <td>4.070000</td>\n",
       "      <td>2828.650</td>\n",
       "      <td>5295.0700</td>\n",
       "      <td>4485.14</td>\n",
       "      <td>5006.1000</td>\n",
       "      <td>2828.650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8934</th>\n",
       "      <td>1524.39</td>\n",
       "      <td>1559.7600</td>\n",
       "      <td>1737.310</td>\n",
       "      <td>1684.38</td>\n",
       "      <td>1742.00</td>\n",
       "      <td>1749.37</td>\n",
       "      <td>1810.34</td>\n",
       "      <td>1832.4500</td>\n",
       "      <td>1933.33</td>\n",
       "      <td>1866.59</td>\n",
       "      <td>...</td>\n",
       "      <td>bulka mala/kajzerka__</td>\n",
       "      <td>0.019857</td>\n",
       "      <td>0.084403</td>\n",
       "      <td>0.5325</td>\n",
       "      <td>0.678333</td>\n",
       "      <td>5668.640</td>\n",
       "      <td>4821.4600</td>\n",
       "      <td>5175.75</td>\n",
       "      <td>5576.1200</td>\n",
       "      <td>5668.640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1179.57</td>\n",
       "      <td>1180.2462</td>\n",
       "      <td>1474.095</td>\n",
       "      <td>1333.20</td>\n",
       "      <td>1380.16</td>\n",
       "      <td>1418.04</td>\n",
       "      <td>1532.16</td>\n",
       "      <td>1476.2305</td>\n",
       "      <td>1602.12</td>\n",
       "      <td>1525.68</td>\n",
       "      <td>...</td>\n",
       "      <td>c chleb krojony 0_6 kg</td>\n",
       "      <td>0.015664</td>\n",
       "      <td>0.116533</td>\n",
       "      <td>2.6000</td>\n",
       "      <td>3.050833</td>\n",
       "      <td>4180.546</td>\n",
       "      <td>3833.9112</td>\n",
       "      <td>4131.40</td>\n",
       "      <td>4610.5105</td>\n",
       "      <td>4180.546</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           jan        feb       mar      apr      may      jun      jul  \\\n",
       "sku                                                                       \n",
       "374    2625.48  2384.2800  2737.260  2081.82  2872.80  2537.04  3177.20   \n",
       "304    1955.20  2088.1700  3087.980  3372.84  3898.96  3760.41  3867.99   \n",
       "14233  2079.77  1221.0000  1994.300  1664.63  1461.13  1359.38  1615.79   \n",
       "8934   1524.39  1559.7600  1737.310  1684.38  1742.00  1749.37  1810.34   \n",
       "3      1179.57  1180.2462  1474.095  1333.20  1380.16  1418.04  1532.16   \n",
       "\n",
       "             aug      sep      oct  ...                    name  rev_share  \\\n",
       "sku                                 ...                                      \n",
       "374    3458.9100  3339.84  3167.80  ...   gos.maslo 250g gostyn   0.032106   \n",
       "304    3929.4400  3127.91  1805.27  ...  piwo zubr 0_5l butelka   0.032440   \n",
       "14233  1575.0900  1815.22  1302.40  ...     pompka simplus 5 zl   0.016466   \n",
       "8934   1832.4500  1933.33  1866.59  ...   bulka mala/kajzerka__   0.019857   \n",
       "3      1476.2305  1602.12  1525.68  ...  c chleb krojony 0_6 kg   0.015664   \n",
       "\n",
       "       cumulative_rev unit_cogs unit_revenue  rev_last_n_months  q1_contrib  \\\n",
       "sku                                                                           \n",
       "374          0.064546    6.3750     6.645000           9130.710   7747.0200   \n",
       "304          0.032440    1.3800     1.637500           5614.540   7131.3500   \n",
       "14233        0.100869    3.8275     4.070000           2828.650   5295.0700   \n",
       "8934         0.084403    0.5325     0.678333           5668.640   4821.4600   \n",
       "3            0.116533    2.6000     3.050833           4180.546   3833.9112   \n",
       "\n",
       "       q2_contrib  q3_contrib  q4_contrib  \n",
       "sku                                        \n",
       "374       7491.66   9975.9500    9130.710  \n",
       "304      11032.21  10925.3400    5614.540  \n",
       "14233     4485.14   5006.1000    2828.650  \n",
       "8934      5175.75   5576.1200    5668.640  \n",
       "3         4131.40   4610.5105    4180.546  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_best_product_for_quarter(1).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cigarettes       41\n",
       "vegetables       25\n",
       "bread            24\n",
       "dairy_chesse     24\n",
       "vodka_alcohol    23\n",
       "drink_juice      12\n",
       "beer             11\n",
       "Name: group, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What categories do top SKUs in Q1 belong to?\n",
    "# If you do this for all 4 quarters you will see these rankings stays relatively constant, \n",
    "# meaning all categories exhibit similar seasonality trends\n",
    "get_best_product_for_quarter(1).group.value_counts().head(7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Finding Growth Categories and Products\n",
    "You can then use this to find trending product and better match consumer demand with stock levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Getting a list of products that have significant sales. This will make sure we have meaningful month over month\n",
    "# growth metrhics. We'll use 1500 PLN annual sales as the bar\n",
    "\n",
    "def get_highest_growth_skus(top_n, min_annual_pln, month):\n",
    "    \"\"\"Returns a dataframe with highest growth skus\n",
    "    \n",
    "    Args:\n",
    "        top_n: int\n",
    "            Get top n high growth skus\n",
    "            \n",
    "        min_annual_pln: int\n",
    "            Minimum annual sales in PLN the sku needs to make in order for it to be considered as a potential\n",
    "            high growth candidate\n",
    "            \n",
    "        month: str\n",
    "            Abbrevated month to rank the high growth skus\n",
    "            \n",
    "    Returns:\n",
    "        df: DataFrame\n",
    "            df containing high growth skus sorted by the month of choice, values in df are 2 month \n",
    "            moving average of dollar contribution growth\n",
    "    \n",
    "    \"\"\"\n",
    "    significant_skus_idx = product_performance[product_performance.annual_total > min_annual_pln].index\n",
    "\n",
    "    # High Growth Products\n",
    "    high_growth_skus = ma(get_mom_growth(product_performance.copy().loc[:,'jan':'dec']), 2)\n",
    "\n",
    "    high_growth_skus = high_growth_skus.loc[significant_skus_idx,:].sort_values(month, ascending=False)\n",
    "    \n",
    "    high_growth_skus = high_growth_skus.join(product_performance[['group','name']])\n",
    "    \n",
    "    return high_growth_skus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>mar</th>\n",
       "      <th>apr</th>\n",
       "      <th>may</th>\n",
       "      <th>jun</th>\n",
       "      <th>jul</th>\n",
       "      <th>aug</th>\n",
       "      <th>sep</th>\n",
       "      <th>oct</th>\n",
       "      <th>nov</th>\n",
       "      <th>dec</th>\n",
       "      <th>group</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sku</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15612</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.544180</td>\n",
       "      <td>-0.327270</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vegetables</td>\n",
       "      <td>kt truskawki kg.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9380</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.301813</td>\n",
       "      <td>2.516216</td>\n",
       "      <td>0.023309</td>\n",
       "      <td>-0.174514</td>\n",
       "      <td>-0.013607</td>\n",
       "      <td>0.022748</td>\n",
       "      <td>-0.079341</td>\n",
       "      <td>0.142659</td>\n",
       "      <td>vegetables</td>\n",
       "      <td>kt ziemniak wczesny kg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>-0.253323</td>\n",
       "      <td>-0.211010</td>\n",
       "      <td>1.132978</td>\n",
       "      <td>1.324529</td>\n",
       "      <td>-0.040267</td>\n",
       "      <td>0.044381</td>\n",
       "      <td>0.415034</td>\n",
       "      <td>0.112238</td>\n",
       "      <td>-0.155521</td>\n",
       "      <td>-0.230972</td>\n",
       "      <td>vegetables</td>\n",
       "      <td>kt kalafior</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12405</th>\n",
       "      <td>-0.486842</td>\n",
       "      <td>-0.500000</td>\n",
       "      <td>0.550000</td>\n",
       "      <td>0.953846</td>\n",
       "      <td>0.477376</td>\n",
       "      <td>0.091387</td>\n",
       "      <td>0.567857</td>\n",
       "      <td>0.517949</td>\n",
       "      <td>-0.399698</td>\n",
       "      <td>0.305430</td>\n",
       "      <td>vodka_alcohol</td>\n",
       "      <td>wodka krupnik premium 0_2l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15403</th>\n",
       "      <td>-0.500404</td>\n",
       "      <td>0.266667</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.928571</td>\n",
       "      <td>0.578571</td>\n",
       "      <td>0.291256</td>\n",
       "      <td>0.579474</td>\n",
       "      <td>0.168987</td>\n",
       "      <td>0.178138</td>\n",
       "      <td>-0.111455</td>\n",
       "      <td>cigarettes</td>\n",
       "      <td>pap rothmans blu link</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            mar       apr       may       jun       jul       aug       sep  \\\n",
       "sku                                                                           \n",
       "15612       NaN       NaN       NaN  7.544180 -0.327270       NaN       NaN   \n",
       "9380        NaN       NaN  5.301813  2.516216  0.023309 -0.174514 -0.013607   \n",
       "277   -0.253323 -0.211010  1.132978  1.324529 -0.040267  0.044381  0.415034   \n",
       "12405 -0.486842 -0.500000  0.550000  0.953846  0.477376  0.091387  0.567857   \n",
       "15403 -0.500404  0.266667  0.666667  0.928571  0.578571  0.291256  0.579474   \n",
       "\n",
       "            oct       nov       dec          group                        name  \n",
       "sku                                                                             \n",
       "15612       NaN       NaN       NaN     vegetables            kt truskawki kg.  \n",
       "9380   0.022748 -0.079341  0.142659     vegetables      kt ziemniak wczesny kg  \n",
       "277    0.112238 -0.155521 -0.230972     vegetables                 kt kalafior  \n",
       "12405  0.517949 -0.399698  0.305430  vodka_alcohol  wodka krupnik premium 0_2l  \n",
       "15403  0.168987  0.178138 -0.111455     cigarettes       pap rothmans blu link  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Getting the highest growth SKUs for jun, next year this time you can promote these a bit more, put them on\n",
    "# better shelf locations etc...\n",
    "\n",
    "get_highest_growth_skus(200, 1500, 'jun').head()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "python3.7",
   "language": "python",
   "name": "python3.7"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}