5__Merging_Concatenating.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Merging and Concatenating Dataframes\n",
    "\n",
    "\n",
    "In this section, you will merge and concatenate multiple dataframes. Merging is one of the most common operations you will do, since data often comes in various files. \n",
    "\n",
    "In our case, we have sales data of a retail store spread across multiple files. We will now work with all these data files and learn to:\n",
    "* Merge multiple dataframes using common columns/keys using ```pd.merge()```\n",
    "* Concatenate dataframes using ```pd.concat()```\n",
    "\n",
    "Let's first read all the data files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] File b'./global_sales_data/market_fact.csv' does not exist: b'./global_sales_data/market_fact.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-5-951898b71644>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mmarket_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"./global_sales_data/market_fact.csv\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[0mcustomer_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"./global_sales_data/cust_dimen.csv\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[0mproduct_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"./global_sales_data/prod_dimen.csv\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[0;32m    700\u001b[0m                     skip_blank_lines=skip_blank_lines)\n\u001b[0;32m    701\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 702\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    703\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    704\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_read\u001b[1;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[0;32m    427\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    428\u001b[0m     \u001b[1;31m# Create the parser.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 429\u001b[1;33m     \u001b[0mparser\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    430\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    431\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[0;32m    893\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'has_index_names'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'has_index_names'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    894\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 895\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    896\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    897\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[1;34m(self, engine)\u001b[0m\n\u001b[0;32m   1120\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'c'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1121\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'c'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1122\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1123\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1124\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'python'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, src, **kwds)\u001b[0m\n\u001b[0;32m   1851\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'usecols'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0musecols\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1852\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1853\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1854\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munnamed_cols\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munnamed_cols\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1855\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] File b'./global_sales_data/market_fact.csv' does not exist: b'./global_sales_data/market_fact.csv'"
     ]
    }
   ],
   "source": [
    "# loading libraries and reading the data\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "market_df = pd.read_csv(\"./global_sales_data/market_fact.csv\")\n",
    "customer_df = pd.read_csv(\"./global_sales_data/cust_dimen.csv\")\n",
    "product_df = pd.read_csv(\"./global_sales_data/prod_dimen.csv\")\n",
    "shipping_df = pd.read_csv(\"./global_sales_data/shipping_dimen.csv\")\n",
    "orders_df = pd.read_csv(\"./global_sales_data/orders_dimen.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Merging Dataframes Using ```pd.merge()```\n",
    "\n",
    "There are five data files:\n",
    "1. The ```market_fact``` table contains the sales data of each order\n",
    "2. The other 4 files are called 'dimension tables/files' and contain metadata about customers, products, shipping details, order details etc.\n",
    "\n",
    "If you are familiar with star schemas and data warehouse designs, you will note that we have one fact table and four dimension tables. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ord_id</th>\n",
       "      <th>Prod_id</th>\n",
       "      <th>Ship_id</th>\n",
       "      <th>Cust_id</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Shipping_Cost</th>\n",
       "      <th>Product_Base_Margin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7609</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>136.81</td>\n",
       "      <td>0.01</td>\n",
       "      <td>23</td>\n",
       "      <td>-30.51</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ord_5406</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_7549</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>42.27</td>\n",
       "      <td>0.01</td>\n",
       "      <td>13</td>\n",
       "      <td>4.56</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_7610</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>4701.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>26</td>\n",
       "      <td>1148.90</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ord_5456</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_7625</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>2337.89</td>\n",
       "      <td>0.09</td>\n",
       "      <td>43</td>\n",
       "      <td>729.34</td>\n",
       "      <td>14.30</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ord_5485</td>\n",
       "      <td>Prod_17</td>\n",
       "      <td>SHP_7664</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>4233.15</td>\n",
       "      <td>0.08</td>\n",
       "      <td>35</td>\n",
       "      <td>1219.87</td>\n",
       "      <td>26.30</td>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ord_id  Prod_id   Ship_id    Cust_id    Sales  Discount  Order_Quantity  \\\n",
       "0  Ord_5446  Prod_16  SHP_7609  Cust_1818   136.81      0.01              23   \n",
       "1  Ord_5406  Prod_13  SHP_7549  Cust_1818    42.27      0.01              13   \n",
       "2  Ord_5446   Prod_4  SHP_7610  Cust_1818  4701.69      0.00              26   \n",
       "3  Ord_5456   Prod_6  SHP_7625  Cust_1818  2337.89      0.09              43   \n",
       "4  Ord_5485  Prod_17  SHP_7664  Cust_1818  4233.15      0.08              35   \n",
       "\n",
       "    Profit  Shipping_Cost  Product_Base_Margin  \n",
       "0   -30.51           3.60                 0.56  \n",
       "1     4.56           0.93                 0.54  \n",
       "2  1148.90           2.50                 0.59  \n",
       "3   729.34          14.30                 0.37  \n",
       "4  1219.87          26.30                 0.38  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Already familiar with market data: Each row is an order\n",
    "market_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer_Name</th>\n",
       "      <th>Province</th>\n",
       "      <th>Region</th>\n",
       "      <th>Customer_Segment</th>\n",
       "      <th>Cust_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MUHAMMED MACINTYRE</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>SMALL BUSINESS</td>\n",
       "      <td>Cust_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BARRY FRENCH</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>CONSUMER</td>\n",
       "      <td>Cust_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CLAY ROZENDAL</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>Cust_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CARLOS SOLTERO</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>CONSUMER</td>\n",
       "      <td>Cust_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CARL JACKSON</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>Cust_5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Customer_Name Province   Region Customer_Segment Cust_id\n",
       "0  MUHAMMED MACINTYRE  NUNAVUT  NUNAVUT   SMALL BUSINESS  Cust_1\n",
       "1        BARRY FRENCH  NUNAVUT  NUNAVUT         CONSUMER  Cust_2\n",
       "2       CLAY ROZENDAL  NUNAVUT  NUNAVUT        CORPORATE  Cust_3\n",
       "3      CARLOS SOLTERO  NUNAVUT  NUNAVUT         CONSUMER  Cust_4\n",
       "4        CARL JACKSON  NUNAVUT  NUNAVUT        CORPORATE  Cust_5"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Customer dimension table: Each row contains metadata about customers\n",
    "customer_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Product_Category</th>\n",
       "      <th>Product_Sub_Category</th>\n",
       "      <th>Prod_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "      <td>Prod_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>APPLIANCES</td>\n",
       "      <td>Prod_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>BINDERS AND BINDER ACCESSORIES</td>\n",
       "      <td>Prod_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TECHNOLOGY</td>\n",
       "      <td>TELEPHONES AND COMMUNICATION</td>\n",
       "      <td>Prod_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FURNITURE</td>\n",
       "      <td>OFFICE FURNISHINGS</td>\n",
       "      <td>Prod_5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Product_Category            Product_Sub_Category Prod_id\n",
       "0  OFFICE SUPPLIES          STORAGE & ORGANIZATION  Prod_1\n",
       "1  OFFICE SUPPLIES                      APPLIANCES  Prod_2\n",
       "2  OFFICE SUPPLIES  BINDERS AND BINDER ACCESSORIES  Prod_3\n",
       "3       TECHNOLOGY    TELEPHONES AND COMMUNICATION  Prod_4\n",
       "4        FURNITURE              OFFICE FURNISHINGS  Prod_5"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Product dimension table\n",
    "product_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Order_ID</th>\n",
       "      <th>Ship_Mode</th>\n",
       "      <th>Ship_Date</th>\n",
       "      <th>Ship_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>REGULAR AIR</td>\n",
       "      <td>20-10-2010</td>\n",
       "      <td>SHP_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>293</td>\n",
       "      <td>DELIVERY TRUCK</td>\n",
       "      <td>02-10-2012</td>\n",
       "      <td>SHP_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>293</td>\n",
       "      <td>REGULAR AIR</td>\n",
       "      <td>03-10-2012</td>\n",
       "      <td>SHP_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>483</td>\n",
       "      <td>REGULAR AIR</td>\n",
       "      <td>12-07-2011</td>\n",
       "      <td>SHP_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>515</td>\n",
       "      <td>REGULAR AIR</td>\n",
       "      <td>30-08-2010</td>\n",
       "      <td>SHP_5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Order_ID       Ship_Mode   Ship_Date Ship_id\n",
       "0         3     REGULAR AIR  20-10-2010   SHP_1\n",
       "1       293  DELIVERY TRUCK  02-10-2012   SHP_2\n",
       "2       293     REGULAR AIR  03-10-2012   SHP_3\n",
       "3       483     REGULAR AIR  12-07-2011   SHP_4\n",
       "4       515     REGULAR AIR  30-08-2010   SHP_5"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Shipping metadata\n",
    "shipping_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Order_ID</th>\n",
       "      <th>Order_Date</th>\n",
       "      <th>Order_Priority</th>\n",
       "      <th>Ord_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>13-10-2010</td>\n",
       "      <td>LOW</td>\n",
       "      <td>Ord_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>293</td>\n",
       "      <td>01-10-2012</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>Ord_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>483</td>\n",
       "      <td>10-07-2011</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>Ord_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>515</td>\n",
       "      <td>28-08-2010</td>\n",
       "      <td>NOT SPECIFIED</td>\n",
       "      <td>Ord_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>613</td>\n",
       "      <td>17-06-2011</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>Ord_5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Order_ID  Order_Date Order_Priority Ord_id\n",
       "0         3  13-10-2010            LOW  Ord_1\n",
       "1       293  01-10-2012           HIGH  Ord_2\n",
       "2       483  10-07-2011           HIGH  Ord_3\n",
       "3       515  28-08-2010  NOT SPECIFIED  Ord_4\n",
       "4       613  17-06-2011           HIGH  Ord_5"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Orders dimension table\n",
    "orders_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Merging Dataframes\n",
    "\n",
    "Say you want to select all orders and observe the ```Sales``` of the customer segment *Corporate*. Since customer segment details are present in the dataframe ```customer_df```, we will first need to merge it with ```market_df```.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ord_id</th>\n",
       "      <th>Prod_id</th>\n",
       "      <th>Ship_id</th>\n",
       "      <th>Cust_id</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Shipping_Cost</th>\n",
       "      <th>Product_Base_Margin</th>\n",
       "      <th>Customer_Name</th>\n",
       "      <th>Province</th>\n",
       "      <th>Region</th>\n",
       "      <th>Customer_Segment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7609</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>136.81</td>\n",
       "      <td>0.01</td>\n",
       "      <td>23</td>\n",
       "      <td>-30.51</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.56</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ord_5406</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_7549</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>42.27</td>\n",
       "      <td>0.01</td>\n",
       "      <td>13</td>\n",
       "      <td>4.56</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.54</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_7610</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>4701.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>26</td>\n",
       "      <td>1148.90</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.59</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ord_5456</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_7625</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>2337.89</td>\n",
       "      <td>0.09</td>\n",
       "      <td>43</td>\n",
       "      <td>729.34</td>\n",
       "      <td>14.30</td>\n",
       "      <td>0.37</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ord_5485</td>\n",
       "      <td>Prod_17</td>\n",
       "      <td>SHP_7664</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>4233.15</td>\n",
       "      <td>0.08</td>\n",
       "      <td>35</td>\n",
       "      <td>1219.87</td>\n",
       "      <td>26.30</td>\n",
       "      <td>0.38</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ord_id  Prod_id   Ship_id    Cust_id    Sales  Discount  Order_Quantity  \\\n",
       "0  Ord_5446  Prod_16  SHP_7609  Cust_1818   136.81      0.01              23   \n",
       "1  Ord_5406  Prod_13  SHP_7549  Cust_1818    42.27      0.01              13   \n",
       "2  Ord_5446   Prod_4  SHP_7610  Cust_1818  4701.69      0.00              26   \n",
       "3  Ord_5456   Prod_6  SHP_7625  Cust_1818  2337.89      0.09              43   \n",
       "4  Ord_5485  Prod_17  SHP_7664  Cust_1818  4233.15      0.08              35   \n",
       "\n",
       "    Profit  Shipping_Cost  Product_Base_Margin  Customer_Name Province Region  \\\n",
       "0   -30.51           3.60                 0.56  AARON BERGMAN  ALBERTA   WEST   \n",
       "1     4.56           0.93                 0.54  AARON BERGMAN  ALBERTA   WEST   \n",
       "2  1148.90           2.50                 0.59  AARON BERGMAN  ALBERTA   WEST   \n",
       "3   729.34          14.30                 0.37  AARON BERGMAN  ALBERTA   WEST   \n",
       "4  1219.87          26.30                 0.38  AARON BERGMAN  ALBERTA   WEST   \n",
       "\n",
       "  Customer_Segment  \n",
       "0        CORPORATE  \n",
       "1        CORPORATE  \n",
       "2        CORPORATE  \n",
       "3        CORPORATE  \n",
       "4        CORPORATE  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merging the dataframes\n",
    "# Note that Cust_id is the common column/key, which is provided to the 'on' argument\n",
    "# how = 'inner' makes sure that only the customer ids present in both dfs are included in the result\n",
    "df_1 = pd.merge(market_df, customer_df, how='inner', on='Cust_id')\n",
    "df_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ord_id</th>\n",
       "      <th>Prod_id</th>\n",
       "      <th>Ship_id</th>\n",
       "      <th>Cust_id</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Shipping_Cost</th>\n",
       "      <th>Product_Base_Margin</th>\n",
       "      <th>Customer_Name</th>\n",
       "      <th>Province</th>\n",
       "      <th>Region</th>\n",
       "      <th>Customer_Segment</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7609</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>136.8100</td>\n",
       "      <td>0.01</td>\n",
       "      <td>23</td>\n",
       "      <td>-30.51</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.56</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ord_5406</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_7549</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>42.2700</td>\n",
       "      <td>0.01</td>\n",
       "      <td>13</td>\n",
       "      <td>4.56</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.54</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_7610</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>4701.6900</td>\n",
       "      <td>0.00</td>\n",
       "      <td>26</td>\n",
       "      <td>1148.90</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.59</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ord_5456</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_7625</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>2337.8900</td>\n",
       "      <td>0.09</td>\n",
       "      <td>43</td>\n",
       "      <td>729.34</td>\n",
       "      <td>14.30</td>\n",
       "      <td>0.37</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ord_5485</td>\n",
       "      <td>Prod_17</td>\n",
       "      <td>SHP_7664</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>4233.1500</td>\n",
       "      <td>0.08</td>\n",
       "      <td>35</td>\n",
       "      <td>1219.87</td>\n",
       "      <td>26.30</td>\n",
       "      <td>0.38</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_7608</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>164.0200</td>\n",
       "      <td>0.03</td>\n",
       "      <td>23</td>\n",
       "      <td>-47.64</td>\n",
       "      <td>6.15</td>\n",
       "      <td>0.37</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ord_31</td>\n",
       "      <td>Prod_12</td>\n",
       "      <td>SHP_41</td>\n",
       "      <td>Cust_26</td>\n",
       "      <td>14.7600</td>\n",
       "      <td>0.01</td>\n",
       "      <td>5</td>\n",
       "      <td>1.32</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.36</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Ord_4768</td>\n",
       "      <td>Prod_12</td>\n",
       "      <td>SHP_6650</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>3.8500</td>\n",
       "      <td>0.08</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.36</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.37</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Ord_4690</td>\n",
       "      <td>Prod_2</td>\n",
       "      <td>SHP_6545</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>904.1200</td>\n",
       "      <td>0.07</td>\n",
       "      <td>4</td>\n",
       "      <td>28.81</td>\n",
       "      <td>11.79</td>\n",
       "      <td>0.42</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Ord_4659</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_6493</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>1451.5900</td>\n",
       "      <td>0.06</td>\n",
       "      <td>26</td>\n",
       "      <td>435.11</td>\n",
       "      <td>14.30</td>\n",
       "      <td>0.37</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Ord_4622</td>\n",
       "      <td>Prod_12</td>\n",
       "      <td>SHP_6437</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>56.2600</td>\n",
       "      <td>0.00</td>\n",
       "      <td>14</td>\n",
       "      <td>28.11</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.38</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Ord_4657</td>\n",
       "      <td>Prod_5</td>\n",
       "      <td>SHP_6490</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>336.8600</td>\n",
       "      <td>0.06</td>\n",
       "      <td>23</td>\n",
       "      <td>36.32</td>\n",
       "      <td>5.30</td>\n",
       "      <td>0.46</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Ord_4682</td>\n",
       "      <td>Prod_5</td>\n",
       "      <td>SHP_6531</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>63.9100</td>\n",
       "      <td>0.04</td>\n",
       "      <td>14</td>\n",
       "      <td>-44.47</td>\n",
       "      <td>6.60</td>\n",
       "      <td>0.49</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Ord_4768</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_6651</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>547.0005</td>\n",
       "      <td>0.08</td>\n",
       "      <td>10</td>\n",
       "      <td>-97.20</td>\n",
       "      <td>3.90</td>\n",
       "      <td>0.55</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Ord_4755</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_6628</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>3.4100</td>\n",
       "      <td>0.06</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.78</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.56</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Ord_4659</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_6492</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>391.9000</td>\n",
       "      <td>0.10</td>\n",
       "      <td>11</td>\n",
       "      <td>-47.01</td>\n",
       "      <td>19.99</td>\n",
       "      <td>0.38</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Ord_4682</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_6531</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>1909.0065</td>\n",
       "      <td>0.01</td>\n",
       "      <td>32</td>\n",
       "      <td>344.13</td>\n",
       "      <td>8.99</td>\n",
       "      <td>0.59</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Ord_4657</td>\n",
       "      <td>Prod_5</td>\n",
       "      <td>SHP_6489</td>\n",
       "      <td>Cust_1579</td>\n",
       "      <td>418.0300</td>\n",
       "      <td>0.00</td>\n",
       "      <td>47</td>\n",
       "      <td>-158.58</td>\n",
       "      <td>7.96</td>\n",
       "      <td>0.49</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Ord_4410</td>\n",
       "      <td>Prod_5</td>\n",
       "      <td>SHP_6146</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>605.7700</td>\n",
       "      <td>0.05</td>\n",
       "      <td>42</td>\n",
       "      <td>129.33</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0.49</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Ord_4546</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6327</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>5208.7800</td>\n",
       "      <td>0.05</td>\n",
       "      <td>34</td>\n",
       "      <td>1547.78</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.59</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Ord_4499</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_6264</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>67.4900</td>\n",
       "      <td>0.06</td>\n",
       "      <td>1</td>\n",
       "      <td>-22.82</td>\n",
       "      <td>14.30</td>\n",
       "      <td>0.37</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Ord_4552</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_6335</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>284.4525</td>\n",
       "      <td>0.06</td>\n",
       "      <td>5</td>\n",
       "      <td>-254.78</td>\n",
       "      <td>8.99</td>\n",
       "      <td>0.58</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Ord_4552</td>\n",
       "      <td>Prod_12</td>\n",
       "      <td>SHP_6335</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>104.7000</td>\n",
       "      <td>0.09</td>\n",
       "      <td>29</td>\n",
       "      <td>42.16</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.38</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Ord_4497</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_6261</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>211.9700</td>\n",
       "      <td>0.06</td>\n",
       "      <td>10</td>\n",
       "      <td>-46.83</td>\n",
       "      <td>8.99</td>\n",
       "      <td>0.59</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Ord_4410</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_6146</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>1480.9100</td>\n",
       "      <td>0.00</td>\n",
       "      <td>44</td>\n",
       "      <td>489.14</td>\n",
       "      <td>8.74</td>\n",
       "      <td>0.40</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Ord_4499</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_6265</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>6.7600</td>\n",
       "      <td>0.02</td>\n",
       "      <td>3</td>\n",
       "      <td>-4.28</td>\n",
       "      <td>1.57</td>\n",
       "      <td>0.59</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Ord_4475</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_6234</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>7640.2250</td>\n",
       "      <td>0.07</td>\n",
       "      <td>46</td>\n",
       "      <td>2027.68</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.59</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Ord_4547</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_6328</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>23.4400</td>\n",
       "      <td>0.05</td>\n",
       "      <td>3</td>\n",
       "      <td>-10.58</td>\n",
       "      <td>5.20</td>\n",
       "      <td>0.36</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Ord_4360</td>\n",
       "      <td>Prod_11</td>\n",
       "      <td>SHP_6079</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>1736.4100</td>\n",
       "      <td>0.10</td>\n",
       "      <td>12</td>\n",
       "      <td>-762.44</td>\n",
       "      <td>80.20</td>\n",
       "      <td>0.71</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Ord_4541</td>\n",
       "      <td>Prod_2</td>\n",
       "      <td>SHP_6322</td>\n",
       "      <td>Cust_1474</td>\n",
       "      <td>336.6500</td>\n",
       "      <td>0.07</td>\n",
       "      <td>30</td>\n",
       "      <td>-71.05</td>\n",
       "      <td>6.96</td>\n",
       "      <td>0.50</td>\n",
       "      <td>ADAM HART</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8351</th>\n",
       "      <td>Ord_3584</td>\n",
       "      <td>Prod_15</td>\n",
       "      <td>SHP_4961</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>2502.6700</td>\n",
       "      <td>0.10</td>\n",
       "      <td>9</td>\n",
       "      <td>-198.80</td>\n",
       "      <td>64.73</td>\n",
       "      <td>0.56</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8352</th>\n",
       "      <td>Ord_3638</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_5037</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>36.4300</td>\n",
       "      <td>0.04</td>\n",
       "      <td>5</td>\n",
       "      <td>-22.04</td>\n",
       "      <td>7.15</td>\n",
       "      <td>0.36</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8353</th>\n",
       "      <td>Ord_3610</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_4999</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>88.5900</td>\n",
       "      <td>0.05</td>\n",
       "      <td>7</td>\n",
       "      <td>-26.29</td>\n",
       "      <td>5.81</td>\n",
       "      <td>0.60</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8354</th>\n",
       "      <td>Ord_3592</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_4973</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>2614.3705</td>\n",
       "      <td>0.07</td>\n",
       "      <td>25</td>\n",
       "      <td>384.01</td>\n",
       "      <td>7.69</td>\n",
       "      <td>0.58</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8355</th>\n",
       "      <td>Ord_3592</td>\n",
       "      <td>Prod_17</td>\n",
       "      <td>SHP_4973</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>636.5000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>46</td>\n",
       "      <td>-71.98</td>\n",
       "      <td>9.44</td>\n",
       "      <td>0.39</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8356</th>\n",
       "      <td>Ord_3639</td>\n",
       "      <td>Prod_5</td>\n",
       "      <td>SHP_5040</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>40.3400</td>\n",
       "      <td>0.03</td>\n",
       "      <td>2</td>\n",
       "      <td>-23.62</td>\n",
       "      <td>7.74</td>\n",
       "      <td>0.50</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8357</th>\n",
       "      <td>Ord_3610</td>\n",
       "      <td>Prod_14</td>\n",
       "      <td>SHP_4998</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>1759.6500</td>\n",
       "      <td>0.06</td>\n",
       "      <td>3</td>\n",
       "      <td>-2213.75</td>\n",
       "      <td>24.49</td>\n",
       "      <td>0.50</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8358</th>\n",
       "      <td>Ord_3582</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_4959</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>539.6600</td>\n",
       "      <td>0.00</td>\n",
       "      <td>26</td>\n",
       "      <td>147.08</td>\n",
       "      <td>5.97</td>\n",
       "      <td>0.38</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8359</th>\n",
       "      <td>Ord_3543</td>\n",
       "      <td>Prod_3</td>\n",
       "      <td>SHP_4906</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>514.2200</td>\n",
       "      <td>0.02</td>\n",
       "      <td>17</td>\n",
       "      <td>187.37</td>\n",
       "      <td>2.99</td>\n",
       "      <td>0.35</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8360</th>\n",
       "      <td>Ord_3639</td>\n",
       "      <td>Prod_10</td>\n",
       "      <td>SHP_5038</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>2173.2600</td>\n",
       "      <td>0.00</td>\n",
       "      <td>35</td>\n",
       "      <td>-465.66</td>\n",
       "      <td>36.61</td>\n",
       "      <td>0.61</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8370</th>\n",
       "      <td>Ord_2696</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_3690</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>62.7800</td>\n",
       "      <td>0.04</td>\n",
       "      <td>20</td>\n",
       "      <td>-17.75</td>\n",
       "      <td>2.03</td>\n",
       "      <td>0.57</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8371</th>\n",
       "      <td>Ord_2624</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_3591</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>4924.1350</td>\n",
       "      <td>0.07</td>\n",
       "      <td>28</td>\n",
       "      <td>1049.54</td>\n",
       "      <td>8.99</td>\n",
       "      <td>0.58</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8372</th>\n",
       "      <td>Ord_2772</td>\n",
       "      <td>Prod_9</td>\n",
       "      <td>SHP_3806</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>56.9000</td>\n",
       "      <td>0.03</td>\n",
       "      <td>7</td>\n",
       "      <td>12.64</td>\n",
       "      <td>1.39</td>\n",
       "      <td>0.36</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8373</th>\n",
       "      <td>Ord_2600</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_3560</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>106.6400</td>\n",
       "      <td>0.10</td>\n",
       "      <td>30</td>\n",
       "      <td>-31.95</td>\n",
       "      <td>1.32</td>\n",
       "      <td>0.83</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8374</th>\n",
       "      <td>Ord_2658</td>\n",
       "      <td>Prod_5</td>\n",
       "      <td>SHP_3637</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>1082.6600</td>\n",
       "      <td>0.08</td>\n",
       "      <td>14</td>\n",
       "      <td>-256.93</td>\n",
       "      <td>48.20</td>\n",
       "      <td>0.74</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8375</th>\n",
       "      <td>Ord_2772</td>\n",
       "      <td>Prod_3</td>\n",
       "      <td>SHP_3806</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>1413.8200</td>\n",
       "      <td>0.10</td>\n",
       "      <td>47</td>\n",
       "      <td>226.53</td>\n",
       "      <td>11.63</td>\n",
       "      <td>0.37</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8376</th>\n",
       "      <td>Ord_2624</td>\n",
       "      <td>Prod_8</td>\n",
       "      <td>SHP_3590</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>1211.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>36</td>\n",
       "      <td>-27.99</td>\n",
       "      <td>6.50</td>\n",
       "      <td>0.79</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8377</th>\n",
       "      <td>Ord_2722</td>\n",
       "      <td>Prod_12</td>\n",
       "      <td>SHP_3729</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>34.0100</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12</td>\n",
       "      <td>10.58</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.39</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8378</th>\n",
       "      <td>Ord_2706</td>\n",
       "      <td>Prod_2</td>\n",
       "      <td>SHP_3705</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>1361.9100</td>\n",
       "      <td>0.05</td>\n",
       "      <td>20</td>\n",
       "      <td>312.52</td>\n",
       "      <td>3.50</td>\n",
       "      <td>0.59</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8379</th>\n",
       "      <td>Ord_2722</td>\n",
       "      <td>Prod_5</td>\n",
       "      <td>SHP_3730</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>1008.9500</td>\n",
       "      <td>0.04</td>\n",
       "      <td>41</td>\n",
       "      <td>69.31</td>\n",
       "      <td>8.99</td>\n",
       "      <td>0.50</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8380</th>\n",
       "      <td>Ord_2772</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_3807</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>308.9200</td>\n",
       "      <td>0.04</td>\n",
       "      <td>45</td>\n",
       "      <td>-143.58</td>\n",
       "      <td>7.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8381</th>\n",
       "      <td>Ord_2696</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_3691</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>2836.0505</td>\n",
       "      <td>0.01</td>\n",
       "      <td>25</td>\n",
       "      <td>561.13</td>\n",
       "      <td>8.99</td>\n",
       "      <td>0.59</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8382</th>\n",
       "      <td>Ord_2658</td>\n",
       "      <td>Prod_3</td>\n",
       "      <td>SHP_3636</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>120.9800</td>\n",
       "      <td>0.00</td>\n",
       "      <td>28</td>\n",
       "      <td>-92.85</td>\n",
       "      <td>5.34</td>\n",
       "      <td>0.38</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8383</th>\n",
       "      <td>Ord_2722</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_3731</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>3508.3300</td>\n",
       "      <td>0.04</td>\n",
       "      <td>21</td>\n",
       "      <td>-546.98</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.85</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8384</th>\n",
       "      <td>Ord_4620</td>\n",
       "      <td>Prod_3</td>\n",
       "      <td>SHP_6435</td>\n",
       "      <td>Cust_1577</td>\n",
       "      <td>59.6200</td>\n",
       "      <td>0.04</td>\n",
       "      <td>10</td>\n",
       "      <td>-56.30</td>\n",
       "      <td>7.78</td>\n",
       "      <td>0.37</td>\n",
       "      <td>YANA SORENSEN</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8385</th>\n",
       "      <td>Ord_1833</td>\n",
       "      <td>Prod_3</td>\n",
       "      <td>SHP_2527</td>\n",
       "      <td>Cust_637</td>\n",
       "      <td>611.1600</td>\n",
       "      <td>0.04</td>\n",
       "      <td>46</td>\n",
       "      <td>100.22</td>\n",
       "      <td>4.98</td>\n",
       "      <td>0.40</td>\n",
       "      <td>YANA SORENSEN</td>\n",
       "      <td>NEWFOUNDLAND</td>\n",
       "      <td>ATLANTIC</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8386</th>\n",
       "      <td>Ord_2324</td>\n",
       "      <td>Prod_7</td>\n",
       "      <td>SHP_3189</td>\n",
       "      <td>Cust_851</td>\n",
       "      <td>121.8700</td>\n",
       "      <td>0.07</td>\n",
       "      <td>39</td>\n",
       "      <td>11.32</td>\n",
       "      <td>1.35</td>\n",
       "      <td>0.40</td>\n",
       "      <td>YANA SORENSEN</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8387</th>\n",
       "      <td>Ord_2220</td>\n",
       "      <td>Prod_3</td>\n",
       "      <td>SHP_3019</td>\n",
       "      <td>Cust_851</td>\n",
       "      <td>41.0600</td>\n",
       "      <td>0.04</td>\n",
       "      <td>4</td>\n",
       "      <td>-16.39</td>\n",
       "      <td>6.28</td>\n",
       "      <td>0.35</td>\n",
       "      <td>YANA SORENSEN</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8388</th>\n",
       "      <td>Ord_4424</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6165</td>\n",
       "      <td>Cust_1519</td>\n",
       "      <td>994.0400</td>\n",
       "      <td>0.03</td>\n",
       "      <td>10</td>\n",
       "      <td>-335.06</td>\n",
       "      <td>35.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>YANA SORENSEN</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8389</th>\n",
       "      <td>Ord_4444</td>\n",
       "      <td>Prod_13</td>\n",
       "      <td>SHP_6192</td>\n",
       "      <td>Cust_1519</td>\n",
       "      <td>159.4100</td>\n",
       "      <td>0.00</td>\n",
       "      <td>44</td>\n",
       "      <td>34.68</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.52</td>\n",
       "      <td>YANA SORENSEN</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3076 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ord_id  Prod_id   Ship_id    Cust_id      Sales  Discount  \\\n",
       "0     Ord_5446  Prod_16  SHP_7609  Cust_1818   136.8100      0.01   \n",
       "1     Ord_5406  Prod_13  SHP_7549  Cust_1818    42.2700      0.01   \n",
       "2     Ord_5446   Prod_4  SHP_7610  Cust_1818  4701.6900      0.00   \n",
       "3     Ord_5456   Prod_6  SHP_7625  Cust_1818  2337.8900      0.09   \n",
       "4     Ord_5485  Prod_17  SHP_7664  Cust_1818  4233.1500      0.08   \n",
       "5     Ord_5446   Prod_6  SHP_7608  Cust_1818   164.0200      0.03   \n",
       "6       Ord_31  Prod_12    SHP_41    Cust_26    14.7600      0.01   \n",
       "45    Ord_4768  Prod_12  SHP_6650  Cust_1579     3.8500      0.08   \n",
       "46    Ord_4690   Prod_2  SHP_6545  Cust_1579   904.1200      0.07   \n",
       "47    Ord_4659   Prod_6  SHP_6493  Cust_1579  1451.5900      0.06   \n",
       "48    Ord_4622  Prod_12  SHP_6437  Cust_1579    56.2600      0.00   \n",
       "49    Ord_4657   Prod_5  SHP_6490  Cust_1579   336.8600      0.06   \n",
       "50    Ord_4682   Prod_5  SHP_6531  Cust_1579    63.9100      0.04   \n",
       "51    Ord_4768   Prod_4  SHP_6651  Cust_1579   547.0005      0.08   \n",
       "52    Ord_4755  Prod_13  SHP_6628  Cust_1579     3.4100      0.06   \n",
       "53    Ord_4659   Prod_6  SHP_6492  Cust_1579   391.9000      0.10   \n",
       "54    Ord_4682   Prod_4  SHP_6531  Cust_1579  1909.0065      0.01   \n",
       "55    Ord_4657   Prod_5  SHP_6489  Cust_1579   418.0300      0.00   \n",
       "56    Ord_4410   Prod_5  SHP_6146  Cust_1474   605.7700      0.05   \n",
       "57    Ord_4546   Prod_1  SHP_6327  Cust_1474  5208.7800      0.05   \n",
       "58    Ord_4499   Prod_6  SHP_6264  Cust_1474    67.4900      0.06   \n",
       "59    Ord_4552   Prod_4  SHP_6335  Cust_1474   284.4525      0.06   \n",
       "60    Ord_4552  Prod_12  SHP_6335  Cust_1474   104.7000      0.09   \n",
       "61    Ord_4497  Prod_13  SHP_6261  Cust_1474   211.9700      0.06   \n",
       "62    Ord_4410   Prod_6  SHP_6146  Cust_1474  1480.9100      0.00   \n",
       "63    Ord_4499  Prod_13  SHP_6265  Cust_1474     6.7600      0.02   \n",
       "64    Ord_4475   Prod_4  SHP_6234  Cust_1474  7640.2250      0.07   \n",
       "65    Ord_4547   Prod_6  SHP_6328  Cust_1474    23.4400      0.05   \n",
       "66    Ord_4360  Prod_11  SHP_6079  Cust_1474  1736.4100      0.10   \n",
       "67    Ord_4541   Prod_2  SHP_6322  Cust_1474   336.6500      0.07   \n",
       "...        ...      ...       ...        ...        ...       ...   \n",
       "8351  Ord_3584  Prod_15  SHP_4961  Cust_1266  2502.6700      0.10   \n",
       "8352  Ord_3638   Prod_6  SHP_5037  Cust_1266    36.4300      0.04   \n",
       "8353  Ord_3610  Prod_13  SHP_4999  Cust_1266    88.5900      0.05   \n",
       "8354  Ord_3592   Prod_4  SHP_4973  Cust_1266  2614.3705      0.07   \n",
       "8355  Ord_3592  Prod_17  SHP_4973  Cust_1266   636.5000      0.01   \n",
       "8356  Ord_3639   Prod_5  SHP_5040  Cust_1266    40.3400      0.03   \n",
       "8357  Ord_3610  Prod_14  SHP_4998  Cust_1266  1759.6500      0.06   \n",
       "8358  Ord_3582   Prod_6  SHP_4959  Cust_1266   539.6600      0.00   \n",
       "8359  Ord_3543   Prod_3  SHP_4906  Cust_1266   514.2200      0.02   \n",
       "8360  Ord_3639  Prod_10  SHP_5038  Cust_1266  2173.2600      0.00   \n",
       "8370  Ord_2696  Prod_13  SHP_3690  Cust_1006    62.7800      0.04   \n",
       "8371  Ord_2624   Prod_4  SHP_3591  Cust_1006  4924.1350      0.07   \n",
       "8372  Ord_2772   Prod_9  SHP_3806  Cust_1006    56.9000      0.03   \n",
       "8373  Ord_2600  Prod_16  SHP_3560  Cust_1006   106.6400      0.10   \n",
       "8374  Ord_2658   Prod_5  SHP_3637  Cust_1006  1082.6600      0.08   \n",
       "8375  Ord_2772   Prod_3  SHP_3806  Cust_1006  1413.8200      0.10   \n",
       "8376  Ord_2624   Prod_8  SHP_3590  Cust_1006  1211.0000      0.00   \n",
       "8377  Ord_2722  Prod_12  SHP_3729  Cust_1006    34.0100      0.00   \n",
       "8378  Ord_2706   Prod_2  SHP_3705  Cust_1006  1361.9100      0.05   \n",
       "8379  Ord_2722   Prod_5  SHP_3730  Cust_1006  1008.9500      0.04   \n",
       "8380  Ord_2772   Prod_6  SHP_3807  Cust_1006   308.9200      0.04   \n",
       "8381  Ord_2696   Prod_4  SHP_3691  Cust_1006  2836.0505      0.01   \n",
       "8382  Ord_2658   Prod_3  SHP_3636  Cust_1006   120.9800      0.00   \n",
       "8383  Ord_2722   Prod_1  SHP_3731  Cust_1006  3508.3300      0.04   \n",
       "8384  Ord_4620   Prod_3  SHP_6435  Cust_1577    59.6200      0.04   \n",
       "8385  Ord_1833   Prod_3  SHP_2527   Cust_637   611.1600      0.04   \n",
       "8386  Ord_2324   Prod_7  SHP_3189   Cust_851   121.8700      0.07   \n",
       "8387  Ord_2220   Prod_3  SHP_3019   Cust_851    41.0600      0.04   \n",
       "8388  Ord_4424   Prod_1  SHP_6165  Cust_1519   994.0400      0.03   \n",
       "8389  Ord_4444  Prod_13  SHP_6192  Cust_1519   159.4100      0.00   \n",
       "\n",
       "      Order_Quantity   Profit  Shipping_Cost  Product_Base_Margin  \\\n",
       "0                 23   -30.51           3.60                 0.56   \n",
       "1                 13     4.56           0.93                 0.54   \n",
       "2                 26  1148.90           2.50                 0.59   \n",
       "3                 43   729.34          14.30                 0.37   \n",
       "4                 35  1219.87          26.30                 0.38   \n",
       "5                 23   -47.64           6.15                 0.37   \n",
       "6                  5     1.32           0.50                 0.36   \n",
       "45                 1    -1.36           0.99                 0.37   \n",
       "46                 4    28.81          11.79                 0.42   \n",
       "47                26   435.11          14.30                 0.37   \n",
       "48                14    28.11           0.50                 0.38   \n",
       "49                23    36.32           5.30                 0.46   \n",
       "50                14   -44.47           6.60                 0.49   \n",
       "51                10   -97.20           3.90                 0.55   \n",
       "52                 1    -1.78           0.70                 0.56   \n",
       "53                11   -47.01          19.99                 0.38   \n",
       "54                32   344.13           8.99                 0.59   \n",
       "55                47  -158.58           7.96                 0.49   \n",
       "56                42   129.33           5.00                 0.49   \n",
       "57                34  1547.78           7.07                 0.59   \n",
       "58                 1   -22.82          14.30                 0.37   \n",
       "59                 5  -254.78           8.99                 0.58   \n",
       "60                29    42.16           0.50                 0.38   \n",
       "61                10   -46.83           8.99                 0.59   \n",
       "62                44   489.14           8.74                 0.40   \n",
       "63                 3    -4.28           1.57                 0.59   \n",
       "64                46  2027.68           2.50                 0.59   \n",
       "65                 3   -10.58           5.20                 0.36   \n",
       "66                12  -762.44          80.20                 0.71   \n",
       "67                30   -71.05           6.96                 0.50   \n",
       "...              ...      ...            ...                  ...   \n",
       "8351               9  -198.80          64.73                 0.56   \n",
       "8352               5   -22.04           7.15                 0.36   \n",
       "8353               7   -26.29           5.81                 0.60   \n",
       "8354              25   384.01           7.69                 0.58   \n",
       "8355              46   -71.98           9.44                 0.39   \n",
       "8356               2   -23.62           7.74                 0.50   \n",
       "8357               3 -2213.75          24.49                 0.50   \n",
       "8358              26   147.08           5.97                 0.38   \n",
       "8359              17   187.37           2.99                 0.35   \n",
       "8360              35  -465.66          36.61                 0.61   \n",
       "8370              20   -17.75           2.03                 0.57   \n",
       "8371              28  1049.54           8.99                 0.58   \n",
       "8372               7    12.64           1.39                 0.36   \n",
       "8373              30   -31.95           1.32                 0.83   \n",
       "8374              14  -256.93          48.20                 0.74   \n",
       "8375              47   226.53          11.63                 0.37   \n",
       "8376              36   -27.99           6.50                 0.79   \n",
       "8377              12    10.58           0.50                 0.39   \n",
       "8378              20   312.52           3.50                 0.59   \n",
       "8379              41    69.31           8.99                 0.50   \n",
       "8380              45  -143.58           7.37                 0.37   \n",
       "8381              25   561.13           8.99                 0.59   \n",
       "8382              28   -92.85           5.34                 0.38   \n",
       "8383              21  -546.98          35.00                 0.85   \n",
       "8384              10   -56.30           7.78                 0.37   \n",
       "8385              46   100.22           4.98                 0.40   \n",
       "8386              39    11.32           1.35                 0.40   \n",
       "8387               4   -16.39           6.28                 0.35   \n",
       "8388              10  -335.06          35.00                  NaN   \n",
       "8389              44    34.68           0.98                 0.52   \n",
       "\n",
       "      Customer_Name          Province    Region Customer_Segment  \n",
       "0     AARON BERGMAN           ALBERTA      WEST        CORPORATE  \n",
       "1     AARON BERGMAN           ALBERTA      WEST        CORPORATE  \n",
       "2     AARON BERGMAN           ALBERTA      WEST        CORPORATE  \n",
       "3     AARON BERGMAN           ALBERTA      WEST        CORPORATE  \n",
       "4     AARON BERGMAN           ALBERTA      WEST        CORPORATE  \n",
       "5     AARON BERGMAN           ALBERTA      WEST        CORPORATE  \n",
       "6     AARON BERGMAN           NUNAVUT   NUNAVUT        CORPORATE  \n",
       "45        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "46        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "47        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "48        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "49        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "50        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "51        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "52        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "53        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "54        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "55        ADAM HART  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "56        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "57        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "58        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "59        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "60        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "61        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "62        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "63        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "64        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "65        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "66        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "67        ADAM HART             YUKON     YUKON        CORPORATE  \n",
       "...             ...               ...       ...              ...  \n",
       "8351  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8352  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8353  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8354  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8355  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8356  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8357  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8358  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8359  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8360  WILLIAM BROWN       SASKACHEWAN    PRARIE        CORPORATE  \n",
       "8370   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8371   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8372   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8373   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8374   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8375   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8376   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8377   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8378   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8379   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8380   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8381   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8382   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8383   XYLONA PRICE           ONTARIO   ONTARIO        CORPORATE  \n",
       "8384  YANA SORENSEN  BRITISH COLUMBIA      WEST        CORPORATE  \n",
       "8385  YANA SORENSEN      NEWFOUNDLAND  ATLANTIC        CORPORATE  \n",
       "8386  YANA SORENSEN            QUEBEC    QUEBEC        CORPORATE  \n",
       "8387  YANA SORENSEN            QUEBEC    QUEBEC        CORPORATE  \n",
       "8388  YANA SORENSEN             YUKON     YUKON        CORPORATE  \n",
       "8389  YANA SORENSEN             YUKON     YUKON        CORPORATE  \n",
       "\n",
       "[3076 rows x 14 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now, you can subset the orders made by customers from 'Corporate' segment\n",
    "df_1.loc[df_1['Customer_Segment'] == 'CORPORATE', :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Ord_id</th>\n",
       "      <th>Prod_id</th>\n",
       "      <th>Ship_id</th>\n",
       "      <th>Cust_id</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Shipping_Cost</th>\n",
       "      <th>Product_Base_Margin</th>\n",
       "      <th>Customer_Name</th>\n",
       "      <th>Province</th>\n",
       "      <th>Region</th>\n",
       "      <th>Customer_Segment</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Product_Sub_Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7609</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>136.81</td>\n",
       "      <td>0.01</td>\n",
       "      <td>23</td>\n",
       "      <td>-30.51</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.56</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ord_2978</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_4112</td>\n",
       "      <td>Cust_1088</td>\n",
       "      <td>305.05</td>\n",
       "      <td>0.04</td>\n",
       "      <td>27</td>\n",
       "      <td>23.12</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.57</td>\n",
       "      <td>AARON HAWKINS</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>HOME OFFICE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ord_5484</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7663</td>\n",
       "      <td>Cust_1820</td>\n",
       "      <td>322.82</td>\n",
       "      <td>0.05</td>\n",
       "      <td>35</td>\n",
       "      <td>-17.58</td>\n",
       "      <td>3.98</td>\n",
       "      <td>0.56</td>\n",
       "      <td>ADRIAN SHAMI</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CONSUMER</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ord_3730</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_5175</td>\n",
       "      <td>Cust_1314</td>\n",
       "      <td>459.08</td>\n",
       "      <td>0.04</td>\n",
       "      <td>34</td>\n",
       "      <td>61.57</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.60</td>\n",
       "      <td>ALEKSANDRA GANNAWAY</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ord_4143</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_5771</td>\n",
       "      <td>Cust_1417</td>\n",
       "      <td>207.21</td>\n",
       "      <td>0.06</td>\n",
       "      <td>24</td>\n",
       "      <td>-78.64</td>\n",
       "      <td>6.14</td>\n",
       "      <td>0.59</td>\n",
       "      <td>ALLEN ARMOLD</td>\n",
       "      <td>NEW BRUNSWICK</td>\n",
       "      <td>ATLANTIC</td>\n",
       "      <td>HOME OFFICE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ord_id  Prod_id   Ship_id    Cust_id   Sales  Discount  Order_Quantity  \\\n",
       "0  Ord_5446  Prod_16  SHP_7609  Cust_1818  136.81      0.01              23   \n",
       "1  Ord_2978  Prod_16  SHP_4112  Cust_1088  305.05      0.04              27   \n",
       "2  Ord_5484  Prod_16  SHP_7663  Cust_1820  322.82      0.05              35   \n",
       "3  Ord_3730  Prod_16  SHP_5175  Cust_1314  459.08      0.04              34   \n",
       "4  Ord_4143  Prod_16  SHP_5771  Cust_1417  207.21      0.06              24   \n",
       "\n",
       "   Profit  Shipping_Cost  Product_Base_Margin        Customer_Name  \\\n",
       "0  -30.51           3.60                 0.56        AARON BERGMAN   \n",
       "1   23.12           3.37                 0.57        AARON HAWKINS   \n",
       "2  -17.58           3.98                 0.56         ADRIAN SHAMI   \n",
       "3   61.57           3.14                 0.60  ALEKSANDRA GANNAWAY   \n",
       "4  -78.64           6.14                 0.59         ALLEN ARMOLD   \n",
       "\n",
       "        Province    Region Customer_Segment Product_Category  \\\n",
       "0        ALBERTA      WEST        CORPORATE  OFFICE SUPPLIES   \n",
       "1        ONTARIO   ONTARIO      HOME OFFICE  OFFICE SUPPLIES   \n",
       "2        ALBERTA      WEST         CONSUMER  OFFICE SUPPLIES   \n",
       "3    SASKACHEWAN    PRARIE        CORPORATE  OFFICE SUPPLIES   \n",
       "4  NEW BRUNSWICK  ATLANTIC      HOME OFFICE  OFFICE SUPPLIES   \n",
       "\n",
       "            Product_Sub_Category  \n",
       "0  SCISSORS, RULERS AND TRIMMERS  \n",
       "1  SCISSORS, RULERS AND TRIMMERS  \n",
       "2  SCISSORS, RULERS AND TRIMMERS  \n",
       "3  SCISSORS, RULERS AND TRIMMERS  \n",
       "4  SCISSORS, RULERS AND TRIMMERS  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example 2: Select all orders from product category = office supplies and from the corporate segment\n",
    "# We now need to merge the product_df\n",
    "\n",
    "df_2 = pd.merge(df_1, product_df, how='inner', on='Prod_id')\n",
    "df_2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Ord_id</th>\n",
       "      <th>Prod_id</th>\n",
       "      <th>Ship_id</th>\n",
       "      <th>Cust_id</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Shipping_Cost</th>\n",
       "      <th>Product_Base_Margin</th>\n",
       "      <th>Customer_Name</th>\n",
       "      <th>Province</th>\n",
       "      <th>Region</th>\n",
       "      <th>Customer_Segment</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Product_Sub_Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7609</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>136.81</td>\n",
       "      <td>0.01</td>\n",
       "      <td>23</td>\n",
       "      <td>-30.51</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.56</td>\n",
       "      <td>AARON BERGMAN</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ord_3730</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_5175</td>\n",
       "      <td>Cust_1314</td>\n",
       "      <td>459.08</td>\n",
       "      <td>0.04</td>\n",
       "      <td>34</td>\n",
       "      <td>61.57</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.60</td>\n",
       "      <td>ALEKSANDRA GANNAWAY</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Ord_4506</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_6273</td>\n",
       "      <td>Cust_1544</td>\n",
       "      <td>92.02</td>\n",
       "      <td>0.07</td>\n",
       "      <td>9</td>\n",
       "      <td>-24.88</td>\n",
       "      <td>4.68</td>\n",
       "      <td>0.59</td>\n",
       "      <td>AMY COX</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Ord_1551</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_2145</td>\n",
       "      <td>Cust_531</td>\n",
       "      <td>184.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>29</td>\n",
       "      <td>-71.96</td>\n",
       "      <td>5.30</td>\n",
       "      <td>0.55</td>\n",
       "      <td>ANDY YOTOV</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ord_1429</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_1976</td>\n",
       "      <td>Cust_510</td>\n",
       "      <td>539.06</td>\n",
       "      <td>0.05</td>\n",
       "      <td>42</td>\n",
       "      <td>-123.07</td>\n",
       "      <td>4.59</td>\n",
       "      <td>0.82</td>\n",
       "      <td>ANNA HABERLIN</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Ord_43</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_56</td>\n",
       "      <td>Cust_34</td>\n",
       "      <td>9620.82</td>\n",
       "      <td>0.04</td>\n",
       "      <td>6</td>\n",
       "      <td>-1759.58</td>\n",
       "      <td>24.49</td>\n",
       "      <td>0.81</td>\n",
       "      <td>BARRY WEIRICH</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>NUNAVUT</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Ord_956</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_1324</td>\n",
       "      <td>Cust_346</td>\n",
       "      <td>503.17</td>\n",
       "      <td>0.01</td>\n",
       "      <td>46</td>\n",
       "      <td>-10.21</td>\n",
       "      <td>4.68</td>\n",
       "      <td>0.59</td>\n",
       "      <td>BART WATTERS</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Ord_975</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_1345</td>\n",
       "      <td>Cust_346</td>\n",
       "      <td>638.91</td>\n",
       "      <td>0.02</td>\n",
       "      <td>49</td>\n",
       "      <td>77.48</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.60</td>\n",
       "      <td>BART WATTERS</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Ord_208</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_284</td>\n",
       "      <td>Cust_67</td>\n",
       "      <td>327.15</td>\n",
       "      <td>0.04</td>\n",
       "      <td>19</td>\n",
       "      <td>47.30</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.56</td>\n",
       "      <td>BETH THOMPSON</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Ord_1154</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_1590</td>\n",
       "      <td>Cust_444</td>\n",
       "      <td>483.64</td>\n",
       "      <td>0.10</td>\n",
       "      <td>45</td>\n",
       "      <td>28.39</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.57</td>\n",
       "      <td>BILL DONATELLI</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Ord_1486</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_2052</td>\n",
       "      <td>Cust_513</td>\n",
       "      <td>487.50</td>\n",
       "      <td>0.05</td>\n",
       "      <td>46</td>\n",
       "      <td>-25.88</td>\n",
       "      <td>4.68</td>\n",
       "      <td>0.59</td>\n",
       "      <td>BILL STEWART</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Ord_1793</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_2484</td>\n",
       "      <td>Cust_826</td>\n",
       "      <td>482.93</td>\n",
       "      <td>0.06</td>\n",
       "      <td>34</td>\n",
       "      <td>-67.59</td>\n",
       "      <td>7.59</td>\n",
       "      <td>0.56</td>\n",
       "      <td>CARLOS MEADOR</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Ord_1005</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_1392</td>\n",
       "      <td>Cust_377</td>\n",
       "      <td>15.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1</td>\n",
       "      <td>-11.02</td>\n",
       "      <td>8.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>CHAD SIEVERT</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Ord_278</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_377</td>\n",
       "      <td>Cust_97</td>\n",
       "      <td>302.20</td>\n",
       "      <td>0.04</td>\n",
       "      <td>27</td>\n",
       "      <td>20.27</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.57</td>\n",
       "      <td>CHARLES MCCROSSIN</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Ord_5062</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7068</td>\n",
       "      <td>Cust_1720</td>\n",
       "      <td>587.71</td>\n",
       "      <td>0.09</td>\n",
       "      <td>49</td>\n",
       "      <td>26.28</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.60</td>\n",
       "      <td>CHUCK CLARK</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Ord_4331</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_6038</td>\n",
       "      <td>Cust_1441</td>\n",
       "      <td>77.43</td>\n",
       "      <td>0.01</td>\n",
       "      <td>36</td>\n",
       "      <td>-60.07</td>\n",
       "      <td>2.56</td>\n",
       "      <td>0.55</td>\n",
       "      <td>CINDY CHAPMAN</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Ord_195</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_264</td>\n",
       "      <td>Cust_106</td>\n",
       "      <td>110.32</td>\n",
       "      <td>0.09</td>\n",
       "      <td>31</td>\n",
       "      <td>-32.65</td>\n",
       "      <td>1.32</td>\n",
       "      <td>0.83</td>\n",
       "      <td>CINDY SCHNELLING</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Ord_4864</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_6786</td>\n",
       "      <td>Cust_1679</td>\n",
       "      <td>114.53</td>\n",
       "      <td>0.07</td>\n",
       "      <td>21</td>\n",
       "      <td>-39.23</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.56</td>\n",
       "      <td>CYNTHIA DELANEY</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Ord_4905</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_6842</td>\n",
       "      <td>Cust_1679</td>\n",
       "      <td>348.92</td>\n",
       "      <td>0.06</td>\n",
       "      <td>31</td>\n",
       "      <td>28.47</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.57</td>\n",
       "      <td>CYNTHIA DELANEY</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Ord_1624</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_2243</td>\n",
       "      <td>Cust_525</td>\n",
       "      <td>452.15</td>\n",
       "      <td>0.06</td>\n",
       "      <td>42</td>\n",
       "      <td>25.79</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.57</td>\n",
       "      <td>DAN LAWERA</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Ord_231</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_320</td>\n",
       "      <td>Cust_79</td>\n",
       "      <td>224.47</td>\n",
       "      <td>0.08</td>\n",
       "      <td>16</td>\n",
       "      <td>-49.31</td>\n",
       "      <td>7.59</td>\n",
       "      <td>0.56</td>\n",
       "      <td>DOROTHY WARDLE</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Ord_2547</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_3486</td>\n",
       "      <td>Cust_974</td>\n",
       "      <td>98.24</td>\n",
       "      <td>0.04</td>\n",
       "      <td>9</td>\n",
       "      <td>-10.38</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.57</td>\n",
       "      <td>DORRIS LOVE</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Ord_213</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_294</td>\n",
       "      <td>Cust_49</td>\n",
       "      <td>42.89</td>\n",
       "      <td>0.02</td>\n",
       "      <td>5</td>\n",
       "      <td>-32.48</td>\n",
       "      <td>8.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>DOUG BICKFORD</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Ord_488</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_656</td>\n",
       "      <td>Cust_179</td>\n",
       "      <td>134.86</td>\n",
       "      <td>0.04</td>\n",
       "      <td>42</td>\n",
       "      <td>-62.84</td>\n",
       "      <td>1.92</td>\n",
       "      <td>0.84</td>\n",
       "      <td>ERICA BERN</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Ord_1499</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_2071</td>\n",
       "      <td>Cust_487</td>\n",
       "      <td>248.42</td>\n",
       "      <td>0.02</td>\n",
       "      <td>35</td>\n",
       "      <td>-58.81</td>\n",
       "      <td>4.42</td>\n",
       "      <td>0.58</td>\n",
       "      <td>ERIN CREIGHTON</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Ord_2350</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_3226</td>\n",
       "      <td>Cust_941</td>\n",
       "      <td>67.30</td>\n",
       "      <td>0.02</td>\n",
       "      <td>27</td>\n",
       "      <td>-115.38</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0.81</td>\n",
       "      <td>FRED CHUNG</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Ord_487</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_655</td>\n",
       "      <td>Cust_164</td>\n",
       "      <td>343.26</td>\n",
       "      <td>0.04</td>\n",
       "      <td>50</td>\n",
       "      <td>-287.28</td>\n",
       "      <td>8.37</td>\n",
       "      <td>0.58</td>\n",
       "      <td>GUY ARMSTRONG</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Ord_363</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_482</td>\n",
       "      <td>Cust_145</td>\n",
       "      <td>63.02</td>\n",
       "      <td>0.07</td>\n",
       "      <td>27</td>\n",
       "      <td>-119.66</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0.81</td>\n",
       "      <td>HILARY HOLDEN</td>\n",
       "      <td>PRINCE EDWARD ISLAND</td>\n",
       "      <td>ATLANTIC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>Ord_175</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_238</td>\n",
       "      <td>Cust_104</td>\n",
       "      <td>501.31</td>\n",
       "      <td>0.05</td>\n",
       "      <td>40</td>\n",
       "      <td>38.23</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.60</td>\n",
       "      <td>JEREMY LONSDALE</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Ord_834</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_1142</td>\n",
       "      <td>Cust_269</td>\n",
       "      <td>5.06</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1</td>\n",
       "      <td>-2.64</td>\n",
       "      <td>1.92</td>\n",
       "      <td>0.84</td>\n",
       "      <td>JOHN GRADY</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7467</th>\n",
       "      <td>Ord_4728</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6596</td>\n",
       "      <td>Cust_1607</td>\n",
       "      <td>373.13</td>\n",
       "      <td>0.05</td>\n",
       "      <td>33</td>\n",
       "      <td>-35.26</td>\n",
       "      <td>5.03</td>\n",
       "      <td>0.59</td>\n",
       "      <td>ROLAND FJELD</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7469</th>\n",
       "      <td>Ord_2097</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_2869</td>\n",
       "      <td>Cust_800</td>\n",
       "      <td>2040.95</td>\n",
       "      <td>0.07</td>\n",
       "      <td>42</td>\n",
       "      <td>-1231.87</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.83</td>\n",
       "      <td>ROSS DEVINCENTIS</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7470</th>\n",
       "      <td>Ord_2171</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_2959</td>\n",
       "      <td>Cust_800</td>\n",
       "      <td>302.91</td>\n",
       "      <td>0.05</td>\n",
       "      <td>24</td>\n",
       "      <td>-36.76</td>\n",
       "      <td>6.13</td>\n",
       "      <td>0.57</td>\n",
       "      <td>ROSS DEVINCENTIS</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7471</th>\n",
       "      <td>Ord_4004</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_5575</td>\n",
       "      <td>Cust_1375</td>\n",
       "      <td>236.46</td>\n",
       "      <td>0.05</td>\n",
       "      <td>23</td>\n",
       "      <td>-134.31</td>\n",
       "      <td>9.45</td>\n",
       "      <td>0.60</td>\n",
       "      <td>ROY COLLINS</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7472</th>\n",
       "      <td>Ord_3286</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_4560</td>\n",
       "      <td>Cust_1194</td>\n",
       "      <td>7156.56</td>\n",
       "      <td>0.03</td>\n",
       "      <td>50</td>\n",
       "      <td>1871.26</td>\n",
       "      <td>19.99</td>\n",
       "      <td>0.56</td>\n",
       "      <td>ROY SKARIA</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7473</th>\n",
       "      <td>Ord_1531</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_2118</td>\n",
       "      <td>Cust_537</td>\n",
       "      <td>1025.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>30</td>\n",
       "      <td>87.03</td>\n",
       "      <td>8.74</td>\n",
       "      <td>0.61</td>\n",
       "      <td>RUBEN AUSMAN</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7475</th>\n",
       "      <td>Ord_571</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_1160</td>\n",
       "      <td>Cust_280</td>\n",
       "      <td>195.04</td>\n",
       "      <td>0.08</td>\n",
       "      <td>1</td>\n",
       "      <td>-149.41</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.85</td>\n",
       "      <td>SALLY KNUTSON</td>\n",
       "      <td>NOVA SCOTIA</td>\n",
       "      <td>ATLANTIC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7481</th>\n",
       "      <td>Ord_1778</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_2465</td>\n",
       "      <td>Cust_587</td>\n",
       "      <td>669.69</td>\n",
       "      <td>0.03</td>\n",
       "      <td>8</td>\n",
       "      <td>-297.02</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.81</td>\n",
       "      <td>SCOT CORAM</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7484</th>\n",
       "      <td>Ord_994</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_1375</td>\n",
       "      <td>Cust_369</td>\n",
       "      <td>11103.75</td>\n",
       "      <td>0.10</td>\n",
       "      <td>32</td>\n",
       "      <td>-522.59</td>\n",
       "      <td>99.00</td>\n",
       "      <td>0.65</td>\n",
       "      <td>SEAN WENDT</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7488</th>\n",
       "      <td>Ord_696</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_953</td>\n",
       "      <td>Cust_232</td>\n",
       "      <td>309.62</td>\n",
       "      <td>0.00</td>\n",
       "      <td>21</td>\n",
       "      <td>-80.20</td>\n",
       "      <td>9.37</td>\n",
       "      <td>0.56</td>\n",
       "      <td>SHAHID SHARIARI</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7489</th>\n",
       "      <td>Ord_4984</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6957</td>\n",
       "      <td>Cust_1701</td>\n",
       "      <td>298.11</td>\n",
       "      <td>0.08</td>\n",
       "      <td>25</td>\n",
       "      <td>-60.79</td>\n",
       "      <td>6.27</td>\n",
       "      <td>0.57</td>\n",
       "      <td>SHAUN CHANCE</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7490</th>\n",
       "      <td>Ord_5021</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_7006</td>\n",
       "      <td>Cust_1701</td>\n",
       "      <td>192.02</td>\n",
       "      <td>0.09</td>\n",
       "      <td>7</td>\n",
       "      <td>-293.74</td>\n",
       "      <td>53.03</td>\n",
       "      <td>0.78</td>\n",
       "      <td>SHAUN CHANCE</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7492</th>\n",
       "      <td>Ord_2559</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_3504</td>\n",
       "      <td>Cust_988</td>\n",
       "      <td>1200.70</td>\n",
       "      <td>0.06</td>\n",
       "      <td>47</td>\n",
       "      <td>-37.27</td>\n",
       "      <td>8.79</td>\n",
       "      <td>0.66</td>\n",
       "      <td>SHIRLEY DANIELS</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7493</th>\n",
       "      <td>Ord_2248</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_3056</td>\n",
       "      <td>Cust_879</td>\n",
       "      <td>241.89</td>\n",
       "      <td>0.02</td>\n",
       "      <td>15</td>\n",
       "      <td>-83.30</td>\n",
       "      <td>10.68</td>\n",
       "      <td>0.58</td>\n",
       "      <td>SHIRLEY JACKSON</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7496</th>\n",
       "      <td>Ord_5221</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_7294</td>\n",
       "      <td>Cust_1741</td>\n",
       "      <td>135.38</td>\n",
       "      <td>0.05</td>\n",
       "      <td>17</td>\n",
       "      <td>-71.12</td>\n",
       "      <td>6.50</td>\n",
       "      <td>0.59</td>\n",
       "      <td>SONIA COOLEY</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7497</th>\n",
       "      <td>Ord_615</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_842</td>\n",
       "      <td>Cust_214</td>\n",
       "      <td>4538.66</td>\n",
       "      <td>0.00</td>\n",
       "      <td>40</td>\n",
       "      <td>506.86</td>\n",
       "      <td>8.64</td>\n",
       "      <td>0.78</td>\n",
       "      <td>SONIA SUNLEY</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7498</th>\n",
       "      <td>Ord_2198</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_2996</td>\n",
       "      <td>Cust_829</td>\n",
       "      <td>1610.76</td>\n",
       "      <td>0.10</td>\n",
       "      <td>38</td>\n",
       "      <td>-8.67</td>\n",
       "      <td>16.36</td>\n",
       "      <td>0.55</td>\n",
       "      <td>SPEROS GORANITIS</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>QUEBEC</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7500</th>\n",
       "      <td>Ord_3127</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_4340</td>\n",
       "      <td>Cust_1162</td>\n",
       "      <td>1724.82</td>\n",
       "      <td>0.10</td>\n",
       "      <td>32</td>\n",
       "      <td>407.80</td>\n",
       "      <td>5.08</td>\n",
       "      <td>0.59</td>\n",
       "      <td>STEVE CHAPMAN</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7507</th>\n",
       "      <td>Ord_199</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_272</td>\n",
       "      <td>Cust_107</td>\n",
       "      <td>456.91</td>\n",
       "      <td>0.04</td>\n",
       "      <td>28</td>\n",
       "      <td>-328.18</td>\n",
       "      <td>17.78</td>\n",
       "      <td>0.59</td>\n",
       "      <td>SUSAN VITTORINI</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>NORTHWEST TERRITORIES</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7510</th>\n",
       "      <td>Ord_5014</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6996</td>\n",
       "      <td>Cust_1698</td>\n",
       "      <td>431.11</td>\n",
       "      <td>0.07</td>\n",
       "      <td>4</td>\n",
       "      <td>-244.33</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.82</td>\n",
       "      <td>TAMARA MANNING</td>\n",
       "      <td>ALBERTA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7513</th>\n",
       "      <td>Ord_3333</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_4626</td>\n",
       "      <td>Cust_1196</td>\n",
       "      <td>1243.45</td>\n",
       "      <td>0.10</td>\n",
       "      <td>39</td>\n",
       "      <td>-1212.55</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.81</td>\n",
       "      <td>TANJA NORVELL</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7520</th>\n",
       "      <td>Ord_4549</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6332</td>\n",
       "      <td>Cust_1530</td>\n",
       "      <td>297.85</td>\n",
       "      <td>0.04</td>\n",
       "      <td>5</td>\n",
       "      <td>-69.89</td>\n",
       "      <td>19.99</td>\n",
       "      <td>0.59</td>\n",
       "      <td>TIM TASLIMI</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7529</th>\n",
       "      <td>Ord_4758</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6637</td>\n",
       "      <td>Cust_1638</td>\n",
       "      <td>448.10</td>\n",
       "      <td>0.10</td>\n",
       "      <td>35</td>\n",
       "      <td>-15.07</td>\n",
       "      <td>4.51</td>\n",
       "      <td>0.59</td>\n",
       "      <td>TONY MOLINARI</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7540</th>\n",
       "      <td>Ord_3300</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_4578</td>\n",
       "      <td>Cust_1180</td>\n",
       "      <td>312.25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>9</td>\n",
       "      <td>15.56</td>\n",
       "      <td>5.10</td>\n",
       "      <td>0.60</td>\n",
       "      <td>VALERIE DOMINGUEZ</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7541</th>\n",
       "      <td>Ord_3339</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_4632</td>\n",
       "      <td>Cust_1180</td>\n",
       "      <td>257.41</td>\n",
       "      <td>0.09</td>\n",
       "      <td>43</td>\n",
       "      <td>-131.08</td>\n",
       "      <td>4.69</td>\n",
       "      <td>0.68</td>\n",
       "      <td>VALERIE DOMINGUEZ</td>\n",
       "      <td>MANITOBA</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7545</th>\n",
       "      <td>Ord_4629</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6447</td>\n",
       "      <td>Cust_1587</td>\n",
       "      <td>848.19</td>\n",
       "      <td>0.06</td>\n",
       "      <td>25</td>\n",
       "      <td>120.02</td>\n",
       "      <td>5.49</td>\n",
       "      <td>0.60</td>\n",
       "      <td>VICTORIA PISTEKA</td>\n",
       "      <td>BRITISH COLUMBIA</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7546</th>\n",
       "      <td>Ord_4604</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6403</td>\n",
       "      <td>Cust_1522</td>\n",
       "      <td>234.24</td>\n",
       "      <td>0.09</td>\n",
       "      <td>24</td>\n",
       "      <td>-151.80</td>\n",
       "      <td>9.45</td>\n",
       "      <td>0.60</td>\n",
       "      <td>VICTORIA PISTEKA</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7551</th>\n",
       "      <td>Ord_3543</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_4905</td>\n",
       "      <td>Cust_1266</td>\n",
       "      <td>1184.11</td>\n",
       "      <td>0.07</td>\n",
       "      <td>6</td>\n",
       "      <td>-145.07</td>\n",
       "      <td>19.99</td>\n",
       "      <td>0.71</td>\n",
       "      <td>WILLIAM BROWN</td>\n",
       "      <td>SASKACHEWAN</td>\n",
       "      <td>PRARIE</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7552</th>\n",
       "      <td>Ord_2722</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_3731</td>\n",
       "      <td>Cust_1006</td>\n",
       "      <td>3508.33</td>\n",
       "      <td>0.04</td>\n",
       "      <td>21</td>\n",
       "      <td>-546.98</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.85</td>\n",
       "      <td>XYLONA PRICE</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7553</th>\n",
       "      <td>Ord_4424</td>\n",
       "      <td>Prod_1</td>\n",
       "      <td>SHP_6165</td>\n",
       "      <td>Cust_1519</td>\n",
       "      <td>994.04</td>\n",
       "      <td>0.03</td>\n",
       "      <td>10</td>\n",
       "      <td>-335.06</td>\n",
       "      <td>35.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>YANA SORENSEN</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>YUKON</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>STORAGE &amp; ORGANIZATION</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1680 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ord_id  Prod_id   Ship_id    Cust_id     Sales  Discount  \\\n",
       "0     Ord_5446  Prod_16  SHP_7609  Cust_1818    136.81      0.01   \n",
       "3     Ord_3730  Prod_16  SHP_5175  Cust_1314    459.08      0.04   \n",
       "7     Ord_4506  Prod_16  SHP_6273  Cust_1544     92.02      0.07   \n",
       "9     Ord_1551  Prod_16  SHP_2145   Cust_531    184.77      0.00   \n",
       "11    Ord_1429  Prod_16  SHP_1976   Cust_510    539.06      0.05   \n",
       "14      Ord_43  Prod_16    SHP_56    Cust_34   9620.82      0.04   \n",
       "15     Ord_956  Prod_16  SHP_1324   Cust_346    503.17      0.01   \n",
       "16     Ord_975  Prod_16  SHP_1345   Cust_346    638.91      0.02   \n",
       "21     Ord_208  Prod_16   SHP_284    Cust_67    327.15      0.04   \n",
       "22    Ord_1154  Prod_16  SHP_1590   Cust_444    483.64      0.10   \n",
       "23    Ord_1486  Prod_16  SHP_2052   Cust_513    487.50      0.05   \n",
       "27    Ord_1793  Prod_16  SHP_2484   Cust_826    482.93      0.06   \n",
       "30    Ord_1005  Prod_16  SHP_1392   Cust_377     15.00      0.05   \n",
       "31     Ord_278  Prod_16   SHP_377    Cust_97    302.20      0.04   \n",
       "35    Ord_5062  Prod_16  SHP_7068  Cust_1720    587.71      0.09   \n",
       "36    Ord_4331  Prod_16  SHP_6038  Cust_1441     77.43      0.01   \n",
       "37     Ord_195  Prod_16   SHP_264   Cust_106    110.32      0.09   \n",
       "40    Ord_4864  Prod_16  SHP_6786  Cust_1679    114.53      0.07   \n",
       "41    Ord_4905  Prod_16  SHP_6842  Cust_1679    348.92      0.06   \n",
       "42    Ord_1624  Prod_16  SHP_2243   Cust_525    452.15      0.06   \n",
       "47     Ord_231  Prod_16   SHP_320    Cust_79    224.47      0.08   \n",
       "48    Ord_2547  Prod_16  SHP_3486   Cust_974     98.24      0.04   \n",
       "49     Ord_213  Prod_16   SHP_294    Cust_49     42.89      0.02   \n",
       "55     Ord_488  Prod_16   SHP_656   Cust_179    134.86      0.04   \n",
       "58    Ord_1499  Prod_16  SHP_2071   Cust_487    248.42      0.02   \n",
       "61    Ord_2350  Prod_16  SHP_3226   Cust_941     67.30      0.02   \n",
       "63     Ord_487  Prod_16   SHP_655   Cust_164    343.26      0.04   \n",
       "65     Ord_363  Prod_16   SHP_482   Cust_145     63.02      0.07   \n",
       "72     Ord_175  Prod_16   SHP_238   Cust_104    501.31      0.05   \n",
       "74     Ord_834  Prod_16  SHP_1142   Cust_269      5.06      0.01   \n",
       "...        ...      ...       ...        ...       ...       ...   \n",
       "7467  Ord_4728   Prod_1  SHP_6596  Cust_1607    373.13      0.05   \n",
       "7469  Ord_2097   Prod_1  SHP_2869   Cust_800   2040.95      0.07   \n",
       "7470  Ord_2171   Prod_1  SHP_2959   Cust_800    302.91      0.05   \n",
       "7471  Ord_4004   Prod_1  SHP_5575  Cust_1375    236.46      0.05   \n",
       "7472  Ord_3286   Prod_1  SHP_4560  Cust_1194   7156.56      0.03   \n",
       "7473  Ord_1531   Prod_1  SHP_2118   Cust_537   1025.02      0.04   \n",
       "7475   Ord_571   Prod_1  SHP_1160   Cust_280    195.04      0.08   \n",
       "7481  Ord_1778   Prod_1  SHP_2465   Cust_587    669.69      0.03   \n",
       "7484   Ord_994   Prod_1  SHP_1375   Cust_369  11103.75      0.10   \n",
       "7488   Ord_696   Prod_1   SHP_953   Cust_232    309.62      0.00   \n",
       "7489  Ord_4984   Prod_1  SHP_6957  Cust_1701    298.11      0.08   \n",
       "7490  Ord_5021   Prod_1  SHP_7006  Cust_1701    192.02      0.09   \n",
       "7492  Ord_2559   Prod_1  SHP_3504   Cust_988   1200.70      0.06   \n",
       "7493  Ord_2248   Prod_1  SHP_3056   Cust_879    241.89      0.02   \n",
       "7496  Ord_5221   Prod_1  SHP_7294  Cust_1741    135.38      0.05   \n",
       "7497   Ord_615   Prod_1   SHP_842   Cust_214   4538.66      0.00   \n",
       "7498  Ord_2198   Prod_1  SHP_2996   Cust_829   1610.76      0.10   \n",
       "7500  Ord_3127   Prod_1  SHP_4340  Cust_1162   1724.82      0.10   \n",
       "7507   Ord_199   Prod_1   SHP_272   Cust_107    456.91      0.04   \n",
       "7510  Ord_5014   Prod_1  SHP_6996  Cust_1698    431.11      0.07   \n",
       "7513  Ord_3333   Prod_1  SHP_4626  Cust_1196   1243.45      0.10   \n",
       "7520  Ord_4549   Prod_1  SHP_6332  Cust_1530    297.85      0.04   \n",
       "7529  Ord_4758   Prod_1  SHP_6637  Cust_1638    448.10      0.10   \n",
       "7540  Ord_3300   Prod_1  SHP_4578  Cust_1180    312.25      0.05   \n",
       "7541  Ord_3339   Prod_1  SHP_4632  Cust_1180    257.41      0.09   \n",
       "7545  Ord_4629   Prod_1  SHP_6447  Cust_1587    848.19      0.06   \n",
       "7546  Ord_4604   Prod_1  SHP_6403  Cust_1522    234.24      0.09   \n",
       "7551  Ord_3543   Prod_1  SHP_4905  Cust_1266   1184.11      0.07   \n",
       "7552  Ord_2722   Prod_1  SHP_3731  Cust_1006   3508.33      0.04   \n",
       "7553  Ord_4424   Prod_1  SHP_6165  Cust_1519    994.04      0.03   \n",
       "\n",
       "      Order_Quantity   Profit  Shipping_Cost  Product_Base_Margin  \\\n",
       "0                 23   -30.51           3.60                 0.56   \n",
       "3                 34    61.57           3.14                 0.60   \n",
       "7                  9   -24.88           4.68                 0.59   \n",
       "9                 29   -71.96           5.30                 0.55   \n",
       "11                42  -123.07           4.59                 0.82   \n",
       "14                 6 -1759.58          24.49                 0.81   \n",
       "15                46   -10.21           4.68                 0.59   \n",
       "16                49    77.48           3.14                 0.60   \n",
       "21                19    47.30           3.26                 0.56   \n",
       "22                45    28.39           3.37                 0.57   \n",
       "23                46   -25.88           4.68                 0.59   \n",
       "27                34   -67.59           7.59                 0.56   \n",
       "30                 1   -11.02           8.37                 0.58   \n",
       "31                27    20.27           3.37                 0.57   \n",
       "35                49    26.28           3.14                 0.60   \n",
       "36                36   -60.07           2.56                 0.55   \n",
       "37                31   -32.65           1.32                 0.83   \n",
       "40                21   -39.23           3.60                 0.56   \n",
       "41                31    28.47           3.37                 0.57   \n",
       "42                42    25.79           3.37                 0.57   \n",
       "47                16   -49.31           7.59                 0.56   \n",
       "48                 9   -10.38           3.37                 0.57   \n",
       "49                 5   -32.48           8.37                 0.58   \n",
       "55                42   -62.84           1.92                 0.84   \n",
       "58                35   -58.81           4.42                 0.58   \n",
       "61                27  -115.38           5.00                 0.81   \n",
       "63                50  -287.28           8.37                 0.58   \n",
       "65                27  -119.66           5.00                 0.81   \n",
       "72                40    38.23           3.14                 0.60   \n",
       "74                 1    -2.64           1.92                 0.84   \n",
       "...              ...      ...            ...                  ...   \n",
       "7467              33   -35.26           5.03                 0.59   \n",
       "7469              42 -1231.87          35.00                 0.83   \n",
       "7470              24   -36.76           6.13                 0.57   \n",
       "7471              23  -134.31           9.45                 0.60   \n",
       "7472              50  1871.26          19.99                 0.56   \n",
       "7473              30    87.03           8.74                 0.61   \n",
       "7475               1  -149.41          35.00                 0.85   \n",
       "7481               8  -297.02          35.00                 0.81   \n",
       "7484              32  -522.59          99.00                 0.65   \n",
       "7488              21   -80.20           9.37                 0.56   \n",
       "7489              25   -60.79           6.27                 0.57   \n",
       "7490               7  -293.74          53.03                 0.78   \n",
       "7492              47   -37.27           8.79                 0.66   \n",
       "7493              15   -83.30          10.68                 0.58   \n",
       "7496              17   -71.12           6.50                 0.59   \n",
       "7497              40   506.86           8.64                 0.78   \n",
       "7498              38    -8.67          16.36                 0.55   \n",
       "7500              32   407.80           5.08                 0.59   \n",
       "7507              28  -328.18          17.78                 0.59   \n",
       "7510               4  -244.33          35.00                 0.82   \n",
       "7513              39 -1212.55          35.00                 0.81   \n",
       "7520               5   -69.89          19.99                 0.59   \n",
       "7529              35   -15.07           4.51                 0.59   \n",
       "7540               9    15.56           5.10                 0.60   \n",
       "7541              43  -131.08           4.69                 0.68   \n",
       "7545              25   120.02           5.49                 0.60   \n",
       "7546              24  -151.80           9.45                 0.60   \n",
       "7551               6  -145.07          19.99                 0.71   \n",
       "7552              21  -546.98          35.00                 0.85   \n",
       "7553              10  -335.06          35.00                  NaN   \n",
       "\n",
       "            Customer_Name               Province                 Region  \\\n",
       "0           AARON BERGMAN                ALBERTA                   WEST   \n",
       "3     ALEKSANDRA GANNAWAY            SASKACHEWAN                 PRARIE   \n",
       "7                 AMY COX                  YUKON                  YUKON   \n",
       "9              ANDY YOTOV                ONTARIO                ONTARIO   \n",
       "11          ANNA HABERLIN                ONTARIO                ONTARIO   \n",
       "14          BARRY WEIRICH                NUNAVUT                NUNAVUT   \n",
       "15           BART WATTERS       BRITISH COLUMBIA                   WEST   \n",
       "16           BART WATTERS       BRITISH COLUMBIA                   WEST   \n",
       "21          BETH THOMPSON  NORTHWEST TERRITORIES  NORTHWEST TERRITORIES   \n",
       "22         BILL DONATELLI                ONTARIO                ONTARIO   \n",
       "23           BILL STEWART                ONTARIO                ONTARIO   \n",
       "27          CARLOS MEADOR                 QUEBEC                 QUEBEC   \n",
       "30           CHAD SIEVERT               MANITOBA                 PRARIE   \n",
       "31      CHARLES MCCROSSIN  NORTHWEST TERRITORIES  NORTHWEST TERRITORIES   \n",
       "35            CHUCK CLARK                ALBERTA                   WEST   \n",
       "36          CINDY CHAPMAN                  YUKON                  YUKON   \n",
       "37       CINDY SCHNELLING  NORTHWEST TERRITORIES  NORTHWEST TERRITORIES   \n",
       "40        CYNTHIA DELANEY       BRITISH COLUMBIA                   WEST   \n",
       "41        CYNTHIA DELANEY       BRITISH COLUMBIA                   WEST   \n",
       "42             DAN LAWERA                ONTARIO                ONTARIO   \n",
       "47         DOROTHY WARDLE  NORTHWEST TERRITORIES  NORTHWEST TERRITORIES   \n",
       "48            DORRIS LOVE                 QUEBEC                 QUEBEC   \n",
       "49          DOUG BICKFORD  NORTHWEST TERRITORIES  NORTHWEST TERRITORIES   \n",
       "55             ERICA BERN               MANITOBA                 PRARIE   \n",
       "58         ERIN CREIGHTON                ONTARIO                ONTARIO   \n",
       "61             FRED CHUNG                 QUEBEC                 QUEBEC   \n",
       "63          GUY ARMSTRONG               MANITOBA                 PRARIE   \n",
       "65          HILARY HOLDEN   PRINCE EDWARD ISLAND               ATLANTIC   \n",
       "72        JEREMY LONSDALE  NORTHWEST TERRITORIES  NORTHWEST TERRITORIES   \n",
       "74             JOHN GRADY       BRITISH COLUMBIA                   WEST   \n",
       "...                   ...                    ...                    ...   \n",
       "7467         ROLAND FJELD       BRITISH COLUMBIA                   WEST   \n",
       "7469     ROSS DEVINCENTIS                 QUEBEC                 QUEBEC   \n",
       "7470     ROSS DEVINCENTIS                 QUEBEC                 QUEBEC   \n",
       "7471          ROY COLLINS            SASKACHEWAN                 PRARIE   \n",
       "7472           ROY SKARIA               MANITOBA                 PRARIE   \n",
       "7473         RUBEN AUSMAN                ONTARIO                ONTARIO   \n",
       "7475        SALLY KNUTSON            NOVA SCOTIA               ATLANTIC   \n",
       "7481           SCOT CORAM                ONTARIO                ONTARIO   \n",
       "7484           SEAN WENDT               MANITOBA                 PRARIE   \n",
       "7488      SHAHID SHARIARI       BRITISH COLUMBIA                   WEST   \n",
       "7489         SHAUN CHANCE                ALBERTA                   WEST   \n",
       "7490         SHAUN CHANCE                ALBERTA                   WEST   \n",
       "7492      SHIRLEY DANIELS                 QUEBEC                 QUEBEC   \n",
       "7493      SHIRLEY JACKSON                 QUEBEC                 QUEBEC   \n",
       "7496         SONIA COOLEY                ALBERTA                   WEST   \n",
       "7497         SONIA SUNLEY       BRITISH COLUMBIA                   WEST   \n",
       "7498     SPEROS GORANITIS                 QUEBEC                 QUEBEC   \n",
       "7500        STEVE CHAPMAN               MANITOBA                 PRARIE   \n",
       "7507      SUSAN VITTORINI  NORTHWEST TERRITORIES  NORTHWEST TERRITORIES   \n",
       "7510       TAMARA MANNING                ALBERTA                   WEST   \n",
       "7513        TANJA NORVELL               MANITOBA                 PRARIE   \n",
       "7520          TIM TASLIMI                  YUKON                  YUKON   \n",
       "7529        TONY MOLINARI       BRITISH COLUMBIA                   WEST   \n",
       "7540    VALERIE DOMINGUEZ               MANITOBA                 PRARIE   \n",
       "7541    VALERIE DOMINGUEZ               MANITOBA                 PRARIE   \n",
       "7545     VICTORIA PISTEKA       BRITISH COLUMBIA                   WEST   \n",
       "7546     VICTORIA PISTEKA                  YUKON                  YUKON   \n",
       "7551        WILLIAM BROWN            SASKACHEWAN                 PRARIE   \n",
       "7552         XYLONA PRICE                ONTARIO                ONTARIO   \n",
       "7553        YANA SORENSEN                  YUKON                  YUKON   \n",
       "\n",
       "     Customer_Segment Product_Category           Product_Sub_Category  \n",
       "0           CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "3           CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "7           CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "9           CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "11          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "14          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "15          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "16          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "21          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "22          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "23          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "27          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "30          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "31          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "35          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "36          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "37          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "40          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "41          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "42          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "47          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "48          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "49          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "55          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "58          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "61          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "63          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "65          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "72          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "74          CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS  \n",
       "...               ...              ...                            ...  \n",
       "7467        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7469        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7470        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7471        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7472        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7473        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7475        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7481        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7484        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7488        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7489        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7490        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7492        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7493        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7496        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7497        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7498        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7500        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7507        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7510        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7513        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7520        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7529        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7540        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7541        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7545        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7546        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7551        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7552        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "7553        CORPORATE  OFFICE SUPPLIES         STORAGE & ORGANIZATION  \n",
       "\n",
       "[1680 rows x 16 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select all orders from product category = office supplies and from the corporate segment\n",
    "df_2.loc[(df_2['Product_Category']=='OFFICE SUPPLIES') & (df_2['Customer_Segment']=='CORPORATE'),:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Similary, you can merge the other dimension tables - ```shipping_df``` and ```orders_df``` to create a ```master_df``` and perform indexing using any column in the master dataframe.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8399, 19)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merging shipping_df\n",
    "df_3 = pd.merge(df_2, shipping_df, how='inner', on='Ship_id')\n",
    "df_3.shape"
   ]
  },
  {
   "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>Ord_id</th>\n",
       "      <th>Prod_id</th>\n",
       "      <th>Ship_id</th>\n",
       "      <th>Cust_id</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Shipping_Cost</th>\n",
       "      <th>Product_Base_Margin</th>\n",
       "      <th>...</th>\n",
       "      <th>Region</th>\n",
       "      <th>Customer_Segment</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Product_Sub_Category</th>\n",
       "      <th>Order_ID_x</th>\n",
       "      <th>Ship_Mode</th>\n",
       "      <th>Ship_Date</th>\n",
       "      <th>Order_ID_y</th>\n",
       "      <th>Order_Date</th>\n",
       "      <th>Order_Priority</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7609</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>136.81</td>\n",
       "      <td>0.01</td>\n",
       "      <td>23</td>\n",
       "      <td>-30.51</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.56</td>\n",
       "      <td>...</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "      <td>36262</td>\n",
       "      <td>REGULAR AIR</td>\n",
       "      <td>28-07-2010</td>\n",
       "      <td>36262</td>\n",
       "      <td>27-07-2010</td>\n",
       "      <td>NOT SPECIFIED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_4</td>\n",
       "      <td>SHP_7610</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>4701.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>26</td>\n",
       "      <td>1148.90</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.59</td>\n",
       "      <td>...</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>TECHNOLOGY</td>\n",
       "      <td>TELEPHONES AND COMMUNICATION</td>\n",
       "      <td>36262</td>\n",
       "      <td>EXPRESS AIR</td>\n",
       "      <td>27-07-2010</td>\n",
       "      <td>36262</td>\n",
       "      <td>27-07-2010</td>\n",
       "      <td>NOT SPECIFIED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ord_5446</td>\n",
       "      <td>Prod_6</td>\n",
       "      <td>SHP_7608</td>\n",
       "      <td>Cust_1818</td>\n",
       "      <td>164.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>23</td>\n",
       "      <td>-47.64</td>\n",
       "      <td>6.15</td>\n",
       "      <td>0.37</td>\n",
       "      <td>...</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CORPORATE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>PAPER</td>\n",
       "      <td>36262</td>\n",
       "      <td>EXPRESS AIR</td>\n",
       "      <td>28-07-2010</td>\n",
       "      <td>36262</td>\n",
       "      <td>27-07-2010</td>\n",
       "      <td>NOT SPECIFIED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ord_2978</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_4112</td>\n",
       "      <td>Cust_1088</td>\n",
       "      <td>305.05</td>\n",
       "      <td>0.04</td>\n",
       "      <td>27</td>\n",
       "      <td>23.12</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.57</td>\n",
       "      <td>...</td>\n",
       "      <td>ONTARIO</td>\n",
       "      <td>HOME OFFICE</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "      <td>37863</td>\n",
       "      <td>REGULAR AIR</td>\n",
       "      <td>26-02-2011</td>\n",
       "      <td>37863</td>\n",
       "      <td>24-02-2011</td>\n",
       "      <td>HIGH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ord_5484</td>\n",
       "      <td>Prod_16</td>\n",
       "      <td>SHP_7663</td>\n",
       "      <td>Cust_1820</td>\n",
       "      <td>322.82</td>\n",
       "      <td>0.05</td>\n",
       "      <td>35</td>\n",
       "      <td>-17.58</td>\n",
       "      <td>3.98</td>\n",
       "      <td>0.56</td>\n",
       "      <td>...</td>\n",
       "      <td>WEST</td>\n",
       "      <td>CONSUMER</td>\n",
       "      <td>OFFICE SUPPLIES</td>\n",
       "      <td>SCISSORS, RULERS AND TRIMMERS</td>\n",
       "      <td>53026</td>\n",
       "      <td>REGULAR AIR</td>\n",
       "      <td>03-03-2012</td>\n",
       "      <td>53026</td>\n",
       "      <td>26-02-2012</td>\n",
       "      <td>LOW</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ord_id  Prod_id   Ship_id    Cust_id    Sales  Discount  Order_Quantity  \\\n",
       "0  Ord_5446  Prod_16  SHP_7609  Cust_1818   136.81      0.01              23   \n",
       "1  Ord_5446   Prod_4  SHP_7610  Cust_1818  4701.69      0.00              26   \n",
       "2  Ord_5446   Prod_6  SHP_7608  Cust_1818   164.02      0.03              23   \n",
       "3  Ord_2978  Prod_16  SHP_4112  Cust_1088   305.05      0.04              27   \n",
       "4  Ord_5484  Prod_16  SHP_7663  Cust_1820   322.82      0.05              35   \n",
       "\n",
       "    Profit  Shipping_Cost  Product_Base_Margin       ...         Region  \\\n",
       "0   -30.51           3.60                 0.56       ...           WEST   \n",
       "1  1148.90           2.50                 0.59       ...           WEST   \n",
       "2   -47.64           6.15                 0.37       ...           WEST   \n",
       "3    23.12           3.37                 0.57       ...        ONTARIO   \n",
       "4   -17.58           3.98                 0.56       ...           WEST   \n",
       "\n",
       "  Customer_Segment Product_Category           Product_Sub_Category Order_ID_x  \\\n",
       "0        CORPORATE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS      36262   \n",
       "1        CORPORATE       TECHNOLOGY   TELEPHONES AND COMMUNICATION      36262   \n",
       "2        CORPORATE  OFFICE SUPPLIES                          PAPER      36262   \n",
       "3      HOME OFFICE  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS      37863   \n",
       "4         CONSUMER  OFFICE SUPPLIES  SCISSORS, RULERS AND TRIMMERS      53026   \n",
       "\n",
       "     Ship_Mode   Ship_Date Order_ID_y  Order_Date  Order_Priority  \n",
       "0  REGULAR AIR  28-07-2010      36262  27-07-2010   NOT SPECIFIED  \n",
       "1  EXPRESS AIR  27-07-2010      36262  27-07-2010   NOT SPECIFIED  \n",
       "2  EXPRESS AIR  28-07-2010      36262  27-07-2010   NOT SPECIFIED  \n",
       "3  REGULAR AIR  26-02-2011      37863  24-02-2011            HIGH  \n",
       "4  REGULAR AIR  03-03-2012      53026  26-02-2012             LOW  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merging the orders table to create a master df\n",
    "master_df = pd.merge(df_3, orders_df, how='inner', on='Ord_id')\n",
    "master_df.shape\n",
    "master_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similary, you can perform left, right and outer merges (joins) by using the argument ```how = 'left' / 'right' / 'outer'```."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Concatenating Dataframes\n",
    "\n",
    "Concatenation is much more straightforward than merging. It is used when you have dataframes having the same columns and want to append them (pile one on top of the other), or having the same rows and want to append them side-by-side.\n",
    "\n",
    "#### Concatenating Dataframes Having the Same columns\n",
    "\n",
    "Say you have two dataframes having the same columns, like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aman</td>\n",
       "      <td>34</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joy</td>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rashmi</td>\n",
       "      <td>22</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Saif</td>\n",
       "      <td>33</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name Age Gender\n",
       "0    Aman  34      M\n",
       "1     Joy  31      M\n",
       "2  Rashmi  22      F\n",
       "3    Saif  33      M"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dataframes having the same columns\n",
    "df1 = pd.DataFrame({'Name': ['Aman', 'Joy', 'Rashmi', 'Saif'],\n",
    "                    'Age': ['34', '31', '22', '33'],\n",
    "                    'Gender': ['M', 'M', 'F', 'M']}\n",
    "                  )\n",
    "\n",
    "df2 = pd.DataFrame({'Name': ['Akhil', 'Asha', 'Preeti'],\n",
    "                    'Age': ['31', '22', '23'],\n",
    "                    'Gender': ['M', 'F', 'F']}\n",
    "                  )\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     Akhil\n",
       "1      Asha\n",
       "2    Preeti\n",
       "Name: Name, dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2['Name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aman</td>\n",
       "      <td>34</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joy</td>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rashmi</td>\n",
       "      <td>22</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Saif</td>\n",
       "      <td>33</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Akhil</td>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asha</td>\n",
       "      <td>22</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Preeti</td>\n",
       "      <td>23</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name Age Gender\n",
       "0    Aman  34      M\n",
       "1     Joy  31      M\n",
       "2  Rashmi  22      F\n",
       "3    Saif  33      M\n",
       "0   Akhil  31      M\n",
       "1    Asha  22      F\n",
       "2  Preeti  23      F"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To concatenate them, one on top of the other, you can use pd.concat\n",
    "# The first argument is a sequence (list) of dataframes\n",
    "# axis = 0 indicates that we want to concat along the row axis\n",
    "pd.concat([df1, df2], axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aman</td>\n",
       "      <td>34</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joy</td>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rashmi</td>\n",
       "      <td>22</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Saif</td>\n",
       "      <td>33</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Akhil</td>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asha</td>\n",
       "      <td>22</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Preeti</td>\n",
       "      <td>23</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name Age Gender\n",
       "0    Aman  34      M\n",
       "1     Joy  31      M\n",
       "2  Rashmi  22      F\n",
       "3    Saif  33      M\n",
       "0   Akhil  31      M\n",
       "1    Asha  22      F\n",
       "2  Preeti  23      F"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A useful and intuitive alternative to concat along the rows is the append() function\n",
    "# It concatenates along the rows\n",
    "df1.append(df2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Concatenating Dataframes Having the Same Rows\n",
    "\n",
    "You may also have dataframes having the same rows but different columns (and having no common columns). In this case, you may want to concat them side-by-side. For e.g.:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aman</td>\n",
       "      <td>34</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joy</td>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rashmi</td>\n",
       "      <td>22</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Saif</td>\n",
       "      <td>33</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name Age Gender\n",
       "0    Aman  34      M\n",
       "1     Joy  31      M\n",
       "2  Rashmi  22      F\n",
       "3    Saif  33      M"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame({'Name': ['Aman', 'Joy', 'Rashmi', 'Saif'],\n",
    "                    'Age': ['34', '31', '22', '33'],\n",
    "                    'Gender': ['M', 'M', 'F', 'M']}\n",
    "                  )\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>School</th>\n",
       "      <th>Graduation Marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RK Public</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JSP</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Carmel Convent</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>St. Paul</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           School Graduation Marks\n",
       "0       RK Public               84\n",
       "1             JSP               89\n",
       "2  Carmel Convent               76\n",
       "3        St. Paul               91"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame({'School': ['RK Public', 'JSP', 'Carmel Convent', 'St. Paul'],\n",
    "                    'Graduation Marks': ['84', '89', '76', '91']}\n",
    "                  )\n",
    "df2[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>School</th>\n",
       "      <th>Graduation Marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aman</td>\n",
       "      <td>34</td>\n",
       "      <td>M</td>\n",
       "      <td>RK Public</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joy</td>\n",
       "      <td>31</td>\n",
       "      <td>M</td>\n",
       "      <td>JSP</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rashmi</td>\n",
       "      <td>22</td>\n",
       "      <td>F</td>\n",
       "      <td>Carmel Convent</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Saif</td>\n",
       "      <td>33</td>\n",
       "      <td>M</td>\n",
       "      <td>St. Paul</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name Age Gender          School Graduation Marks\n",
       "0    Aman  34      M       RK Public               84\n",
       "1     Joy  31      M             JSP               89\n",
       "2  Rashmi  22      F  Carmel Convent               76\n",
       "3    Saif  33      M        St. Paul               91"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To join the two dataframes, use axis = 1 to indicate joining along the columns axis\n",
    "# The join is possible because the corresponding rows have the same indices\n",
    "pd.concat([df1, df2], axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that you can also use the ```pd.concat()``` method to merge dataframes using common keys, though here we will not discuss that. For simplicity, we have used the ```pd.merge()``` method for database-style merging and ```pd.concat()``` for appending dataframes having no common columns."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Performing Arithmetic Operations on two or more dataframes\n",
    "\n",
    "We can also perform simple arithmetic operations on two or more dataframes. Below are the stats for IPL 2018 and 2017."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Matches Played</th>\n",
       "      <th>Matches Won</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IPL Team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CSK</th>\n",
       "      <td>16</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRH</th>\n",
       "      <td>17</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KKR</th>\n",
       "      <td>16</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RR</th>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCB</th>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KXIP</th>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DD</th>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Matches Played  Matches Won\n",
       "IPL Team                             \n",
       "CSK                   16           11\n",
       "SRH                   17           10\n",
       "KKR                   16            9\n",
       "RR                    15            7\n",
       "MI                    14            6\n",
       "RCB                   14            6\n",
       "KXIP                  14            6\n",
       "DD                    14            5"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Teamwise stats for IPL 2018\n",
    "IPL_2018 = pd.DataFrame({'IPL Team': ['CSK', 'SRH', 'KKR', 'RR', 'MI', 'RCB', 'KXIP', 'DD'],\n",
    "                         'Matches Played': [16, 17, 16, 15, 14, 14, 14, 14],\n",
    "                         'Matches Won': [11, 10, 9, 7, 6, 6, 6, 5]}\n",
    "                       )\n",
    "\n",
    "# Set the 'IPL Team' column as the index to perform arithmetic operations on the other rows using the team as reference\n",
    "IPL_2018.set_index('IPL Team', inplace = True)\n",
    "IPL_2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Matches Played</th>\n",
       "      <th>Matches Won</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IPL Team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPS</th>\n",
       "      <td>16</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KKR</th>\n",
       "      <td>16</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRH</th>\n",
       "      <td>15</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KXIP</th>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DD</th>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GL</th>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCB</th>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Matches Played  Matches Won\n",
       "IPL Team                             \n",
       "MI                    17           12\n",
       "RPS                   16           10\n",
       "KKR                   16            9\n",
       "SRH                   15            8\n",
       "KXIP                  14            7\n",
       "DD                    14            6\n",
       "GL                    14            4\n",
       "RCB                   14            3"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Similarly, we have the stats for IPL 2017\n",
    "IPL_2017 = pd.DataFrame({'IPL Team': ['MI', 'RPS', 'KKR', 'SRH', 'KXIP', 'DD', 'GL', 'RCB'],\n",
    "                         'Matches Played': [17, 16, 16, 15, 14, 14, 14, 14],\n",
    "                         'Matches Won': [12, 10, 9, 8, 7, 6, 4, 3]}\n",
    "                       )\n",
    "IPL_2017.set_index('IPL Team', inplace = True)\n",
    "IPL_2017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Matches Played</th>\n",
       "      <th>Matches Won</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IPL Team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CSK</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DD</th>\n",
       "      <td>28.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GL</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KKR</th>\n",
       "      <td>32.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KXIP</th>\n",
       "      <td>28.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>31.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCB</th>\n",
       "      <td>28.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPS</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RR</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRH</th>\n",
       "      <td>32.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Matches Played  Matches Won\n",
       "IPL Team                             \n",
       "CSK                  NaN          NaN\n",
       "DD                  28.0         11.0\n",
       "GL                   NaN          NaN\n",
       "KKR                 32.0         18.0\n",
       "KXIP                28.0         13.0\n",
       "MI                  31.0         18.0\n",
       "RCB                 28.0          9.0\n",
       "RPS                  NaN          NaN\n",
       "RR                   NaN          NaN\n",
       "SRH                 32.0         18.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Simply add the two DFs using the add opearator\n",
    "\n",
    "Total = IPL_2018 + IPL_2017\n",
    "Total"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that there are a lot of NaN values. This is because some teams which played in IPL 2017 were not present in IPL 2018. In addition, there were also new teams present in IPL 2018. We can handle these NaN values by using `df.add()` instead of the simple add operator. Let's see how."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Matches Played</th>\n",
       "      <th>Matches Won</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IPL Team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CSK</th>\n",
       "      <td>16.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DD</th>\n",
       "      <td>28.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GL</th>\n",
       "      <td>14.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KKR</th>\n",
       "      <td>32.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KXIP</th>\n",
       "      <td>28.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>31.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCB</th>\n",
       "      <td>28.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPS</th>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RR</th>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRH</th>\n",
       "      <td>32.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Matches Played  Matches Won\n",
       "IPL Team                             \n",
       "CSK                 16.0         11.0\n",
       "DD                  28.0         11.0\n",
       "GL                  14.0          4.0\n",
       "KKR                 32.0         18.0\n",
       "KXIP                28.0         13.0\n",
       "MI                  31.0         18.0\n",
       "RCB                 28.0          9.0\n",
       "RPS                 16.0         10.0\n",
       "RR                  15.0          7.0\n",
       "SRH                 32.0         18.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The fill_value argument inside the df.add() function replaces all the NaN values in the two dataframes w.r.t. each other with zero.\n",
    "Total = IPL_2018.add(IPL_2017, fill_value = 0)\n",
    "Total"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also notice how the resultant dataframe is sorted by the index, i.e. 'IPL Team' alphabetically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Matches Played</th>\n",
       "      <th>Matches Won</th>\n",
       "      <th>Win Percentage</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IPL Team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CSK</th>\n",
       "      <td>16.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.687500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DD</th>\n",
       "      <td>28.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.392857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GL</th>\n",
       "      <td>14.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KKR</th>\n",
       "      <td>32.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.562500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KXIP</th>\n",
       "      <td>28.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.464286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>31.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.580645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCB</th>\n",
       "      <td>28.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.321429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPS</th>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RR</th>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRH</th>\n",
       "      <td>32.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.562500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Matches Played  Matches Won  Win Percentage\n",
       "IPL Team                                             \n",
       "CSK                 16.0         11.0        0.687500\n",
       "DD                  28.0         11.0        0.392857\n",
       "GL                  14.0          4.0        0.285714\n",
       "KKR                 32.0         18.0        0.562500\n",
       "KXIP                28.0         13.0        0.464286\n",
       "MI                  31.0         18.0        0.580645\n",
       "RCB                 28.0          9.0        0.321429\n",
       "RPS                 16.0         10.0        0.625000\n",
       "RR                  15.0          7.0        0.466667\n",
       "SRH                 32.0         18.0        0.562500"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a new column - 'Win Percentage'\n",
    "\n",
    "Total['Win Percentage'] = Total['Matches Won']/Total['Matches Played']\n",
    "Total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Matches Played</th>\n",
       "      <th>Matches Won</th>\n",
       "      <th>Win Percentage</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IPL Team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>31.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.580645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KKR</th>\n",
       "      <td>32.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.562500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRH</th>\n",
       "      <td>32.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.562500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KXIP</th>\n",
       "      <td>28.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.464286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSK</th>\n",
       "      <td>16.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.687500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DD</th>\n",
       "      <td>28.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.392857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPS</th>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCB</th>\n",
       "      <td>28.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.321429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RR</th>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GL</th>\n",
       "      <td>14.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.285714</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Matches Played  Matches Won  Win Percentage\n",
       "IPL Team                                             \n",
       "MI                  31.0         18.0        0.580645\n",
       "KKR                 32.0         18.0        0.562500\n",
       "SRH                 32.0         18.0        0.562500\n",
       "KXIP                28.0         13.0        0.464286\n",
       "CSK                 16.0         11.0        0.687500\n",
       "DD                  28.0         11.0        0.392857\n",
       "RPS                 16.0         10.0        0.625000\n",
       "RCB                 28.0          9.0        0.321429\n",
       "RR                  15.0          7.0        0.466667\n",
       "GL                  14.0          4.0        0.285714"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sorting to determine the teams with most number of wins. If the number of wins of two teams are the same, sort by the win percentage.\n",
    "\n",
    "Total.sort_values(by = (['Matches Won', 'Win Percentage']), ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apart from add(), there are also other operator-equivalent mathematical functions that you can use on Dataframes. Below is a list of all the functions that you can use to perform operations on two or more dataframes\n",
    "-  `add()`: +\n",
    "-  `sub()`: -\n",
    "-  `mul()`: *\n",
    "-  `div()`: /\n",
    "-  `floordiv()`: //\n",
    "-  `mod()`: %\n",
    "-  `pow()`: **"
   ]
  }
 ],
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