department_and_aisles_asso.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center>**<span style=\"color:#3f9ae0\">Department and Aisles Association</span>**</center>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are trying to find department and aisles associations. Because we are trying to find the relationships between them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "from mlxtend.frequent_patterns import fpgrowth\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from mlxtend.preprocessing import TransactionEncoder\n",
    "from mlxtend.frequent_patterns import association_rules\n",
    "from mlxtend.frequent_patterns import apriori\n",
    "import matplotlib.pyplot as plt\n",
    "from pyECLAT import ECLAT\n",
    "import time\n",
    "from pycaret.arules import *\n",
    "import plotly.express as px\n",
    "import numpy as np"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <span style=\"color:#6ebdfa\">Transforming the data</span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "transaction_aisle = pd.read_csv('tran_aisels.csv')\n",
    "transaction_department = pd.read_csv('tran_department.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>order_id</th>\n",
       "      <th>products</th>\n",
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      "text/plain": [
       "        order_id                                           products\n",
       "0           3179  water seltzer sparkling water, energy granola ...\n",
       "1           9180  other creams cheeses, canned jarred vegetables...\n",
       "2           4827  soy lactosefree, fresh fruits, fresh fruits, f...\n",
       "3           5933  fresh fruits, fresh fruits, fresh fruits, fres...\n",
       "4           2021  fresh fruits, oils vinegars, fresh vegetables,...\n",
       "...          ...                                                ...\n",
       "131204   1271911                               candy chocolate, tea\n",
       "131205   2694840  fresh fruits, energy granola bars, ice cream i...\n",
       "131206   2487952  candy chocolate, eggs, juice nectars, fresh fr...\n",
       "131207   1032306  nuts seeds dried fruit, packaged cheese, candy...\n",
       "131208   1313098  cookies cakes, water seltzer sparkling water, ...\n",
       "\n",
       "[131209 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transaction_aisle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "        order_id                                           products\n",
       "0           3179  beverages, snacks, snacks, beverages, snacks, ...\n",
       "1           9180             dairy eggs, canned goods, canned goods\n",
       "2           4827  dairy eggs, produce, produce, produce, frozen,...\n",
       "3           5933  produce, produce, produce, produce, produce, p...\n",
       "4           2021  produce, pantry, produce, produce, produce, da...\n",
       "...          ...                                                ...\n",
       "131204   1271911                                  snacks, beverages\n",
       "131205   2694840  produce, snacks, frozen, frozen, dairy eggs, d...\n",
       "131206   2487952  snacks, dairy eggs, beverages, produce, frozen...\n",
       "131207   1032306  snacks, dairy eggs, snacks, snacks, produce, d...\n",
       "131208   1313098  snacks, beverages, beverages, beverages, bever...\n",
       "\n",
       "[131209 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "transaction_department"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <span style=\"color:#6ebdfa\">Association Rules for Aisles</span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an empty list to store the column values\n",
    "column_list = []\n",
    "\n",
    "# Loop over the values in the 'column_name' column and add them to the list\n",
    "for value in transaction_aisle['products']:\n",
    "    my_list = value.split(\",\")\n",
    "    column_list.append(my_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131209 rows × 268 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         air fresheners candles   asian foods   baby accessories  \\\n",
       "0                         False         False              False   \n",
       "1                         False         False              False   \n",
       "2                         False         False              False   \n",
       "3                         False         False              False   \n",
       "4                         False         False              False   \n",
       "...                         ...           ...                ...   \n",
       "131204                    False         False              False   \n",
       "131205                    False         False              False   \n",
       "131206                    False         False              False   \n",
       "131207                    False         False              False   \n",
       "131208                    False         False              False   \n",
       "\n",
       "         baby bath body care   baby food formula   bakery desserts  \\\n",
       "0                      False               False             False   \n",
       "1                      False               False             False   \n",
       "2                      False               False             False   \n",
       "3                      False               False             False   \n",
       "4                      False               False             False   \n",
       "...                      ...                 ...               ...   \n",
       "131204                 False               False             False   \n",
       "131205                 False               False             False   \n",
       "131206                 False               False             False   \n",
       "131207                 False               False             False   \n",
       "131208                 False               False             False   \n",
       "\n",
       "         baking ingredients   baking supplies decor   beauty   beers coolers  \\\n",
       "0                     False                   False    False           False   \n",
       "1                     False                   False    False           False   \n",
       "2                     False                   False    False           False   \n",
       "3                     False                   False    False           False   \n",
       "4                     False                   False    False           False   \n",
       "...                     ...                     ...      ...             ...   \n",
       "131204                False                   False    False           False   \n",
       "131205                False                   False    False           False   \n",
       "131206                 True                   False    False           False   \n",
       "131207                False                   False    False           False   \n",
       "131208                False                   False    False           False   \n",
       "\n",
       "        ...  spreads    tea  tofu meat alternatives  tortillas flat bread  \\\n",
       "0       ...    False  False                   False                 False   \n",
       "1       ...    False  False                   False                 False   \n",
       "2       ...    False  False                   False                 False   \n",
       "3       ...    False  False                   False                 False   \n",
       "4       ...    False  False                   False                 False   \n",
       "...     ...      ...    ...                     ...                   ...   \n",
       "131204  ...    False  False                   False                 False   \n",
       "131205  ...    False  False                   False                 False   \n",
       "131206  ...    False  False                   False                 False   \n",
       "131207  ...    False  False                   False                 False   \n",
       "131208  ...    False  False                   False                 False   \n",
       "\n",
       "        trail mix snack mix  trash bags liners  vitamins supplements  \\\n",
       "0                     False              False                 False   \n",
       "1                     False              False                 False   \n",
       "2                     False              False                 False   \n",
       "3                     False              False                 False   \n",
       "4                     False              False                 False   \n",
       "...                     ...                ...                   ...   \n",
       "131204                False              False                 False   \n",
       "131205                False              False                 False   \n",
       "131206                False              False                 False   \n",
       "131207                False              False                 False   \n",
       "131208                False              False                 False   \n",
       "\n",
       "        water seltzer sparkling water  white wines  yogurt  \n",
       "0                                True        False   False  \n",
       "1                               False        False   False  \n",
       "2                               False        False   False  \n",
       "3                               False        False   False  \n",
       "4                               False        False   False  \n",
       "...                               ...          ...     ...  \n",
       "131204                          False        False   False  \n",
       "131205                          False        False   False  \n",
       "131206                          False        False   False  \n",
       "131207                          False        False   False  \n",
       "131208                          False        False   False  \n",
       "\n",
       "[131209 rows x 268 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "te = TransactionEncoder()\n",
    "te_ary = te.fit(column_list).transform(column_list)\n",
    "df_ = pd.DataFrame(te_ary, columns=te.columns_)\n",
    "df_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_apriori = apriori(df_, min_support=0.09, use_colnames=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>support</th>\n",
       "      <th>itemsets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.147437</td>\n",
       "      <td>( bread)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.091015</td>\n",
       "      <td>( cereal)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.165004</td>\n",
       "      <td>( chips pretzels)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.111928</td>\n",
       "      <td>( crackers)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.126912</td>\n",
       "      <td>( eggs)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.095161</td>\n",
       "      <td>( fresh dips tapenades)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.503426</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.091655</td>\n",
       "      <td>( fresh herbs)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.430108</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.120762</td>\n",
       "      <td>( frozen produce)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.111014</td>\n",
       "      <td>( ice cream ice)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.101030</td>\n",
       "      <td>( lunch meat)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.176253</td>\n",
       "      <td>( milk)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.223925</td>\n",
       "      <td>( packaged cheese)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.358962</td>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.117050</td>\n",
       "      <td>( refrigerated)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.145859</td>\n",
       "      <td>( soy lactosefree)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.165393</td>\n",
       "      <td>( water seltzer sparkling water)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.231417</td>\n",
       "      <td>( yogurt)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.139457</td>\n",
       "      <td>(fresh fruits)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.098553</td>\n",
       "      <td>( fresh fruits,  bread)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.099696</td>\n",
       "      <td>( fresh fruits,  chips pretzels)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.300292</td>\n",
       "      <td>( fresh vegetables,  fresh fruits)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.116326</td>\n",
       "      <td>( fresh fruits,  milk)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.146789</td>\n",
       "      <td>( packaged cheese,  fresh fruits)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.259784</td>\n",
       "      <td>( packaged vegetables fruits,  fresh fruits)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.099521</td>\n",
       "      <td>( fresh fruits,  soy lactosefree)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.095428</td>\n",
       "      <td>( fresh fruits,  water seltzer sparkling water)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.163137</td>\n",
       "      <td>( fresh fruits,  yogurt)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.092783</td>\n",
       "      <td>(fresh fruits,  fresh fruits)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.094574</td>\n",
       "      <td>( fresh vegetables,  milk)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.135235</td>\n",
       "      <td>( packaged cheese,  fresh vegetables)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.235723</td>\n",
       "      <td>( packaged vegetables fruits,  fresh vegetables)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.133520</td>\n",
       "      <td>( fresh vegetables,  yogurt)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.115762</td>\n",
       "      <td>( packaged vegetables fruits,  packaged cheese)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.119717</td>\n",
       "      <td>( packaged vegetables fruits,  yogurt)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.102973</td>\n",
       "      <td>( packaged cheese,  fresh fruits,  fresh veget...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.185262</td>\n",
       "      <td>( packaged vegetables fruits,  fresh vegetable...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.108537</td>\n",
       "      <td>( fresh vegetables,  fresh fruits,  yogurt)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.098065</td>\n",
       "      <td>( packaged vegetables fruits,  fresh fruits,  ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     support                                           itemsets\n",
       "0   0.147437                                           ( bread)\n",
       "1   0.091015                                          ( cereal)\n",
       "2   0.165004                                  ( chips pretzels)\n",
       "3   0.111928                                        ( crackers)\n",
       "4   0.126912                                            ( eggs)\n",
       "5   0.095161                            ( fresh dips tapenades)\n",
       "6   0.503426                                    ( fresh fruits)\n",
       "7   0.091655                                     ( fresh herbs)\n",
       "8   0.430108                                ( fresh vegetables)\n",
       "9   0.120762                                  ( frozen produce)\n",
       "10  0.111014                                   ( ice cream ice)\n",
       "11  0.101030                                      ( lunch meat)\n",
       "12  0.176253                                            ( milk)\n",
       "13  0.223925                                 ( packaged cheese)\n",
       "14  0.358962                      ( packaged vegetables fruits)\n",
       "15  0.117050                                    ( refrigerated)\n",
       "16  0.145859                                 ( soy lactosefree)\n",
       "17  0.165393                   ( water seltzer sparkling water)\n",
       "18  0.231417                                          ( yogurt)\n",
       "19  0.139457                                     (fresh fruits)\n",
       "20  0.098553                            ( fresh fruits,  bread)\n",
       "21  0.099696                   ( fresh fruits,  chips pretzels)\n",
       "22  0.300292                 ( fresh vegetables,  fresh fruits)\n",
       "23  0.116326                             ( fresh fruits,  milk)\n",
       "24  0.146789                  ( packaged cheese,  fresh fruits)\n",
       "25  0.259784       ( packaged vegetables fruits,  fresh fruits)\n",
       "26  0.099521                  ( fresh fruits,  soy lactosefree)\n",
       "27  0.095428    ( fresh fruits,  water seltzer sparkling water)\n",
       "28  0.163137                           ( fresh fruits,  yogurt)\n",
       "29  0.092783                      (fresh fruits,  fresh fruits)\n",
       "30  0.094574                         ( fresh vegetables,  milk)\n",
       "31  0.135235              ( packaged cheese,  fresh vegetables)\n",
       "32  0.235723   ( packaged vegetables fruits,  fresh vegetables)\n",
       "33  0.133520                       ( fresh vegetables,  yogurt)\n",
       "34  0.115762    ( packaged vegetables fruits,  packaged cheese)\n",
       "35  0.119717             ( packaged vegetables fruits,  yogurt)\n",
       "36  0.102973  ( packaged cheese,  fresh fruits,  fresh veget...\n",
       "37  0.185262  ( packaged vegetables fruits,  fresh vegetable...\n",
       "38  0.108537        ( fresh vegetables,  fresh fruits,  yogurt)\n",
       "39  0.098065  ( packaged vegetables fruits,  fresh fruits,  ..."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_apriori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "      <th>zhangs_metric</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>( bread)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.147437</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.098553</td>\n",
       "      <td>0.668441</td>\n",
       "      <td>1.327785</td>\n",
       "      <td>0.024329</td>\n",
       "      <td>1.497697</td>\n",
       "      <td>0.289558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>( chips pretzels)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.165004</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.099696</td>\n",
       "      <td>0.604203</td>\n",
       "      <td>1.200183</td>\n",
       "      <td>0.016629</td>\n",
       "      <td>1.254619</td>\n",
       "      <td>0.199754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.300292</td>\n",
       "      <td>0.698178</td>\n",
       "      <td>1.386855</td>\n",
       "      <td>0.083765</td>\n",
       "      <td>1.645257</td>\n",
       "      <td>0.489468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.300292</td>\n",
       "      <td>0.596497</td>\n",
       "      <td>1.386855</td>\n",
       "      <td>0.083765</td>\n",
       "      <td>1.412361</td>\n",
       "      <td>0.561737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>( milk)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.176253</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.116326</td>\n",
       "      <td>0.659993</td>\n",
       "      <td>1.311004</td>\n",
       "      <td>0.027595</td>\n",
       "      <td>1.460483</td>\n",
       "      <td>0.287984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>( packaged cheese)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.223925</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.146789</td>\n",
       "      <td>0.655526</td>\n",
       "      <td>1.302130</td>\n",
       "      <td>0.034059</td>\n",
       "      <td>1.441542</td>\n",
       "      <td>0.298975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.259784</td>\n",
       "      <td>0.723710</td>\n",
       "      <td>1.437570</td>\n",
       "      <td>0.079073</td>\n",
       "      <td>1.797291</td>\n",
       "      <td>0.474826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.259784</td>\n",
       "      <td>0.516032</td>\n",
       "      <td>1.437570</td>\n",
       "      <td>0.079073</td>\n",
       "      <td>1.324548</td>\n",
       "      <td>0.612963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>( soy lactosefree)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.145859</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.099521</td>\n",
       "      <td>0.682307</td>\n",
       "      <td>1.355329</td>\n",
       "      <td>0.026091</td>\n",
       "      <td>1.563065</td>\n",
       "      <td>0.306942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>( water seltzer sparkling water)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.165393</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.095428</td>\n",
       "      <td>0.576978</td>\n",
       "      <td>1.146103</td>\n",
       "      <td>0.012165</td>\n",
       "      <td>1.173873</td>\n",
       "      <td>0.152740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>( yogurt)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.231417</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.163137</td>\n",
       "      <td>0.704947</td>\n",
       "      <td>1.400299</td>\n",
       "      <td>0.046635</td>\n",
       "      <td>1.682998</td>\n",
       "      <td>0.371940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>(fresh fruits)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.139457</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.092783</td>\n",
       "      <td>0.665319</td>\n",
       "      <td>1.321582</td>\n",
       "      <td>0.022577</td>\n",
       "      <td>1.483722</td>\n",
       "      <td>0.282765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>( milk)</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>0.176253</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.094574</td>\n",
       "      <td>0.536582</td>\n",
       "      <td>1.247553</td>\n",
       "      <td>0.018766</td>\n",
       "      <td>1.229759</td>\n",
       "      <td>0.240888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>( packaged cheese)</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>0.223925</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.135235</td>\n",
       "      <td>0.603928</td>\n",
       "      <td>1.404131</td>\n",
       "      <td>0.038923</td>\n",
       "      <td>1.438859</td>\n",
       "      <td>0.370861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.235723</td>\n",
       "      <td>0.656681</td>\n",
       "      <td>1.526782</td>\n",
       "      <td>0.081331</td>\n",
       "      <td>1.659948</td>\n",
       "      <td>0.538232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.235723</td>\n",
       "      <td>0.548056</td>\n",
       "      <td>1.526782</td>\n",
       "      <td>0.081331</td>\n",
       "      <td>1.418403</td>\n",
       "      <td>0.605426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>( yogurt)</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>0.231417</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.133520</td>\n",
       "      <td>0.576966</td>\n",
       "      <td>1.341446</td>\n",
       "      <td>0.033986</td>\n",
       "      <td>1.347155</td>\n",
       "      <td>0.331175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>( packaged cheese)</td>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>0.223925</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.115762</td>\n",
       "      <td>0.516967</td>\n",
       "      <td>1.440173</td>\n",
       "      <td>0.035381</td>\n",
       "      <td>1.327110</td>\n",
       "      <td>0.393826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>( yogurt)</td>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>0.231417</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.119717</td>\n",
       "      <td>0.517323</td>\n",
       "      <td>1.441165</td>\n",
       "      <td>0.036648</td>\n",
       "      <td>1.328090</td>\n",
       "      <td>0.398288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>( packaged cheese,  fresh fruits)</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>0.146789</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.102973</td>\n",
       "      <td>0.701506</td>\n",
       "      <td>1.631000</td>\n",
       "      <td>0.039838</td>\n",
       "      <td>1.909223</td>\n",
       "      <td>0.453439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>( packaged cheese,  fresh vegetables)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.135235</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.102973</td>\n",
       "      <td>0.761440</td>\n",
       "      <td>1.512518</td>\n",
       "      <td>0.034893</td>\n",
       "      <td>2.081553</td>\n",
       "      <td>0.391841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>( packaged vegetables fruits,  fresh vegetables)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.235723</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.185262</td>\n",
       "      <td>0.785929</td>\n",
       "      <td>1.561162</td>\n",
       "      <td>0.066593</td>\n",
       "      <td>2.319671</td>\n",
       "      <td>0.470316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>( packaged vegetables fruits,  fresh fruits)</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>0.259784</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.185262</td>\n",
       "      <td>0.713137</td>\n",
       "      <td>1.658044</td>\n",
       "      <td>0.073527</td>\n",
       "      <td>1.986638</td>\n",
       "      <td>0.536167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>( fresh vegetables,  fresh fruits)</td>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>0.300292</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.185262</td>\n",
       "      <td>0.616939</td>\n",
       "      <td>1.718676</td>\n",
       "      <td>0.077468</td>\n",
       "      <td>1.673461</td>\n",
       "      <td>0.597616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>( fresh vegetables,  fresh fruits)</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.300292</td>\n",
       "      <td>0.185262</td>\n",
       "      <td>0.516104</td>\n",
       "      <td>1.718676</td>\n",
       "      <td>0.077468</td>\n",
       "      <td>1.445990</td>\n",
       "      <td>0.652311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>( fresh vegetables,  yogurt)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.133520</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.108537</td>\n",
       "      <td>0.812889</td>\n",
       "      <td>1.614714</td>\n",
       "      <td>0.041319</td>\n",
       "      <td>2.653900</td>\n",
       "      <td>0.439358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>( fresh fruits,  yogurt)</td>\n",
       "      <td>( fresh vegetables)</td>\n",
       "      <td>0.163137</td>\n",
       "      <td>0.430108</td>\n",
       "      <td>0.108537</td>\n",
       "      <td>0.665312</td>\n",
       "      <td>1.546849</td>\n",
       "      <td>0.038370</td>\n",
       "      <td>1.702756</td>\n",
       "      <td>0.422440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>( packaged vegetables fruits,  yogurt)</td>\n",
       "      <td>( fresh fruits)</td>\n",
       "      <td>0.119717</td>\n",
       "      <td>0.503426</td>\n",
       "      <td>0.098065</td>\n",
       "      <td>0.819137</td>\n",
       "      <td>1.627125</td>\n",
       "      <td>0.037796</td>\n",
       "      <td>2.745578</td>\n",
       "      <td>0.437836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>( fresh fruits,  yogurt)</td>\n",
       "      <td>( packaged vegetables fruits)</td>\n",
       "      <td>0.163137</td>\n",
       "      <td>0.358962</td>\n",
       "      <td>0.098065</td>\n",
       "      <td>0.601121</td>\n",
       "      <td>1.674611</td>\n",
       "      <td>0.039505</td>\n",
       "      <td>1.607101</td>\n",
       "      <td>0.481377</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         antecedents  \\\n",
       "0                                           ( bread)   \n",
       "1                                  ( chips pretzels)   \n",
       "2                                ( fresh vegetables)   \n",
       "3                                    ( fresh fruits)   \n",
       "4                                            ( milk)   \n",
       "5                                 ( packaged cheese)   \n",
       "6                      ( packaged vegetables fruits)   \n",
       "7                                    ( fresh fruits)   \n",
       "8                                 ( soy lactosefree)   \n",
       "9                   ( water seltzer sparkling water)   \n",
       "10                                         ( yogurt)   \n",
       "11                                    (fresh fruits)   \n",
       "12                                           ( milk)   \n",
       "13                                ( packaged cheese)   \n",
       "14                     ( packaged vegetables fruits)   \n",
       "15                               ( fresh vegetables)   \n",
       "16                                         ( yogurt)   \n",
       "17                                ( packaged cheese)   \n",
       "18                                         ( yogurt)   \n",
       "19                 ( packaged cheese,  fresh fruits)   \n",
       "20             ( packaged cheese,  fresh vegetables)   \n",
       "21  ( packaged vegetables fruits,  fresh vegetables)   \n",
       "22      ( packaged vegetables fruits,  fresh fruits)   \n",
       "23                ( fresh vegetables,  fresh fruits)   \n",
       "24                     ( packaged vegetables fruits)   \n",
       "25                      ( fresh vegetables,  yogurt)   \n",
       "26                          ( fresh fruits,  yogurt)   \n",
       "27            ( packaged vegetables fruits,  yogurt)   \n",
       "28                          ( fresh fruits,  yogurt)   \n",
       "\n",
       "                           consequents  antecedent support  \\\n",
       "0                      ( fresh fruits)            0.147437   \n",
       "1                      ( fresh fruits)            0.165004   \n",
       "2                      ( fresh fruits)            0.430108   \n",
       "3                  ( fresh vegetables)            0.503426   \n",
       "4                      ( fresh fruits)            0.176253   \n",
       "5                      ( fresh fruits)            0.223925   \n",
       "6                      ( fresh fruits)            0.358962   \n",
       "7        ( packaged vegetables fruits)            0.503426   \n",
       "8                      ( fresh fruits)            0.145859   \n",
       "9                      ( fresh fruits)            0.165393   \n",
       "10                     ( fresh fruits)            0.231417   \n",
       "11                     ( fresh fruits)            0.139457   \n",
       "12                 ( fresh vegetables)            0.176253   \n",
       "13                 ( fresh vegetables)            0.223925   \n",
       "14                 ( fresh vegetables)            0.358962   \n",
       "15       ( packaged vegetables fruits)            0.430108   \n",
       "16                 ( fresh vegetables)            0.231417   \n",
       "17       ( packaged vegetables fruits)            0.223925   \n",
       "18       ( packaged vegetables fruits)            0.231417   \n",
       "19                 ( fresh vegetables)            0.146789   \n",
       "20                     ( fresh fruits)            0.135235   \n",
       "21                     ( fresh fruits)            0.235723   \n",
       "22                 ( fresh vegetables)            0.259784   \n",
       "23       ( packaged vegetables fruits)            0.300292   \n",
       "24  ( fresh vegetables,  fresh fruits)            0.358962   \n",
       "25                     ( fresh fruits)            0.133520   \n",
       "26                 ( fresh vegetables)            0.163137   \n",
       "27                     ( fresh fruits)            0.119717   \n",
       "28       ( packaged vegetables fruits)            0.163137   \n",
       "\n",
       "    consequent support   support  confidence      lift  leverage  conviction  \\\n",
       "0             0.503426  0.098553    0.668441  1.327785  0.024329    1.497697   \n",
       "1             0.503426  0.099696    0.604203  1.200183  0.016629    1.254619   \n",
       "2             0.503426  0.300292    0.698178  1.386855  0.083765    1.645257   \n",
       "3             0.430108  0.300292    0.596497  1.386855  0.083765    1.412361   \n",
       "4             0.503426  0.116326    0.659993  1.311004  0.027595    1.460483   \n",
       "5             0.503426  0.146789    0.655526  1.302130  0.034059    1.441542   \n",
       "6             0.503426  0.259784    0.723710  1.437570  0.079073    1.797291   \n",
       "7             0.358962  0.259784    0.516032  1.437570  0.079073    1.324548   \n",
       "8             0.503426  0.099521    0.682307  1.355329  0.026091    1.563065   \n",
       "9             0.503426  0.095428    0.576978  1.146103  0.012165    1.173873   \n",
       "10            0.503426  0.163137    0.704947  1.400299  0.046635    1.682998   \n",
       "11            0.503426  0.092783    0.665319  1.321582  0.022577    1.483722   \n",
       "12            0.430108  0.094574    0.536582  1.247553  0.018766    1.229759   \n",
       "13            0.430108  0.135235    0.603928  1.404131  0.038923    1.438859   \n",
       "14            0.430108  0.235723    0.656681  1.526782  0.081331    1.659948   \n",
       "15            0.358962  0.235723    0.548056  1.526782  0.081331    1.418403   \n",
       "16            0.430108  0.133520    0.576966  1.341446  0.033986    1.347155   \n",
       "17            0.358962  0.115762    0.516967  1.440173  0.035381    1.327110   \n",
       "18            0.358962  0.119717    0.517323  1.441165  0.036648    1.328090   \n",
       "19            0.430108  0.102973    0.701506  1.631000  0.039838    1.909223   \n",
       "20            0.503426  0.102973    0.761440  1.512518  0.034893    2.081553   \n",
       "21            0.503426  0.185262    0.785929  1.561162  0.066593    2.319671   \n",
       "22            0.430108  0.185262    0.713137  1.658044  0.073527    1.986638   \n",
       "23            0.358962  0.185262    0.616939  1.718676  0.077468    1.673461   \n",
       "24            0.300292  0.185262    0.516104  1.718676  0.077468    1.445990   \n",
       "25            0.503426  0.108537    0.812889  1.614714  0.041319    2.653900   \n",
       "26            0.430108  0.108537    0.665312  1.546849  0.038370    1.702756   \n",
       "27            0.503426  0.098065    0.819137  1.627125  0.037796    2.745578   \n",
       "28            0.358962  0.098065    0.601121  1.674611  0.039505    1.607101   \n",
       "\n",
       "    zhangs_metric  \n",
       "0        0.289558  \n",
       "1        0.199754  \n",
       "2        0.489468  \n",
       "3        0.561737  \n",
       "4        0.287984  \n",
       "5        0.298975  \n",
       "6        0.474826  \n",
       "7        0.612963  \n",
       "8        0.306942  \n",
       "9        0.152740  \n",
       "10       0.371940  \n",
       "11       0.282765  \n",
       "12       0.240888  \n",
       "13       0.370861  \n",
       "14       0.538232  \n",
       "15       0.605426  \n",
       "16       0.331175  \n",
       "17       0.393826  \n",
       "18       0.398288  \n",
       "19       0.453439  \n",
       "20       0.391841  \n",
       "21       0.470316  \n",
       "22       0.536167  \n",
       "23       0.597616  \n",
       "24       0.652311  \n",
       "25       0.439358  \n",
       "26       0.422440  \n",
       "27       0.437836  \n",
       "28       0.481377  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rule_APRIORI = association_rules(df_apriori, metric=\"confidence\", min_threshold= 0.5)\n",
    "rule_APRIORI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "metadata": {},
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   "source": [
    "plot_model(rule_APRIORI, plot = '3d')"
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   "metadata": {},
   "source": [
    "## <span style=\"color:#6ebdfa\">Association Rules for departments</span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an empty list to store the column values\n",
    "column_list = []\n",
    "\n",
    "# Loop over the values in the 'column_name' column and add them to the list\n",
    "for value in transaction_department[\"products\"]:\n",
    "    my_list = value.split(\",\")\n",
    "    column_list.append(my_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
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       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131204</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131205</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131206</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131207</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131208</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131209 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         alcohol   babies   bakery   beverages   breakfast   bulk  \\\n",
       "0          False    False    False        True       False  False   \n",
       "1          False    False    False       False       False  False   \n",
       "2          False    False    False       False       False  False   \n",
       "3          False    False     True       False       False  False   \n",
       "4          False    False     True        True       False  False   \n",
       "...          ...      ...      ...         ...         ...    ...   \n",
       "131204     False    False    False        True       False  False   \n",
       "131205     False    False    False        True       False  False   \n",
       "131206     False    False     True        True        True  False   \n",
       "131207     False    False    False        True       False  False   \n",
       "131208     False    False     True        True       False  False   \n",
       "\n",
       "         canned goods   dairy eggs   deli   dry goods pasta  ...  household  \\\n",
       "0               False        False  False             False  ...      False   \n",
       "1                True        False  False             False  ...      False   \n",
       "2                True         True   True              True  ...      False   \n",
       "3                True         True  False             False  ...      False   \n",
       "4                True         True  False             False  ...      False   \n",
       "...               ...          ...    ...               ...  ...        ...   \n",
       "131204          False        False  False             False  ...      False   \n",
       "131205          False         True  False             False  ...      False   \n",
       "131206           True         True  False              True  ...      False   \n",
       "131207           True         True  False             False  ...      False   \n",
       "131208           True         True  False             False  ...      False   \n",
       "\n",
       "        international  meat seafood  missing  other  pantry  personal care  \\\n",
       "0               False         False    False  False   False          False   \n",
       "1               False         False    False  False   False          False   \n",
       "2               False         False    False  False   False          False   \n",
       "3               False         False    False  False   False          False   \n",
       "4               False         False    False  False   False          False   \n",
       "...               ...           ...      ...    ...     ...            ...   \n",
       "131204          False         False    False  False   False          False   \n",
       "131205          False         False    False  False   False          False   \n",
       "131206          False         False    False  False   False          False   \n",
       "131207          False         False    False  False   False          False   \n",
       "131208          False         False    False  False   False          False   \n",
       "\n",
       "         pets  produce  snacks  \n",
       "0       False    False   False  \n",
       "1       False    False   False  \n",
       "2       False    False   False  \n",
       "3       False     True   False  \n",
       "4       False     True   False  \n",
       "...       ...      ...     ...  \n",
       "131204  False    False    True  \n",
       "131205  False     True   False  \n",
       "131206  False    False    True  \n",
       "131207  False    False    True  \n",
       "131208  False    False    True  \n",
       "\n",
       "[131209 rows x 42 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "te = TransactionEncoder()\n",
    "te_ary = te.fit(column_list).transform(column_list)\n",
    "df_ = pd.DataFrame(te_ary, columns=te.columns_)\n",
    "df_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_apriori = apriori(df_, min_support=0.09, use_colnames=True)"
   ]
  },
  {
   "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>support</th>\n",
       "      <th>itemsets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.253321</td>\n",
       "      <td>( bakery)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.405887</td>\n",
       "      <td>( beverages)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.155264</td>\n",
       "      <td>( breakfast)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.212516</td>\n",
       "      <td>( canned goods)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.608845</td>\n",
       "      <td>( dairy eggs)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>0.091625</td>\n",
       "      <td>( snacks,  beverages,  produce,  frozen)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>0.098377</td>\n",
       "      <td>( snacks,  deli,  dairy eggs,  produce)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>0.115930</td>\n",
       "      <td>( pantry,  dairy eggs,  produce,  frozen)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>0.135707</td>\n",
       "      <td>( snacks,  dairy eggs,  produce,  frozen)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>0.123414</td>\n",
       "      <td>( snacks,  pantry,  dairy eggs,  produce)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>134 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      support                                   itemsets\n",
       "0    0.253321                                  ( bakery)\n",
       "1    0.405887                               ( beverages)\n",
       "2    0.155264                               ( breakfast)\n",
       "3    0.212516                            ( canned goods)\n",
       "4    0.608845                              ( dairy eggs)\n",
       "..        ...                                        ...\n",
       "129  0.091625   ( snacks,  beverages,  produce,  frozen)\n",
       "130  0.098377    ( snacks,  deli,  dairy eggs,  produce)\n",
       "131  0.115930  ( pantry,  dairy eggs,  produce,  frozen)\n",
       "132  0.135707  ( snacks,  dairy eggs,  produce,  frozen)\n",
       "133  0.123414  ( snacks,  pantry,  dairy eggs,  produce)\n",
       "\n",
       "[134 rows x 2 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_apriori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "      <th>zhangs_metric</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>( bakery)</td>\n",
       "      <td>( dairy eggs)</td>\n",
       "      <td>0.253321</td>\n",
       "      <td>0.608845</td>\n",
       "      <td>0.202905</td>\n",
       "      <td>0.800981</td>\n",
       "      <td>1.315573</td>\n",
       "      <td>0.048672</td>\n",
       "      <td>1.965411</td>\n",
       "      <td>0.321256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>( bakery)</td>\n",
       "      <td>( produce)</td>\n",
       "      <td>0.253321</td>\n",
       "      <td>0.698199</td>\n",
       "      <td>0.210542</td>\n",
       "      <td>0.831127</td>\n",
       "      <td>1.190387</td>\n",
       "      <td>0.033673</td>\n",
       "      <td>1.787148</td>\n",
       "      <td>0.214198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>( breakfast)</td>\n",
       "      <td>( dairy eggs)</td>\n",
       "      <td>0.155264</td>\n",
       "      <td>0.608845</td>\n",
       "      <td>0.124763</td>\n",
       "      <td>0.803554</td>\n",
       "      <td>1.319800</td>\n",
       "      <td>0.030231</td>\n",
       "      <td>1.991155</td>\n",
       "      <td>0.286846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>( canned goods)</td>\n",
       "      <td>( produce)</td>\n",
       "      <td>0.212516</td>\n",
       "      <td>0.698199</td>\n",
       "      <td>0.183989</td>\n",
       "      <td>0.865765</td>\n",
       "      <td>1.239998</td>\n",
       "      <td>0.035610</td>\n",
       "      <td>2.248308</td>\n",
       "      <td>0.245779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>( dry goods pasta)</td>\n",
       "      <td>( dairy eggs)</td>\n",
       "      <td>0.187335</td>\n",
       "      <td>0.608845</td>\n",
       "      <td>0.151461</td>\n",
       "      <td>0.808503</td>\n",
       "      <td>1.327928</td>\n",
       "      <td>0.037403</td>\n",
       "      <td>2.042613</td>\n",
       "      <td>0.303873</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>( pantry,  produce,  frozen)</td>\n",
       "      <td>( dairy eggs)</td>\n",
       "      <td>0.136286</td>\n",
       "      <td>0.608845</td>\n",
       "      <td>0.115930</td>\n",
       "      <td>0.850632</td>\n",
       "      <td>1.397123</td>\n",
       "      <td>0.032952</td>\n",
       "      <td>2.618729</td>\n",
       "      <td>0.329094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>( snacks,  dairy eggs,  frozen)</td>\n",
       "      <td>( produce)</td>\n",
       "      <td>0.156506</td>\n",
       "      <td>0.698199</td>\n",
       "      <td>0.135707</td>\n",
       "      <td>0.867105</td>\n",
       "      <td>1.241917</td>\n",
       "      <td>0.026435</td>\n",
       "      <td>2.270972</td>\n",
       "      <td>0.230936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>( snacks,  produce,  frozen)</td>\n",
       "      <td>( dairy eggs)</td>\n",
       "      <td>0.160500</td>\n",
       "      <td>0.608845</td>\n",
       "      <td>0.135707</td>\n",
       "      <td>0.845529</td>\n",
       "      <td>1.388742</td>\n",
       "      <td>0.037988</td>\n",
       "      <td>2.532224</td>\n",
       "      <td>0.333441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>( snacks,  pantry,  dairy eggs)</td>\n",
       "      <td>( produce)</td>\n",
       "      <td>0.140623</td>\n",
       "      <td>0.698199</td>\n",
       "      <td>0.123414</td>\n",
       "      <td>0.877622</td>\n",
       "      <td>1.256979</td>\n",
       "      <td>0.025231</td>\n",
       "      <td>2.466133</td>\n",
       "      <td>0.237896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>( snacks,  pantry,  produce)</td>\n",
       "      <td>( dairy eggs)</td>\n",
       "      <td>0.146126</td>\n",
       "      <td>0.608845</td>\n",
       "      <td>0.123414</td>\n",
       "      <td>0.844573</td>\n",
       "      <td>1.387172</td>\n",
       "      <td>0.034446</td>\n",
       "      <td>2.516647</td>\n",
       "      <td>0.326873</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>82 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        antecedents    consequents  antecedent support  \\\n",
       "0                         ( bakery)  ( dairy eggs)            0.253321   \n",
       "1                         ( bakery)     ( produce)            0.253321   \n",
       "2                      ( breakfast)  ( dairy eggs)            0.155264   \n",
       "3                   ( canned goods)     ( produce)            0.212516   \n",
       "4                ( dry goods pasta)  ( dairy eggs)            0.187335   \n",
       "..                              ...            ...                 ...   \n",
       "77     ( pantry,  produce,  frozen)  ( dairy eggs)            0.136286   \n",
       "78  ( snacks,  dairy eggs,  frozen)     ( produce)            0.156506   \n",
       "79     ( snacks,  produce,  frozen)  ( dairy eggs)            0.160500   \n",
       "80  ( snacks,  pantry,  dairy eggs)     ( produce)            0.140623   \n",
       "81     ( snacks,  pantry,  produce)  ( dairy eggs)            0.146126   \n",
       "\n",
       "    consequent support   support  confidence      lift  leverage  conviction  \\\n",
       "0             0.608845  0.202905    0.800981  1.315573  0.048672    1.965411   \n",
       "1             0.698199  0.210542    0.831127  1.190387  0.033673    1.787148   \n",
       "2             0.608845  0.124763    0.803554  1.319800  0.030231    1.991155   \n",
       "3             0.698199  0.183989    0.865765  1.239998  0.035610    2.248308   \n",
       "4             0.608845  0.151461    0.808503  1.327928  0.037403    2.042613   \n",
       "..                 ...       ...         ...       ...       ...         ...   \n",
       "77            0.608845  0.115930    0.850632  1.397123  0.032952    2.618729   \n",
       "78            0.698199  0.135707    0.867105  1.241917  0.026435    2.270972   \n",
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       "\n",
       "    zhangs_metric  \n",
       "0        0.321256  \n",
       "1        0.214198  \n",
       "2        0.286846  \n",
       "3        0.245779  \n",
       "4        0.303873  \n",
       "..            ...  \n",
       "77       0.329094  \n",
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       "79       0.333441  \n",
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       "81       0.326873  \n",
       "\n",
       "[82 rows x 10 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rule_APRIORI = association_rules(df_apriori, metric=\"confidence\", min_threshold= 0.8)\n",
    "rule_APRIORI"
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  },
  {
   "cell_type": "code",
   "execution_count": 31,
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