association_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Association Rules Mining Using Python Generators to Handle Large Datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Motivation\n",
    "I was looking to run association analysis in Python using the apriori algorithm to derive rules of the form {A} -> {B}.  However, I quickly discovered that it's not part of the standard Python machine learning libraries.  Although there are some implementations that exist, I could not find one capable of handling large datasets.  \"Large\" in my case was an orders dataset with 32 million records, containing 3.2 million unique orders and about 50K unique items (file size just over 1 GB).  So, I decided to write my own implementation, leveraging the apriori algorithm to generate simple {A} -> {B} association rules. Since I only care about understanding relationships between any given pair of items, using apriori to get to item sets of size 2 is sufficient.  I went through various iterations, splitting the data into multiple subsets just so I could get functions like crosstab and combinations to run on my machine with 8 GB of memory.  :)  But even with this approach, I could only process about 1800 items before my kernel would crash...  And that's when I learned about the wonderful world of Python generators.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Python Generators\n",
    "\n",
    "In a nutshell, a generator is a special type of function that returns an iterable sequence of items.  However, unlike regular functions which return all the values at once (eg: returning all the elements of a list), a generator <i>yields</i> one value at a time.  To get the next value in the set, we must ask for it - either by explicitly calling the generator's built-in \"next\" method, or implicitly via a for loop.  This is a great property of generators because it means that we don't have to store all of the values in memory at once.  We can load and process one value at a time, discard when finished and move on to process the next value.  This feature makes generators perfect for creating item pairs and counting their frequency of co-occurence.  Here's a concrete example of what we're trying to accomplish:  \n",
    "\n",
    "1. Get all possible item pairs for a given order \n",
    "       eg:  order 1:  apple, egg, milk    -->  item pairs: {apple, egg}, {apple, milk}, {egg, milk}\n",
    "            order 2:  egg, milk           -->  item pairs: {egg, milk}\n",
    "            \n",
    "2. Count the number of times each item pair appears\n",
    "       eg: {apple, egg}: 1\n",
    "           {apple, milk}: 1\n",
    "           {egg, milk}: 2\n",
    "\n",
    "Here's the generator that implements the above tasks:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({('apple', 'egg'): 1, ('apple', 'milk'): 1, ('egg', 'milk'): 2})"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from itertools import combinations, groupby\n",
    "from collections import Counter\n",
    "\n",
    "# Sample data\n",
    "orders = np.array([[1,'apple'], [1,'egg'], [1,'milk'], [2,'egg'], [2,'milk']], dtype=object)\n",
    "\n",
    "# Generator that yields item pairs, one at a time\n",
    "def get_item_pairs(order_item):\n",
    "    \n",
    "    # For each order, generate a list of items in that order\n",
    "    for order_id, order_object in groupby(orders, lambda x: x[0]):\n",
    "        item_list = [item[1] for item in order_object]      \n",
    "    \n",
    "        # For each item list, generate item pairs, one at a time\n",
    "        for item_pair in combinations(item_list, 2):\n",
    "            yield item_pair                                      \n",
    "\n",
    "\n",
    "# Counter iterates through the item pairs returned by our generator and keeps a tally of their occurrence\n",
    "Counter(get_item_pairs(orders))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<i>get_item_pairs()</i> generates a list of items for each order and produces item pairs for that order, one pair at a time.  The first item pair is passed to Counter which keeps track of the number of times an item pair occurs.  The next item pair is taken, and again, passed to Counter.  This process continues until there are no more item pairs left.  With this approach, we end up not using much memory as item pairs are discarded after the count is updated."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Apriori Algorithm \n",
    "Apriori is an algorithm used to identify frequent item sets (in our case, item pairs).  It does so using a \"bottom up\" approach, first identifying individual items that satisfy a minimum occurence threshold. It then extends the item set, adding one item at a time and checking if the resulting item set still satisfies the specified threshold.  The algorithm stops when there are no more items to add that meet the minimum occurrence requirement.  Here's an example of apriori in action, assuming a minimum occurence threshold of 3:\n",
    "\n",
    "\n",
    "    order 1: apple, egg, milk  \n",
    "    order 2: carrot, milk  \n",
    "    order 3: apple, egg, carrot\n",
    "    order 4: apple, egg\n",
    "    order 5: apple, carrot\n",
    "\n",
    "    \n",
    "    Iteration 1:  Count the number of times each item occurs   \n",
    "    item set      occurrence count    \n",
    "    {apple}              4   \n",
    "    {egg}                3   \n",
    "    {milk}               2   \n",
    "    {carrot}             2   \n",
    "\n",
    "    {milk} and {carrot} are eliminated because they do not meet the minimum occurrence threshold.\n",
    "\n",
    "\n",
    "    Iteration 2: Build item sets of size 2 using the remaining items from Iteration 1 (ie: apple, egg)  \n",
    "    item set           occurence count  \n",
    "    {apple, egg}             3  \n",
    "\n",
    "    Only {apple, egg} remains and the algorithm stops since there are no more items to add.\n",
    "   \n",
    "   \n",
    "If we had more orders and items, we can continue to iterate, building item sets consisting of more than 2 elements.  For the problem we are trying to solve  \n",
    "(ie: finding relationships between pairs of items), it suffices to implement apriori to get to item sets of size 2."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Association Rules Mining\n",
    "Once the item sets have been generated using apriori, we can start mining association rules.  Given that we are only looking at item sets of size 2, the association rules we will generate will be of the form {A} -> {B}.  One common application of these rules is in the domain of recommender systems, where customers who purchased item A are recommended item B.\n",
    "\n",
    "Here are 3 key metrics to consider when evaluating association rules:\n",
    "\n",
    "1. <b>support</b>  \n",
    "    This is the percentage of orders that contains the item set. In the example above, there are 5 orders in total \n",
    "    and {apple,egg} occurs in 3 of them, so: \n",
    "       \n",
    "                    support{apple,egg} = 3/5 or 60%\n",
    "        \n",
    "    The minimum support threshold required by apriori can be set based on knowledge of your domain.  In this \n",
    "    grocery dataset for example, since there could be thousands of distinct items and an order can contain \n",
    "    only a small fraction of these items, setting the support threshold to 0.01% may be reasonable.<br><br><br>\n",
    "    \n",
    "2. <b>confidence</b>  \n",
    "    Given two items, A and B, confidence measures the percentage of times that item B is purchased, given that \n",
    "    item A was purchased. This is expressed as:\n",
    "       \n",
    "                    confidence{A->B} = support{A,B} / support{A}   \n",
    "                    \n",
    "    Confidence values range from 0 to 1, where 0 indicates that B is never purchased when A is purchased, and 1 \n",
    "    indicates that B is always purchased whenever A is purchased.  Note that the confidence measure is directional.     This means that we can also compute the percentage of times that item A is purchased, given that item B was \n",
    "    purchased:\n",
    "       \n",
    "                    confidence{B->A} = support{A,B} / support{B}    \n",
    "                    \n",
    "    In our example, the percentage of times that egg is purchased, given that apple was purchased is:  \n",
    "       \n",
    "                    confidence{apple->egg} = support{apple,egg} / support{apple}\n",
    "                                           = (3/5) / (4/5)\n",
    "                                           = 0.75 or 75%\n",
    "\n",
    "    A confidence value of 0.75 implies that out of all orders that contain apple, 75% of them also contain egg.  Now, \n",
    "    we look at the confidence measure in the opposite direction (ie: egg->apple): \n",
    "       \n",
    "                    confidence{egg->apple} = support{apple,egg} / support{egg}\n",
    "                                           = (3/5) / (3/5)\n",
    "                                           = 1 or 100%  \n",
    "                                           \n",
    "    Here we see that all of the orders that contain egg also contain apple.  But, does this mean that there is a \n",
    "    relationship between these two items, or are they occurring together in the same orders simply by chance?  To \n",
    "    answer this question, we look at another measure which takes into account the popularity of <i>both</i> items.<br><br><br>  \n",
    "    \n",
    "3. <b>lift</b>  \n",
    "    Given two items, A and B, lift indicates whether there is a relationship between A and B, or whether the two items \n",
    "    are occuring together in the same orders simply by chance (ie: at random).  Unlike the confidence metric whose \n",
    "    value may vary depending on direction (eg: confidence{A->B} may be different from confidence{B->A}), \n",
    "    lift has no direction. This means that the lift{A,B} is always equal to the lift{B,A}: \n",
    "       \n",
    "                    lift{A,B} = lift{B,A} = support{A,B} / (support{A} * support{B})   \n",
    "    \n",
    "    In our example, we compute lift as follows:\n",
    "    \n",
    "                    lift{apple,egg} = lift{egg,apple} = support{apple,egg} / (support{apple} * support{egg})\n",
    "                                                      = (3/5) / (4/5 * 3/5) \n",
    "                                                      = 1.25    \n",
    "               \n",
    "    One way to understand lift is to think of the denominator as the likelihood that A and B will appear in the same \n",
    "    order if there was <i>no</i> relationship between them. In the example above, if apple occurred in 80% of the\n",
    "    orders and egg occurred in 60% of the orders, then if there was no relationship between them, we would \n",
    "    <i>expect</i> both of them to show up together in the same order 48% of the time (ie: 80% * 60%).  The numerator, \n",
    "    on the other hand, represents how often apple and egg <i>actually</i> appear together in the same order.  In \n",
    "    this example, that is 60% of the time.  Taking the numerator and dividing it by the denominator, we get to how \n",
    "    many more times apple and egg actually appear in the same order, compared to if there was no relationship between     them (ie: that they are occurring together simply at random).  \n",
    "    \n",
    "    In summary, lift can take on the following values:\n",
    "    \n",
    "        * lift = 1 implies no relationship between A and B. \n",
    "          (ie: A and B occur together only by chance)\n",
    "      \n",
    "        * lift > 1 implies that there is a positive relationship between A and B.\n",
    "          (ie:  A and B occur together more often than random)\n",
    "    \n",
    "        * lift < 1 implies that there is a negative relationship between A and B.\n",
    "          (ie:  A and B occur together less often than random)\n",
    "        \n",
    "    In our example, apple and egg occur together 1.25 times <i>more</i> than random, so we conclude that there exists \n",
    "    a positive relationship between them.\n",
    "   \n",
    "Armed with knowledge of apriori and association rules mining, let's dive into the data and code to see what relationships we unravel!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Input Dataset\n",
    "Instacart, an online grocer, has graciously made some of their datasets accessible to the public.  The order and product datasets that we will be using can be downloaded from the link below, along with the data dictionary:\n",
    "\n",
    "“The Instacart Online Grocery Shopping Dataset 2017”, Accessed from https://www.instacart.com/datasets/grocery-shopping-2017 on September 1, 2017.<br><br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import sys\n",
    "from itertools import combinations, groupby\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Function that returns the size of an object in MB\n",
    "def size(obj):\n",
    "    return \"{0:.2f} MB\".format(sys.getsizeof(obj) / (1000 * 1000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 1:  Data Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### A. Load order  data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orders -- dimensions: (32434489, 4);   size: 1037.90 MB\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>product_id</th>\n",
       "      <th>add_to_cart_order</th>\n",
       "      <th>reordered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>33120</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>28985</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>9327</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>45918</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>30035</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  product_id  add_to_cart_order  reordered\n",
       "0         2       33120                  1          1\n",
       "1         2       28985                  2          1\n",
       "2         2        9327                  3          0\n",
       "3         2       45918                  4          1\n",
       "4         2       30035                  5          0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "orders = pd.read_csv('order_products__prior.csv')\n",
    "print('orders -- dimensions: {0};   size: {1}'.format(orders.shape, size(orders)))\n",
    "display(orders.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### B. Convert order data into format expected by the association rules function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "order_id\n",
       "2    33120\n",
       "2    28985\n",
       "2     9327\n",
       "2    45918\n",
       "2    30035\n",
       "2    17794\n",
       "2    40141\n",
       "2     1819\n",
       "2    43668\n",
       "3    33754\n",
       "Name: item_id, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert from DataFrame to a Series, with order_id as index and item_id as value\n",
    "orders = orders.set_index('order_id')['product_id'].rename('item_id')\n",
    "display(orders.head(10))\n",
    "type(orders)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### C. Display summary statistics for order data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orders -- dimensions: (32434489,);   size: 518.95 MB;   unique_orders: 3214874;   unique_items: 49677\n"
     ]
    }
   ],
   "source": [
    "print('orders -- dimensions: {0};   size: {1};   unique_orders: {2};   unique_items: {3}'\n",
    "      .format(orders.shape, size(orders), len(orders.index.unique()), len(orders.value_counts())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 2: Association Rules Function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### A. Helper functions to the main association rules function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Returns frequency counts for items and item pairs\n",
    "def freq(iterable):\n",
    "    if type(iterable) == pd.core.series.Series:\n",
    "        return iterable.value_counts().rename(\"freq\")\n",
    "    else: \n",
    "        return pd.Series(Counter(iterable)).rename(\"freq\")\n",
    "\n",
    "    \n",
    "# Returns number of unique orders\n",
    "def order_count(order_item):\n",
    "    return len(set(order_item.index))\n",
    "\n",
    "\n",
    "# Returns generator that yields item pairs, one at a time\n",
    "def get_item_pairs(order_item):\n",
    "    order_item = order_item.reset_index().as_matrix()\n",
    "    for order_id, order_object in groupby(order_item, lambda x: x[0]):\n",
    "        item_list = [item[1] for item in order_object]\n",
    "              \n",
    "        for item_pair in combinations(item_list, 2):\n",
    "            yield item_pair\n",
    "            \n",
    "\n",
    "# Returns frequency and support associated with item\n",
    "def merge_item_stats(item_pairs, item_stats):\n",
    "    return (item_pairs\n",
    "                .merge(item_stats.rename(columns={'freq': 'freqA', 'support': 'supportA'}), left_on='item_A', right_index=True)\n",
    "                .merge(item_stats.rename(columns={'freq': 'freqB', 'support': 'supportB'}), left_on='item_B', right_index=True))\n",
    "\n",
    "\n",
    "# Returns name associated with item\n",
    "def merge_item_name(rules, item_name):\n",
    "    columns = ['itemA','itemB','freqAB','supportAB','freqA','supportA','freqB','supportB', \n",
    "               'confidenceAtoB','confidenceBtoA','lift']\n",
    "    rules = (rules\n",
    "                .merge(item_name.rename(columns={'item_name': 'itemA'}), left_on='item_A', right_on='item_id')\n",
    "                .merge(item_name.rename(columns={'item_name': 'itemB'}), left_on='item_B', right_on='item_id'))\n",
    "    return rules[columns]               "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### B. Association rules function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def association_rules(order_item, min_support):\n",
    "\n",
    "    print(\"Starting order_item: {:22d}\".format(len(order_item)))\n",
    "\n",
    "\n",
    "    # Calculate item frequency and support\n",
    "    item_stats             = freq(order_item).to_frame(\"freq\")\n",
    "    item_stats['support']  = item_stats['freq'] / order_count(order_item) * 100\n",
    "\n",
    "\n",
    "    # Filter from order_item items below min support \n",
    "    qualifying_items       = item_stats[item_stats['support'] >= min_support].index\n",
    "    order_item             = order_item[order_item.isin(qualifying_items)]\n",
    "\n",
    "    print(\"Items with support >= {}: {:15d}\".format(min_support, len(qualifying_items)))\n",
    "    print(\"Remaining order_item: {:21d}\".format(len(order_item)))\n",
    "\n",
    "\n",
    "    # Filter from order_item orders with less than 2 items\n",
    "    order_size             = freq(order_item.index)\n",
    "    qualifying_orders      = order_size[order_size >= 2].index\n",
    "    order_item             = order_item[order_item.index.isin(qualifying_orders)]\n",
    "\n",
    "    print(\"Remaining orders with 2+ items: {:11d}\".format(len(qualifying_orders)))\n",
    "    print(\"Remaining order_item: {:21d}\".format(len(order_item)))\n",
    "\n",
    "\n",
    "    # Recalculate item frequency and support\n",
    "    item_stats             = freq(order_item).to_frame(\"freq\")\n",
    "    item_stats['support']  = item_stats['freq'] / order_count(order_item) * 100\n",
    "\n",
    "\n",
    "    # Get item pairs generator\n",
    "    item_pair_gen          = get_item_pairs(order_item)\n",
    "\n",
    "\n",
    "    # Calculate item pair frequency and support\n",
    "    item_pairs              = freq(item_pair_gen).to_frame(\"freqAB\")\n",
    "    item_pairs['supportAB'] = item_pairs['freqAB'] / len(qualifying_orders) * 100\n",
    "\n",
    "    print(\"Item pairs: {:31d}\".format(len(item_pairs)))\n",
    "\n",
    "\n",
    "    # Filter from item_pairs those below min support\n",
    "    item_pairs              = item_pairs[item_pairs['supportAB'] >= min_support]\n",
    "\n",
    "    print(\"Item pairs with support >= {}: {:10d}\\n\".format(min_support, len(item_pairs)))\n",
    "\n",
    "\n",
    "    # Create table of association rules and compute relevant metrics\n",
    "    item_pairs = item_pairs.reset_index().rename(columns={'level_0': 'item_A', 'level_1': 'item_B'})\n",
    "    item_pairs = merge_item_stats(item_pairs, item_stats)\n",
    "    \n",
    "    item_pairs['confidenceAtoB'] = item_pairs['supportAB'] / item_pairs['supportA']\n",
    "    item_pairs['confidenceBtoA'] = item_pairs['supportAB'] / item_pairs['supportB']\n",
    "    item_pairs['lift']           = item_pairs['supportAB'] / (item_pairs['supportA'] * item_pairs['supportB'])\n",
    "   \n",
    "\n",
    "    # Return association rules sorted by lift in descending order\n",
    "    return item_pairs.sort_values('lift', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 3:  Association Rules Mining"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting order_item:               32434489\n",
      "Items with support >= 0.01:           10906\n",
      "Remaining order_item:              29843570\n",
      "Remaining orders with 2+ items:     3013325\n",
      "Remaining order_item:              29662716\n",
      "Item pairs:                        30622410\n",
      "Item pairs with support >= 0.01:      48751\n",
      "\n",
      "CPU times: user 10min 22s, sys: 47.6 s, total: 11min 9s\n",
      "Wall time: 11min 40s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rules = association_rules(orders, 0.01)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>itemA</th>\n",
       "      <th>itemB</th>\n",
       "      <th>freqAB</th>\n",
       "      <th>supportAB</th>\n",
       "      <th>freqA</th>\n",
       "      <th>supportA</th>\n",
       "      <th>freqB</th>\n",
       "      <th>supportB</th>\n",
       "      <th>confidenceAtoB</th>\n",
       "      <th>confidenceBtoA</th>\n",
       "      <th>lift</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Organic Strawberry Chia Lowfat 2% Cottage Cheese</td>\n",
       "      <td>Organic Cottage Cheese Blueberry Acai Chia</td>\n",
       "      <td>306</td>\n",
       "      <td>0.010155</td>\n",
       "      <td>1163</td>\n",
       "      <td>0.038595</td>\n",
       "      <td>839</td>\n",
       "      <td>0.027843</td>\n",
       "      <td>0.263113</td>\n",
       "      <td>0.364720</td>\n",
       "      <td>9.449868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Grain Free Chicken Formula Cat Food</td>\n",
       "      <td>Grain Free Turkey Formula Cat Food</td>\n",
       "      <td>318</td>\n",
       "      <td>0.010553</td>\n",
       "      <td>1809</td>\n",
       "      <td>0.060033</td>\n",
       "      <td>879</td>\n",
       "      <td>0.029170</td>\n",
       "      <td>0.175788</td>\n",
       "      <td>0.361775</td>\n",
       "      <td>6.026229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Organic Fruit Yogurt Smoothie Mixed Berry</td>\n",
       "      <td>Apple Blueberry Fruit Yogurt Smoothie</td>\n",
       "      <td>349</td>\n",
       "      <td>0.011582</td>\n",
       "      <td>1518</td>\n",
       "      <td>0.050376</td>\n",
       "      <td>1249</td>\n",
       "      <td>0.041449</td>\n",
       "      <td>0.229908</td>\n",
       "      <td>0.279424</td>\n",
       "      <td>5.546732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nonfat Strawberry With Fruit On The Bottom Gre...</td>\n",
       "      <td>0% Greek, Blueberry on the Bottom Yogurt</td>\n",
       "      <td>409</td>\n",
       "      <td>0.013573</td>\n",
       "      <td>1666</td>\n",
       "      <td>0.055288</td>\n",
       "      <td>1391</td>\n",
       "      <td>0.046162</td>\n",
       "      <td>0.245498</td>\n",
       "      <td>0.294033</td>\n",
       "      <td>5.318230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Organic Grapefruit Ginger Sparkling Yerba Mate</td>\n",
       "      <td>Cranberry Pomegranate Sparkling Yerba Mate</td>\n",
       "      <td>351</td>\n",
       "      <td>0.011648</td>\n",
       "      <td>1731</td>\n",
       "      <td>0.057445</td>\n",
       "      <td>1149</td>\n",
       "      <td>0.038131</td>\n",
       "      <td>0.202773</td>\n",
       "      <td>0.305483</td>\n",
       "      <td>5.317849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Baby Food Pouch - Roasted Carrot Spinach &amp; Beans</td>\n",
       "      <td>Baby Food Pouch - Butternut Squash, Carrot &amp; C...</td>\n",
       "      <td>332</td>\n",
       "      <td>0.011018</td>\n",
       "      <td>1503</td>\n",
       "      <td>0.049878</td>\n",
       "      <td>1290</td>\n",
       "      <td>0.042810</td>\n",
       "      <td>0.220892</td>\n",
       "      <td>0.257364</td>\n",
       "      <td>5.159830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Unsweetened Whole Milk Mixed Berry Greek Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Blueberry Greek Yogurt</td>\n",
       "      <td>438</td>\n",
       "      <td>0.014535</td>\n",
       "      <td>1622</td>\n",
       "      <td>0.053828</td>\n",
       "      <td>1621</td>\n",
       "      <td>0.053794</td>\n",
       "      <td>0.270037</td>\n",
       "      <td>0.270204</td>\n",
       "      <td>5.019798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Uncured Cracked Pepper Beef</td>\n",
       "      <td>Chipotle Beef &amp; Pork Realstick</td>\n",
       "      <td>410</td>\n",
       "      <td>0.013606</td>\n",
       "      <td>1839</td>\n",
       "      <td>0.061029</td>\n",
       "      <td>1370</td>\n",
       "      <td>0.045465</td>\n",
       "      <td>0.222947</td>\n",
       "      <td>0.299270</td>\n",
       "      <td>4.903741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Organic Mango Yogurt</td>\n",
       "      <td>Organic Whole Milk Washington Black Cherry Yogurt</td>\n",
       "      <td>334</td>\n",
       "      <td>0.011084</td>\n",
       "      <td>1675</td>\n",
       "      <td>0.055586</td>\n",
       "      <td>1390</td>\n",
       "      <td>0.046128</td>\n",
       "      <td>0.199403</td>\n",
       "      <td>0.240288</td>\n",
       "      <td>4.322777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Grain Free Chicken Formula Cat Food</td>\n",
       "      <td>Grain Free Turkey &amp; Salmon Formula Cat Food</td>\n",
       "      <td>391</td>\n",
       "      <td>0.012976</td>\n",
       "      <td>1809</td>\n",
       "      <td>0.060033</td>\n",
       "      <td>1553</td>\n",
       "      <td>0.051538</td>\n",
       "      <td>0.216142</td>\n",
       "      <td>0.251771</td>\n",
       "      <td>4.193848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Raspberry Essence Water</td>\n",
       "      <td>Unsweetened Pomegranate Essence Water</td>\n",
       "      <td>366</td>\n",
       "      <td>0.012146</td>\n",
       "      <td>2025</td>\n",
       "      <td>0.067202</td>\n",
       "      <td>1304</td>\n",
       "      <td>0.043274</td>\n",
       "      <td>0.180741</td>\n",
       "      <td>0.280675</td>\n",
       "      <td>4.176615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Unsweetened Whole Milk Strawberry Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Blueberry Greek Yogurt</td>\n",
       "      <td>440</td>\n",
       "      <td>0.014602</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.065210</td>\n",
       "      <td>1621</td>\n",
       "      <td>0.053794</td>\n",
       "      <td>0.223919</td>\n",
       "      <td>0.271437</td>\n",
       "      <td>4.162489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Unsweetened Whole Milk Peach Greek Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Blueberry Greek Yogurt</td>\n",
       "      <td>421</td>\n",
       "      <td>0.013971</td>\n",
       "      <td>1922</td>\n",
       "      <td>0.063783</td>\n",
       "      <td>1621</td>\n",
       "      <td>0.053794</td>\n",
       "      <td>0.219043</td>\n",
       "      <td>0.259716</td>\n",
       "      <td>4.071849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Oh My Yog! Pacific Coast Strawberry Trilayer Y...</td>\n",
       "      <td>Oh My Yog! Organic Wild Quebec Blueberry Cream...</td>\n",
       "      <td>860</td>\n",
       "      <td>0.028540</td>\n",
       "      <td>2857</td>\n",
       "      <td>0.094812</td>\n",
       "      <td>2271</td>\n",
       "      <td>0.075365</td>\n",
       "      <td>0.301015</td>\n",
       "      <td>0.378688</td>\n",
       "      <td>3.994083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Mighty 4 Kale, Strawberry, Amaranth &amp; Greek Yo...</td>\n",
       "      <td>Mighty 4 Essential Tots Spinach, Kiwi, Barley ...</td>\n",
       "      <td>390</td>\n",
       "      <td>0.012943</td>\n",
       "      <td>2206</td>\n",
       "      <td>0.073208</td>\n",
       "      <td>1337</td>\n",
       "      <td>0.044370</td>\n",
       "      <td>0.176791</td>\n",
       "      <td>0.291698</td>\n",
       "      <td>3.984498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Unsweetened Whole Milk Peach Greek Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Strawberry Yogurt</td>\n",
       "      <td>499</td>\n",
       "      <td>0.016560</td>\n",
       "      <td>1922</td>\n",
       "      <td>0.063783</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.065210</td>\n",
       "      <td>0.259625</td>\n",
       "      <td>0.253944</td>\n",
       "      <td>3.981352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>0% Greek, Blueberry on the Bottom Yogurt</td>\n",
       "      <td>Nonfat Strawberry With Fruit On The Bottom Gre...</td>\n",
       "      <td>305</td>\n",
       "      <td>0.010122</td>\n",
       "      <td>1391</td>\n",
       "      <td>0.046162</td>\n",
       "      <td>1666</td>\n",
       "      <td>0.055288</td>\n",
       "      <td>0.219267</td>\n",
       "      <td>0.183073</td>\n",
       "      <td>3.965918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Unsweetened Whole Milk Mixed Berry Greek Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Peach Greek Yogurt</td>\n",
       "      <td>410</td>\n",
       "      <td>0.013606</td>\n",
       "      <td>1622</td>\n",
       "      <td>0.053828</td>\n",
       "      <td>1922</td>\n",
       "      <td>0.063783</td>\n",
       "      <td>0.252774</td>\n",
       "      <td>0.213319</td>\n",
       "      <td>3.963014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Unsweetened Whole Milk Peach Greek Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Mixed Berry Greek Yogurt</td>\n",
       "      <td>407</td>\n",
       "      <td>0.013507</td>\n",
       "      <td>1922</td>\n",
       "      <td>0.063783</td>\n",
       "      <td>1622</td>\n",
       "      <td>0.053828</td>\n",
       "      <td>0.211759</td>\n",
       "      <td>0.250925</td>\n",
       "      <td>3.934016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Unsweetened Blackberry Water</td>\n",
       "      <td>Unsweetened Pomegranate Essence Water</td>\n",
       "      <td>494</td>\n",
       "      <td>0.016394</td>\n",
       "      <td>3114</td>\n",
       "      <td>0.103341</td>\n",
       "      <td>1304</td>\n",
       "      <td>0.043274</td>\n",
       "      <td>0.158638</td>\n",
       "      <td>0.378834</td>\n",
       "      <td>3.665867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Unsweetened Whole Milk Mixed Berry Greek Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Strawberry Yogurt</td>\n",
       "      <td>383</td>\n",
       "      <td>0.012710</td>\n",
       "      <td>1622</td>\n",
       "      <td>0.053828</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.065210</td>\n",
       "      <td>0.236128</td>\n",
       "      <td>0.194911</td>\n",
       "      <td>3.621024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Unsweetened Whole Milk Strawberry Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Peach Greek Yogurt</td>\n",
       "      <td>444</td>\n",
       "      <td>0.014735</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.065210</td>\n",
       "      <td>1922</td>\n",
       "      <td>0.063783</td>\n",
       "      <td>0.225954</td>\n",
       "      <td>0.231009</td>\n",
       "      <td>3.542526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Mighty 4 Sweet Potato, Blueberry, Millet &amp; Gre...</td>\n",
       "      <td>Mighty 4 Essential Tots Spinach, Kiwi, Barley ...</td>\n",
       "      <td>398</td>\n",
       "      <td>0.013208</td>\n",
       "      <td>2534</td>\n",
       "      <td>0.084093</td>\n",
       "      <td>1337</td>\n",
       "      <td>0.044370</td>\n",
       "      <td>0.157064</td>\n",
       "      <td>0.297681</td>\n",
       "      <td>3.539900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Sweet Potatoes Stage 2</td>\n",
       "      <td>Organic Stage 2 Winter Squash Baby Food Puree</td>\n",
       "      <td>322</td>\n",
       "      <td>0.010686</td>\n",
       "      <td>2077</td>\n",
       "      <td>0.068927</td>\n",
       "      <td>1322</td>\n",
       "      <td>0.043872</td>\n",
       "      <td>0.155031</td>\n",
       "      <td>0.243570</td>\n",
       "      <td>3.533734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>Compostable Forks</td>\n",
       "      <td>Plastic Spoons</td>\n",
       "      <td>321</td>\n",
       "      <td>0.010653</td>\n",
       "      <td>1528</td>\n",
       "      <td>0.050708</td>\n",
       "      <td>1838</td>\n",
       "      <td>0.060996</td>\n",
       "      <td>0.210079</td>\n",
       "      <td>0.174646</td>\n",
       "      <td>3.444151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Organic Stage 2 Carrots Baby Food</td>\n",
       "      <td>Organic Stage 2 Winter Squash Baby Food Puree</td>\n",
       "      <td>337</td>\n",
       "      <td>0.011184</td>\n",
       "      <td>2306</td>\n",
       "      <td>0.076527</td>\n",
       "      <td>1322</td>\n",
       "      <td>0.043872</td>\n",
       "      <td>0.146141</td>\n",
       "      <td>0.254917</td>\n",
       "      <td>3.331080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Unsweetened Whole Milk Strawberry Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Mixed Berry Greek Yogurt</td>\n",
       "      <td>352</td>\n",
       "      <td>0.011681</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.065210</td>\n",
       "      <td>1622</td>\n",
       "      <td>0.053828</td>\n",
       "      <td>0.179135</td>\n",
       "      <td>0.217016</td>\n",
       "      <td>3.327938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Unsweetened Whole Milk Blueberry Greek Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Strawberry Yogurt</td>\n",
       "      <td>350</td>\n",
       "      <td>0.011615</td>\n",
       "      <td>1621</td>\n",
       "      <td>0.053794</td>\n",
       "      <td>1965</td>\n",
       "      <td>0.065210</td>\n",
       "      <td>0.215916</td>\n",
       "      <td>0.178117</td>\n",
       "      <td>3.311071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Unsweetened Whole Milk Blueberry Greek Yogurt</td>\n",
       "      <td>Unsweetened Whole Milk Peach Greek Yogurt</td>\n",
       "      <td>341</td>\n",
       "      <td>0.011316</td>\n",
       "      <td>1621</td>\n",
       "      <td>0.053794</td>\n",
       "      <td>1922</td>\n",
       "      <td>0.063783</td>\n",
       "      <td>0.210364</td>\n",
       "      <td>0.177419</td>\n",
       "      <td>3.298101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>Cream Top Blueberry Yogurt</td>\n",
       "      <td>Cream Top Peach on the Bottom Yogurt</td>\n",
       "      <td>313</td>\n",
       "      <td>0.010387</td>\n",
       "      <td>1676</td>\n",
       "      <td>0.055620</td>\n",
       "      <td>1748</td>\n",
       "      <td>0.058009</td>\n",
       "      <td>0.186754</td>\n",
       "      <td>0.179062</td>\n",
       "      <td>3.219399</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22444</th>\n",
       "      <td>Large Lemon</td>\n",
       "      <td>Hass Avocados</td>\n",
       "      <td>468</td>\n",
       "      <td>0.015531</td>\n",
       "      <td>152177</td>\n",
       "      <td>5.050136</td>\n",
       "      <td>49246</td>\n",
       "      <td>1.634274</td>\n",
       "      <td>0.003075</td>\n",
       "      <td>0.009503</td>\n",
       "      <td>0.001882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2577</th>\n",
       "      <td>Red Onion</td>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>1008</td>\n",
       "      <td>0.033451</td>\n",
       "      <td>42906</td>\n",
       "      <td>1.423876</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>0.023493</td>\n",
       "      <td>0.002678</td>\n",
       "      <td>0.001881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>Roasted Pine Nut Hummus</td>\n",
       "      <td>Banana</td>\n",
       "      <td>327</td>\n",
       "      <td>0.010852</td>\n",
       "      <td>11176</td>\n",
       "      <td>0.370886</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>0.029259</td>\n",
       "      <td>0.000696</td>\n",
       "      <td>0.001876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>655</th>\n",
       "      <td>Organic Large Green Asparagus</td>\n",
       "      <td>Banana</td>\n",
       "      <td>556</td>\n",
       "      <td>0.018451</td>\n",
       "      <td>19228</td>\n",
       "      <td>0.638099</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>0.028916</td>\n",
       "      <td>0.001183</td>\n",
       "      <td>0.001854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40897</th>\n",
       "      <td>Banana</td>\n",
       "      <td>Organic Extra Virgin Olive Oil</td>\n",
       "      <td>369</td>\n",
       "      <td>0.012246</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>12788</td>\n",
       "      <td>0.424382</td>\n",
       "      <td>0.000785</td>\n",
       "      <td>0.028855</td>\n",
       "      <td>0.001850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2652</th>\n",
       "      <td>Spinach</td>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>383</td>\n",
       "      <td>0.012710</td>\n",
       "      <td>16766</td>\n",
       "      <td>0.556395</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>0.022844</td>\n",
       "      <td>0.001018</td>\n",
       "      <td>0.001829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2722</th>\n",
       "      <td>Sour Cream</td>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>486</td>\n",
       "      <td>0.016128</td>\n",
       "      <td>21481</td>\n",
       "      <td>0.712867</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>0.022625</td>\n",
       "      <td>0.001291</td>\n",
       "      <td>0.001811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11143</th>\n",
       "      <td>Organic Blueberries</td>\n",
       "      <td>Blueberries</td>\n",
       "      <td>329</td>\n",
       "      <td>0.010918</td>\n",
       "      <td>99359</td>\n",
       "      <td>3.297321</td>\n",
       "      <td>55703</td>\n",
       "      <td>1.848556</td>\n",
       "      <td>0.003311</td>\n",
       "      <td>0.005906</td>\n",
       "      <td>0.001791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2537</th>\n",
       "      <td>Green Onions</td>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>592</td>\n",
       "      <td>0.019646</td>\n",
       "      <td>26467</td>\n",
       "      <td>0.878332</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>0.022367</td>\n",
       "      <td>0.001573</td>\n",
       "      <td>0.001791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1386</th>\n",
       "      <td>2% Reduced Fat Milk</td>\n",
       "      <td>Organic Strawberries</td>\n",
       "      <td>574</td>\n",
       "      <td>0.019049</td>\n",
       "      <td>36768</td>\n",
       "      <td>1.220180</td>\n",
       "      <td>263416</td>\n",
       "      <td>8.741706</td>\n",
       "      <td>0.015611</td>\n",
       "      <td>0.002179</td>\n",
       "      <td>0.001786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3291</th>\n",
       "      <td>2% Reduced Fat Milk</td>\n",
       "      <td>Organic Baby Spinach</td>\n",
       "      <td>523</td>\n",
       "      <td>0.017356</td>\n",
       "      <td>36768</td>\n",
       "      <td>1.220180</td>\n",
       "      <td>240637</td>\n",
       "      <td>7.985763</td>\n",
       "      <td>0.014224</td>\n",
       "      <td>0.002173</td>\n",
       "      <td>0.001781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>Chocolate Chip Cookies</td>\n",
       "      <td>Banana</td>\n",
       "      <td>377</td>\n",
       "      <td>0.012511</td>\n",
       "      <td>13688</td>\n",
       "      <td>0.454249</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>0.027542</td>\n",
       "      <td>0.000802</td>\n",
       "      <td>0.001765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10681</th>\n",
       "      <td>Half &amp; Half</td>\n",
       "      <td>Organic Half &amp; Half</td>\n",
       "      <td>302</td>\n",
       "      <td>0.010022</td>\n",
       "      <td>68842</td>\n",
       "      <td>2.284586</td>\n",
       "      <td>75334</td>\n",
       "      <td>2.500029</td>\n",
       "      <td>0.004387</td>\n",
       "      <td>0.004009</td>\n",
       "      <td>0.001755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5446</th>\n",
       "      <td>Organic Reduced Fat 2% Milk</td>\n",
       "      <td>Organic Whole Milk</td>\n",
       "      <td>379</td>\n",
       "      <td>0.012577</td>\n",
       "      <td>47593</td>\n",
       "      <td>1.579418</td>\n",
       "      <td>136832</td>\n",
       "      <td>4.540898</td>\n",
       "      <td>0.007963</td>\n",
       "      <td>0.002770</td>\n",
       "      <td>0.001754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11455</th>\n",
       "      <td>Banana</td>\n",
       "      <td>Soda</td>\n",
       "      <td>864</td>\n",
       "      <td>0.028673</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>33008</td>\n",
       "      <td>1.095401</td>\n",
       "      <td>0.001838</td>\n",
       "      <td>0.026175</td>\n",
       "      <td>0.001678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11421</th>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>Fridge Pack Cola</td>\n",
       "      <td>366</td>\n",
       "      <td>0.012146</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>18005</td>\n",
       "      <td>0.597513</td>\n",
       "      <td>0.000972</td>\n",
       "      <td>0.020328</td>\n",
       "      <td>0.001628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2568</th>\n",
       "      <td>Asparation/Broccolini/Baby Broccoli</td>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>317</td>\n",
       "      <td>0.010520</td>\n",
       "      <td>16480</td>\n",
       "      <td>0.546904</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>0.019235</td>\n",
       "      <td>0.000842</td>\n",
       "      <td>0.001540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19596</th>\n",
       "      <td>Banana</td>\n",
       "      <td>Organic Tortilla Chips</td>\n",
       "      <td>320</td>\n",
       "      <td>0.010619</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>13458</td>\n",
       "      <td>0.446616</td>\n",
       "      <td>0.000681</td>\n",
       "      <td>0.023778</td>\n",
       "      <td>0.001524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2319</th>\n",
       "      <td>Fridge Pack Cola</td>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>341</td>\n",
       "      <td>0.011316</td>\n",
       "      <td>18005</td>\n",
       "      <td>0.597513</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>0.018939</td>\n",
       "      <td>0.000906</td>\n",
       "      <td>0.001516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11017</th>\n",
       "      <td>Organic Baby Spinach</td>\n",
       "      <td>2% Reduced Fat Milk</td>\n",
       "      <td>403</td>\n",
       "      <td>0.013374</td>\n",
       "      <td>240637</td>\n",
       "      <td>7.985763</td>\n",
       "      <td>36768</td>\n",
       "      <td>1.220180</td>\n",
       "      <td>0.001675</td>\n",
       "      <td>0.010961</td>\n",
       "      <td>0.001373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22572</th>\n",
       "      <td>Organic Raspberries</td>\n",
       "      <td>Raspberries</td>\n",
       "      <td>322</td>\n",
       "      <td>0.010686</td>\n",
       "      <td>136621</td>\n",
       "      <td>4.533895</td>\n",
       "      <td>56858</td>\n",
       "      <td>1.886886</td>\n",
       "      <td>0.002357</td>\n",
       "      <td>0.005663</td>\n",
       "      <td>0.001249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11012</th>\n",
       "      <td>Organic Strawberries</td>\n",
       "      <td>2% Reduced Fat Milk</td>\n",
       "      <td>371</td>\n",
       "      <td>0.012312</td>\n",
       "      <td>263416</td>\n",
       "      <td>8.741706</td>\n",
       "      <td>36768</td>\n",
       "      <td>1.220180</td>\n",
       "      <td>0.001408</td>\n",
       "      <td>0.010090</td>\n",
       "      <td>0.001154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>Soda</td>\n",
       "      <td>Banana</td>\n",
       "      <td>531</td>\n",
       "      <td>0.017622</td>\n",
       "      <td>33008</td>\n",
       "      <td>1.095401</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>0.016087</td>\n",
       "      <td>0.001130</td>\n",
       "      <td>0.001031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11555</th>\n",
       "      <td>Banana</td>\n",
       "      <td>Clementines</td>\n",
       "      <td>397</td>\n",
       "      <td>0.013175</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>29798</td>\n",
       "      <td>0.988874</td>\n",
       "      <td>0.000845</td>\n",
       "      <td>0.013323</td>\n",
       "      <td>0.000854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1474</th>\n",
       "      <td>Strawberries</td>\n",
       "      <td>Organic Strawberries</td>\n",
       "      <td>706</td>\n",
       "      <td>0.023429</td>\n",
       "      <td>141805</td>\n",
       "      <td>4.705931</td>\n",
       "      <td>263416</td>\n",
       "      <td>8.741706</td>\n",
       "      <td>0.004979</td>\n",
       "      <td>0.002680</td>\n",
       "      <td>0.000570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7271</th>\n",
       "      <td>Organic Strawberries</td>\n",
       "      <td>Strawberries</td>\n",
       "      <td>640</td>\n",
       "      <td>0.021239</td>\n",
       "      <td>263416</td>\n",
       "      <td>8.741706</td>\n",
       "      <td>141805</td>\n",
       "      <td>4.705931</td>\n",
       "      <td>0.002430</td>\n",
       "      <td>0.004513</td>\n",
       "      <td>0.000516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6763</th>\n",
       "      <td>Organic Hass Avocado</td>\n",
       "      <td>Organic Avocado</td>\n",
       "      <td>464</td>\n",
       "      <td>0.015398</td>\n",
       "      <td>212785</td>\n",
       "      <td>7.061469</td>\n",
       "      <td>176241</td>\n",
       "      <td>5.848722</td>\n",
       "      <td>0.002181</td>\n",
       "      <td>0.002633</td>\n",
       "      <td>0.000373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4387</th>\n",
       "      <td>Organic Avocado</td>\n",
       "      <td>Organic Hass Avocado</td>\n",
       "      <td>443</td>\n",
       "      <td>0.014701</td>\n",
       "      <td>176241</td>\n",
       "      <td>5.848722</td>\n",
       "      <td>212785</td>\n",
       "      <td>7.061469</td>\n",
       "      <td>0.002514</td>\n",
       "      <td>0.002082</td>\n",
       "      <td>0.000356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2596</th>\n",
       "      <td>Banana</td>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>654</td>\n",
       "      <td>0.021704</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>0.001391</td>\n",
       "      <td>0.001738</td>\n",
       "      <td>0.000111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>670</th>\n",
       "      <td>Bag of Organic Bananas</td>\n",
       "      <td>Banana</td>\n",
       "      <td>522</td>\n",
       "      <td>0.017323</td>\n",
       "      <td>376367</td>\n",
       "      <td>12.490090</td>\n",
       "      <td>470096</td>\n",
       "      <td>15.600574</td>\n",
       "      <td>0.001387</td>\n",
       "      <td>0.001110</td>\n",
       "      <td>0.000089</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>48751 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   itemA  \\\n",
       "0       Organic Strawberry Chia Lowfat 2% Cottage Cheese   \n",
       "1                    Grain Free Chicken Formula Cat Food   \n",
       "3              Organic Fruit Yogurt Smoothie Mixed Berry   \n",
       "9      Nonfat Strawberry With Fruit On The Bottom Gre...   \n",
       "10        Organic Grapefruit Ginger Sparkling Yerba Mate   \n",
       "11      Baby Food Pouch - Roasted Carrot Spinach & Beans   \n",
       "12       Unsweetened Whole Milk Mixed Berry Greek Yogurt   \n",
       "23                           Uncured Cracked Pepper Beef   \n",
       "24                                  Organic Mango Yogurt   \n",
       "2                    Grain Free Chicken Formula Cat Food   \n",
       "25                               Raspberry Essence Water   \n",
       "13              Unsweetened Whole Milk Strawberry Yogurt   \n",
       "14             Unsweetened Whole Milk Peach Greek Yogurt   \n",
       "44     Oh My Yog! Pacific Coast Strawberry Trilayer Y...   \n",
       "55     Mighty 4 Kale, Strawberry, Amaranth & Greek Yo...   \n",
       "20             Unsweetened Whole Milk Peach Greek Yogurt   \n",
       "65              0% Greek, Blueberry on the Bottom Yogurt   \n",
       "15       Unsweetened Whole Milk Mixed Berry Greek Yogurt   \n",
       "43             Unsweetened Whole Milk Peach Greek Yogurt   \n",
       "26                          Unsweetened Blackberry Water   \n",
       "19       Unsweetened Whole Milk Mixed Berry Greek Yogurt   \n",
       "16              Unsweetened Whole Milk Strawberry Yogurt   \n",
       "56     Mighty 4 Sweet Potato, Blueberry, Millet & Gre...   \n",
       "74                                Sweet Potatoes Stage 2   \n",
       "79                                     Compostable Forks   \n",
       "75                     Organic Stage 2 Carrots Baby Food   \n",
       "42              Unsweetened Whole Milk Strawberry Yogurt   \n",
       "21         Unsweetened Whole Milk Blueberry Greek Yogurt   \n",
       "17         Unsweetened Whole Milk Blueberry Greek Yogurt   \n",
       "83                            Cream Top Blueberry Yogurt   \n",
       "...                                                  ...   \n",
       "22444                                        Large Lemon   \n",
       "2577                                           Red Onion   \n",
       "250                              Roasted Pine Nut Hummus   \n",
       "655                        Organic Large Green Asparagus   \n",
       "40897                                             Banana   \n",
       "2652                                             Spinach   \n",
       "2722                                          Sour Cream   \n",
       "11143                                Organic Blueberries   \n",
       "2537                                        Green Onions   \n",
       "1386                                 2% Reduced Fat Milk   \n",
       "3291                                 2% Reduced Fat Milk   \n",
       "530                               Chocolate Chip Cookies   \n",
       "10681                                        Half & Half   \n",
       "5446                         Organic Reduced Fat 2% Milk   \n",
       "11455                                             Banana   \n",
       "11421                             Bag of Organic Bananas   \n",
       "2568                 Asparation/Broccolini/Baby Broccoli   \n",
       "19596                                             Banana   \n",
       "2319                                    Fridge Pack Cola   \n",
       "11017                               Organic Baby Spinach   \n",
       "22572                                Organic Raspberries   \n",
       "11012                               Organic Strawberries   \n",
       "246                                                 Soda   \n",
       "11555                                             Banana   \n",
       "1474                                        Strawberries   \n",
       "7271                                Organic Strawberries   \n",
       "6763                                Organic Hass Avocado   \n",
       "4387                                     Organic Avocado   \n",
       "2596                                              Banana   \n",
       "670                               Bag of Organic Bananas   \n",
       "\n",
       "                                                   itemB  freqAB  supportAB  \\\n",
       "0             Organic Cottage Cheese Blueberry Acai Chia     306   0.010155   \n",
       "1                     Grain Free Turkey Formula Cat Food     318   0.010553   \n",
       "3                  Apple Blueberry Fruit Yogurt Smoothie     349   0.011582   \n",
       "9               0% Greek, Blueberry on the Bottom Yogurt     409   0.013573   \n",
       "10            Cranberry Pomegranate Sparkling Yerba Mate     351   0.011648   \n",
       "11     Baby Food Pouch - Butternut Squash, Carrot & C...     332   0.011018   \n",
       "12         Unsweetened Whole Milk Blueberry Greek Yogurt     438   0.014535   \n",
       "23                        Chipotle Beef & Pork Realstick     410   0.013606   \n",
       "24     Organic Whole Milk Washington Black Cherry Yogurt     334   0.011084   \n",
       "2            Grain Free Turkey & Salmon Formula Cat Food     391   0.012976   \n",
       "25                 Unsweetened Pomegranate Essence Water     366   0.012146   \n",
       "13         Unsweetened Whole Milk Blueberry Greek Yogurt     440   0.014602   \n",
       "14         Unsweetened Whole Milk Blueberry Greek Yogurt     421   0.013971   \n",
       "44     Oh My Yog! Organic Wild Quebec Blueberry Cream...     860   0.028540   \n",
       "55     Mighty 4 Essential Tots Spinach, Kiwi, Barley ...     390   0.012943   \n",
       "20              Unsweetened Whole Milk Strawberry Yogurt     499   0.016560   \n",
       "65     Nonfat Strawberry With Fruit On The Bottom Gre...     305   0.010122   \n",
       "15             Unsweetened Whole Milk Peach Greek Yogurt     410   0.013606   \n",
       "43       Unsweetened Whole Milk Mixed Berry Greek Yogurt     407   0.013507   \n",
       "26                 Unsweetened Pomegranate Essence Water     494   0.016394   \n",
       "19              Unsweetened Whole Milk Strawberry Yogurt     383   0.012710   \n",
       "16             Unsweetened Whole Milk Peach Greek Yogurt     444   0.014735   \n",
       "56     Mighty 4 Essential Tots Spinach, Kiwi, Barley ...     398   0.013208   \n",
       "74         Organic Stage 2 Winter Squash Baby Food Puree     322   0.010686   \n",
       "79                                        Plastic Spoons     321   0.010653   \n",
       "75         Organic Stage 2 Winter Squash Baby Food Puree     337   0.011184   \n",
       "42       Unsweetened Whole Milk Mixed Berry Greek Yogurt     352   0.011681   \n",
       "21              Unsweetened Whole Milk Strawberry Yogurt     350   0.011615   \n",
       "17             Unsweetened Whole Milk Peach Greek Yogurt     341   0.011316   \n",
       "83                  Cream Top Peach on the Bottom Yogurt     313   0.010387   \n",
       "...                                                  ...     ...        ...   \n",
       "22444                                      Hass Avocados     468   0.015531   \n",
       "2577                              Bag of Organic Bananas    1008   0.033451   \n",
       "250                                               Banana     327   0.010852   \n",
       "655                                               Banana     556   0.018451   \n",
       "40897                     Organic Extra Virgin Olive Oil     369   0.012246   \n",
       "2652                              Bag of Organic Bananas     383   0.012710   \n",
       "2722                              Bag of Organic Bananas     486   0.016128   \n",
       "11143                                        Blueberries     329   0.010918   \n",
       "2537                              Bag of Organic Bananas     592   0.019646   \n",
       "1386                                Organic Strawberries     574   0.019049   \n",
       "3291                                Organic Baby Spinach     523   0.017356   \n",
       "530                                               Banana     377   0.012511   \n",
       "10681                                Organic Half & Half     302   0.010022   \n",
       "5446                                  Organic Whole Milk     379   0.012577   \n",
       "11455                                               Soda     864   0.028673   \n",
       "11421                                   Fridge Pack Cola     366   0.012146   \n",
       "2568                              Bag of Organic Bananas     317   0.010520   \n",
       "19596                             Organic Tortilla Chips     320   0.010619   \n",
       "2319                              Bag of Organic Bananas     341   0.011316   \n",
       "11017                                2% Reduced Fat Milk     403   0.013374   \n",
       "22572                                        Raspberries     322   0.010686   \n",
       "11012                                2% Reduced Fat Milk     371   0.012312   \n",
       "246                                               Banana     531   0.017622   \n",
       "11555                                        Clementines     397   0.013175   \n",
       "1474                                Organic Strawberries     706   0.023429   \n",
       "7271                                        Strawberries     640   0.021239   \n",
       "6763                                     Organic Avocado     464   0.015398   \n",
       "4387                                Organic Hass Avocado     443   0.014701   \n",
       "2596                              Bag of Organic Bananas     654   0.021704   \n",
       "670                                               Banana     522   0.017323   \n",
       "\n",
       "        freqA   supportA   freqB   supportB  confidenceAtoB  confidenceBtoA  \\\n",
       "0        1163   0.038595     839   0.027843        0.263113        0.364720   \n",
       "1        1809   0.060033     879   0.029170        0.175788        0.361775   \n",
       "3        1518   0.050376    1249   0.041449        0.229908        0.279424   \n",
       "9        1666   0.055288    1391   0.046162        0.245498        0.294033   \n",
       "10       1731   0.057445    1149   0.038131        0.202773        0.305483   \n",
       "11       1503   0.049878    1290   0.042810        0.220892        0.257364   \n",
       "12       1622   0.053828    1621   0.053794        0.270037        0.270204   \n",
       "23       1839   0.061029    1370   0.045465        0.222947        0.299270   \n",
       "24       1675   0.055586    1390   0.046128        0.199403        0.240288   \n",
       "2        1809   0.060033    1553   0.051538        0.216142        0.251771   \n",
       "25       2025   0.067202    1304   0.043274        0.180741        0.280675   \n",
       "13       1965   0.065210    1621   0.053794        0.223919        0.271437   \n",
       "14       1922   0.063783    1621   0.053794        0.219043        0.259716   \n",
       "44       2857   0.094812    2271   0.075365        0.301015        0.378688   \n",
       "55       2206   0.073208    1337   0.044370        0.176791        0.291698   \n",
       "20       1922   0.063783    1965   0.065210        0.259625        0.253944   \n",
       "65       1391   0.046162    1666   0.055288        0.219267        0.183073   \n",
       "15       1622   0.053828    1922   0.063783        0.252774        0.213319   \n",
       "43       1922   0.063783    1622   0.053828        0.211759        0.250925   \n",
       "26       3114   0.103341    1304   0.043274        0.158638        0.378834   \n",
       "19       1622   0.053828    1965   0.065210        0.236128        0.194911   \n",
       "16       1965   0.065210    1922   0.063783        0.225954        0.231009   \n",
       "56       2534   0.084093    1337   0.044370        0.157064        0.297681   \n",
       "74       2077   0.068927    1322   0.043872        0.155031        0.243570   \n",
       "79       1528   0.050708    1838   0.060996        0.210079        0.174646   \n",
       "75       2306   0.076527    1322   0.043872        0.146141        0.254917   \n",
       "42       1965   0.065210    1622   0.053828        0.179135        0.217016   \n",
       "21       1621   0.053794    1965   0.065210        0.215916        0.178117   \n",
       "17       1621   0.053794    1922   0.063783        0.210364        0.177419   \n",
       "83       1676   0.055620    1748   0.058009        0.186754        0.179062   \n",
       "...       ...        ...     ...        ...             ...             ...   \n",
       "22444  152177   5.050136   49246   1.634274        0.003075        0.009503   \n",
       "2577    42906   1.423876  376367  12.490090        0.023493        0.002678   \n",
       "250     11176   0.370886  470096  15.600574        0.029259        0.000696   \n",
       "655     19228   0.638099  470096  15.600574        0.028916        0.001183   \n",
       "40897  470096  15.600574   12788   0.424382        0.000785        0.028855   \n",
       "2652    16766   0.556395  376367  12.490090        0.022844        0.001018   \n",
       "2722    21481   0.712867  376367  12.490090        0.022625        0.001291   \n",
       "11143   99359   3.297321   55703   1.848556        0.003311        0.005906   \n",
       "2537    26467   0.878332  376367  12.490090        0.022367        0.001573   \n",
       "1386    36768   1.220180  263416   8.741706        0.015611        0.002179   \n",
       "3291    36768   1.220180  240637   7.985763        0.014224        0.002173   \n",
       "530     13688   0.454249  470096  15.600574        0.027542        0.000802   \n",
       "10681   68842   2.284586   75334   2.500029        0.004387        0.004009   \n",
       "5446    47593   1.579418  136832   4.540898        0.007963        0.002770   \n",
       "11455  470096  15.600574   33008   1.095401        0.001838        0.026175   \n",
       "11421  376367  12.490090   18005   0.597513        0.000972        0.020328   \n",
       "2568    16480   0.546904  376367  12.490090        0.019235        0.000842   \n",
       "19596  470096  15.600574   13458   0.446616        0.000681        0.023778   \n",
       "2319    18005   0.597513  376367  12.490090        0.018939        0.000906   \n",
       "11017  240637   7.985763   36768   1.220180        0.001675        0.010961   \n",
       "22572  136621   4.533895   56858   1.886886        0.002357        0.005663   \n",
       "11012  263416   8.741706   36768   1.220180        0.001408        0.010090   \n",
       "246     33008   1.095401  470096  15.600574        0.016087        0.001130   \n",
       "11555  470096  15.600574   29798   0.988874        0.000845        0.013323   \n",
       "1474   141805   4.705931  263416   8.741706        0.004979        0.002680   \n",
       "7271   263416   8.741706  141805   4.705931        0.002430        0.004513   \n",
       "6763   212785   7.061469  176241   5.848722        0.002181        0.002633   \n",
       "4387   176241   5.848722  212785   7.061469        0.002514        0.002082   \n",
       "2596   470096  15.600574  376367  12.490090        0.001391        0.001738   \n",
       "670    376367  12.490090  470096  15.600574        0.001387        0.001110   \n",
       "\n",
       "           lift  \n",
       "0      9.449868  \n",
       "1      6.026229  \n",
       "3      5.546732  \n",
       "9      5.318230  \n",
       "10     5.317849  \n",
       "11     5.159830  \n",
       "12     5.019798  \n",
       "23     4.903741  \n",
       "24     4.322777  \n",
       "2      4.193848  \n",
       "25     4.176615  \n",
       "13     4.162489  \n",
       "14     4.071849  \n",
       "44     3.994083  \n",
       "55     3.984498  \n",
       "20     3.981352  \n",
       "65     3.965918  \n",
       "15     3.963014  \n",
       "43     3.934016  \n",
       "26     3.665867  \n",
       "19     3.621024  \n",
       "16     3.542526  \n",
       "56     3.539900  \n",
       "74     3.533734  \n",
       "79     3.444151  \n",
       "75     3.331080  \n",
       "42     3.327938  \n",
       "21     3.311071  \n",
       "17     3.298101  \n",
       "83     3.219399  \n",
       "...         ...  \n",
       "22444  0.001882  \n",
       "2577   0.001881  \n",
       "250    0.001876  \n",
       "655    0.001854  \n",
       "40897  0.001850  \n",
       "2652   0.001829  \n",
       "2722   0.001811  \n",
       "11143  0.001791  \n",
       "2537   0.001791  \n",
       "1386   0.001786  \n",
       "3291   0.001781  \n",
       "530    0.001765  \n",
       "10681  0.001755  \n",
       "5446   0.001754  \n",
       "11455  0.001678  \n",
       "11421  0.001628  \n",
       "2568   0.001540  \n",
       "19596  0.001524  \n",
       "2319   0.001516  \n",
       "11017  0.001373  \n",
       "22572  0.001249  \n",
       "11012  0.001154  \n",
       "246    0.001031  \n",
       "11555  0.000854  \n",
       "1474   0.000570  \n",
       "7271   0.000516  \n",
       "6763   0.000373  \n",
       "4387   0.000356  \n",
       "2596   0.000111  \n",
       "670    0.000089  \n",
       "\n",
       "[48751 rows x 11 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Replace item ID with item name and display association rules\n",
    "item_name   = pd.read_csv('products.csv')\n",
    "item_name   = item_name.rename(columns={'product_id':'item_id', 'product_name':'item_name'})\n",
    "rules_final = merge_item_name(rules, item_name).sort_values('lift', ascending=False)\n",
    "display(rules_final)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 4:  Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the output above, we see that the top associations are not surprising, with one flavor of an item being purchased with another flavor from the same item family (eg: Strawberry Chia Cottage Cheese with Blueberry Acai Cottage Cheese, Chicken Cat Food with Turkey Cat Food, etc).  As mentioned, one common application of association rules mining is in the domain of recommender systems.  Once item pairs have been identified as having positive relationship, recommendations can be made to customers in order to increase sales.  And hopefully, along the way, also introduce customers to items they never would have tried before or even imagined existed!"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}