Assignment-Association-Rules-Books.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "61412bfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mlxtend.frequent_patterns import apriori,association_rules\n",
    "from mlxtend.preprocessing import TransactionEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "81d021c6",
   "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>ChildBks</th>\n",
       "      <th>YouthBks</th>\n",
       "      <th>CookBks</th>\n",
       "      <th>DoItYBks</th>\n",
       "      <th>RefBks</th>\n",
       "      <th>ArtBks</th>\n",
       "      <th>GeogBks</th>\n",
       "      <th>ItalCook</th>\n",
       "      <th>ItalAtlas</th>\n",
       "      <th>ItalArt</th>\n",
       "      <th>Florence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>1995</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      ChildBks  YouthBks  CookBks  DoItYBks  RefBks  ArtBks  GeogBks  \\\n",
       "0            0         1        0         1       0       0        1   \n",
       "1            1         0        0         0       0       0        0   \n",
       "2            0         0        0         0       0       0        0   \n",
       "3            1         1        1         0       1       0        1   \n",
       "4            0         0        1         0       0       0        1   \n",
       "...        ...       ...      ...       ...     ...     ...      ...   \n",
       "1995         0         0        1         0       0       1        1   \n",
       "1996         0         0        0         0       0       0        0   \n",
       "1997         0         0        0         0       0       0        0   \n",
       "1998         0         0        1         0       0       0        0   \n",
       "1999         0         0        0         0       0       0        0   \n",
       "\n",
       "      ItalCook  ItalAtlas  ItalArt  Florence  \n",
       "0            0          0        0         0  \n",
       "1            0          0        0         0  \n",
       "2            0          0        0         0  \n",
       "3            0          0        0         0  \n",
       "4            0          0        0         0  \n",
       "...        ...        ...      ...       ...  \n",
       "1995         1          0        1         1  \n",
       "1996         0          0        0         0  \n",
       "1997         0          0        0         0  \n",
       "1998         0          0        0         0  \n",
       "1999         0          0        0         0  \n",
       "\n",
       "[2000 rows x 11 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import Dataset\n",
    "book=pd.read_csv('book.csv')\n",
    "book"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b1196378",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data preprocessing not required as it is already in transaction format"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab525856",
   "metadata": {},
   "source": [
    "# Apriori Algorithm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77cdcaf6",
   "metadata": {},
   "source": [
    "# 1. Association rules with 10% Support and 70% confidence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f7611cd6",
   "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>0.4230</td>\n",
       "      <td>(ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.2475</td>\n",
       "      <td>(YouthBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.4310</td>\n",
       "      <td>(CookBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.2820</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.2145</td>\n",
       "      <td>(RefBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.2410</td>\n",
       "      <td>(ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.2760</td>\n",
       "      <td>(GeogBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.1135</td>\n",
       "      <td>(ItalCook)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.1085</td>\n",
       "      <td>(Florence)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.1650</td>\n",
       "      <td>(YouthBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.2560</td>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.1840</td>\n",
       "      <td>(DoItYBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.1515</td>\n",
       "      <td>(RefBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.1625</td>\n",
       "      <td>(ArtBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.1950</td>\n",
       "      <td>(GeogBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.1620</td>\n",
       "      <td>(CookBks, YouthBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.1155</td>\n",
       "      <td>(YouthBks, DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.1010</td>\n",
       "      <td>(YouthBks, ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.1205</td>\n",
       "      <td>(GeogBks, YouthBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.1875</td>\n",
       "      <td>(CookBks, DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.1525</td>\n",
       "      <td>(CookBks, RefBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.1670</td>\n",
       "      <td>(CookBks, ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.1925</td>\n",
       "      <td>(CookBks, GeogBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.1135</td>\n",
       "      <td>(ItalCook, CookBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.1055</td>\n",
       "      <td>(RefBks, DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.1235</td>\n",
       "      <td>(DoItYBks, ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.1325</td>\n",
       "      <td>(GeogBks, DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.1105</td>\n",
       "      <td>(GeogBks, RefBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.1275</td>\n",
       "      <td>(GeogBks, ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.1290</td>\n",
       "      <td>(CookBks, YouthBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.1460</td>\n",
       "      <td>(CookBks, DoItYBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.1225</td>\n",
       "      <td>(CookBks, RefBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.1265</td>\n",
       "      <td>(CookBks, ArtBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.1495</td>\n",
       "      <td>(CookBks, GeogBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.1045</td>\n",
       "      <td>(GeogBks, DoItYBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.1020</td>\n",
       "      <td>(GeogBks, ArtBks, ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.1015</td>\n",
       "      <td>(CookBks, DoItYBks, ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.1085</td>\n",
       "      <td>(CookBks, GeogBks, DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.1035</td>\n",
       "      <td>(CookBks, GeogBks, ArtBks)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    support                       itemsets\n",
       "0    0.4230                     (ChildBks)\n",
       "1    0.2475                     (YouthBks)\n",
       "2    0.4310                      (CookBks)\n",
       "3    0.2820                     (DoItYBks)\n",
       "4    0.2145                       (RefBks)\n",
       "5    0.2410                       (ArtBks)\n",
       "6    0.2760                      (GeogBks)\n",
       "7    0.1135                     (ItalCook)\n",
       "8    0.1085                     (Florence)\n",
       "9    0.1650           (YouthBks, ChildBks)\n",
       "10   0.2560            (CookBks, ChildBks)\n",
       "11   0.1840           (DoItYBks, ChildBks)\n",
       "12   0.1515             (RefBks, ChildBks)\n",
       "13   0.1625             (ArtBks, ChildBks)\n",
       "14   0.1950            (GeogBks, ChildBks)\n",
       "15   0.1620            (CookBks, YouthBks)\n",
       "16   0.1155           (YouthBks, DoItYBks)\n",
       "17   0.1010             (YouthBks, ArtBks)\n",
       "18   0.1205            (GeogBks, YouthBks)\n",
       "19   0.1875            (CookBks, DoItYBks)\n",
       "20   0.1525              (CookBks, RefBks)\n",
       "21   0.1670              (CookBks, ArtBks)\n",
       "22   0.1925             (CookBks, GeogBks)\n",
       "23   0.1135            (ItalCook, CookBks)\n",
       "24   0.1055             (RefBks, DoItYBks)\n",
       "25   0.1235             (DoItYBks, ArtBks)\n",
       "26   0.1325            (GeogBks, DoItYBks)\n",
       "27   0.1105              (GeogBks, RefBks)\n",
       "28   0.1275              (GeogBks, ArtBks)\n",
       "29   0.1290  (CookBks, YouthBks, ChildBks)\n",
       "30   0.1460  (CookBks, DoItYBks, ChildBks)\n",
       "31   0.1225    (CookBks, RefBks, ChildBks)\n",
       "32   0.1265    (CookBks, ArtBks, ChildBks)\n",
       "33   0.1495   (CookBks, GeogBks, ChildBks)\n",
       "34   0.1045  (GeogBks, DoItYBks, ChildBks)\n",
       "35   0.1020    (GeogBks, ArtBks, ChildBks)\n",
       "36   0.1015    (CookBks, DoItYBks, ArtBks)\n",
       "37   0.1085   (CookBks, GeogBks, DoItYBks)\n",
       "38   0.1035     (CookBks, GeogBks, ArtBks)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With 10% Support\n",
    "frequent_itemsets=apriori(book,min_support=0.1,use_colnames=True)\n",
    "frequent_itemsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3f3d120e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.576044</td>\n",
       "      <td>0.060308</td>\n",
       "      <td>1.731000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.390071</td>\n",
       "      <td>1.576044</td>\n",
       "      <td>0.060308</td>\n",
       "      <td>1.233750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.593968</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.421069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.605201</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.441240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2820</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1840</td>\n",
       "      <td>0.652482</td>\n",
       "      <td>1.542511</td>\n",
       "      <td>0.064714</td>\n",
       "      <td>1.660347</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>(CookBks, ArtBks)</td>\n",
       "      <td>(GeogBks)</td>\n",
       "      <td>0.1670</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.619760</td>\n",
       "      <td>2.245509</td>\n",
       "      <td>0.057408</td>\n",
       "      <td>1.904063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>(GeogBks, ArtBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.1275</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.811765</td>\n",
       "      <td>1.883445</td>\n",
       "      <td>0.048547</td>\n",
       "      <td>3.022812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(GeogBks, ArtBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.1275</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.240139</td>\n",
       "      <td>1.883445</td>\n",
       "      <td>0.048547</td>\n",
       "      <td>1.148237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>(GeogBks)</td>\n",
       "      <td>(CookBks, ArtBks)</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.1670</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>2.245509</td>\n",
       "      <td>0.057408</td>\n",
       "      <td>1.332800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>(ArtBks)</td>\n",
       "      <td>(CookBks, GeogBks)</td>\n",
       "      <td>0.2410</td>\n",
       "      <td>0.1925</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.429461</td>\n",
       "      <td>2.230964</td>\n",
       "      <td>0.057107</td>\n",
       "      <td>1.415327</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          antecedents         consequents  antecedent support  \\\n",
       "0          (YouthBks)          (ChildBks)              0.2475   \n",
       "1          (ChildBks)          (YouthBks)              0.4230   \n",
       "2           (CookBks)          (ChildBks)              0.4310   \n",
       "3          (ChildBks)           (CookBks)              0.4230   \n",
       "4          (DoItYBks)          (ChildBks)              0.2820   \n",
       "..                ...                 ...                 ...   \n",
       "95  (CookBks, ArtBks)           (GeogBks)              0.1670   \n",
       "96  (GeogBks, ArtBks)           (CookBks)              0.1275   \n",
       "97          (CookBks)   (GeogBks, ArtBks)              0.4310   \n",
       "98          (GeogBks)   (CookBks, ArtBks)              0.2760   \n",
       "99           (ArtBks)  (CookBks, GeogBks)              0.2410   \n",
       "\n",
       "    consequent support  support  confidence      lift  leverage  conviction  \n",
       "0               0.4230   0.1650    0.666667  1.576044  0.060308    1.731000  \n",
       "1               0.2475   0.1650    0.390071  1.576044  0.060308    1.233750  \n",
       "2               0.4230   0.2560    0.593968  1.404179  0.073687    1.421069  \n",
       "3               0.4310   0.2560    0.605201  1.404179  0.073687    1.441240  \n",
       "4               0.4230   0.1840    0.652482  1.542511  0.064714    1.660347  \n",
       "..                 ...      ...         ...       ...       ...         ...  \n",
       "95              0.2760   0.1035    0.619760  2.245509  0.057408    1.904063  \n",
       "96              0.4310   0.1035    0.811765  1.883445  0.048547    3.022812  \n",
       "97              0.1275   0.1035    0.240139  1.883445  0.048547    1.148237  \n",
       "98              0.1670   0.1035    0.375000  2.245509  0.057408    1.332800  \n",
       "99              0.1925   0.1035    0.429461  2.230964  0.057107    1.415327  \n",
       "\n",
       "[100 rows x 9 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# with 70% confidence\n",
    "rules=association_rules(frequent_itemsets,metric='lift',min_threshold=0.7)\n",
    "rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a0fdb027",
   "metadata": {},
   "outputs": [],
   "source": [
    "## A leverage value of 0 indicates independence. Range will be [-1 1]\n",
    "## A high conviction value means that the consequent is highly depending on the antecedent and range [0 inf]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "56fe4d3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(ItalCook)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.1135</td>\n",
       "      <td>0.1135</td>\n",
       "      <td>0.263341</td>\n",
       "      <td>2.320186</td>\n",
       "      <td>0.064582</td>\n",
       "      <td>1.203406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>(ItalCook)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.1135</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.1135</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.320186</td>\n",
       "      <td>0.064582</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>(ChildBks, ArtBks)</td>\n",
       "      <td>(GeogBks)</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.1020</td>\n",
       "      <td>0.627692</td>\n",
       "      <td>2.274247</td>\n",
       "      <td>0.057150</td>\n",
       "      <td>1.944628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>(GeogBks)</td>\n",
       "      <td>(ChildBks, ArtBks)</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.1020</td>\n",
       "      <td>0.369565</td>\n",
       "      <td>2.274247</td>\n",
       "      <td>0.057150</td>\n",
       "      <td>1.328448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>(ArtBks)</td>\n",
       "      <td>(CookBks, DoItYBks)</td>\n",
       "      <td>0.2410</td>\n",
       "      <td>0.1875</td>\n",
       "      <td>0.1015</td>\n",
       "      <td>0.421162</td>\n",
       "      <td>2.246196</td>\n",
       "      <td>0.056313</td>\n",
       "      <td>1.403674</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2820</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1840</td>\n",
       "      <td>0.652482</td>\n",
       "      <td>1.542511</td>\n",
       "      <td>0.064714</td>\n",
       "      <td>1.660347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.1620</td>\n",
       "      <td>0.375870</td>\n",
       "      <td>1.518667</td>\n",
       "      <td>0.055328</td>\n",
       "      <td>1.205678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.1620</td>\n",
       "      <td>0.654545</td>\n",
       "      <td>1.518667</td>\n",
       "      <td>0.055328</td>\n",
       "      <td>1.647105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.605201</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.441240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.593968</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.421069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           antecedents          consequents  antecedent support  \\\n",
       "29           (CookBks)           (ItalCook)              0.4310   \n",
       "28          (ItalCook)            (CookBks)              0.1135   \n",
       "78  (ChildBks, ArtBks)            (GeogBks)              0.1625   \n",
       "79           (GeogBks)   (ChildBks, ArtBks)              0.2760   \n",
       "87            (ArtBks)  (CookBks, DoItYBks)              0.2410   \n",
       "..                 ...                  ...                 ...   \n",
       "4           (DoItYBks)           (ChildBks)              0.2820   \n",
       "12           (CookBks)           (YouthBks)              0.4310   \n",
       "13          (YouthBks)            (CookBks)              0.2475   \n",
       "3           (ChildBks)            (CookBks)              0.4230   \n",
       "2            (CookBks)           (ChildBks)              0.4310   \n",
       "\n",
       "    consequent support  support  confidence      lift  leverage  conviction  \n",
       "29              0.1135   0.1135    0.263341  2.320186  0.064582    1.203406  \n",
       "28              0.4310   0.1135    1.000000  2.320186  0.064582         inf  \n",
       "78              0.2760   0.1020    0.627692  2.274247  0.057150    1.944628  \n",
       "79              0.1625   0.1020    0.369565  2.274247  0.057150    1.328448  \n",
       "87              0.1875   0.1015    0.421162  2.246196  0.056313    1.403674  \n",
       "..                 ...      ...         ...       ...       ...         ...  \n",
       "4               0.4230   0.1840    0.652482  1.542511  0.064714    1.660347  \n",
       "12              0.2475   0.1620    0.375870  1.518667  0.055328    1.205678  \n",
       "13              0.4310   0.1620    0.654545  1.518667  0.055328    1.647105  \n",
       "3               0.4310   0.2560    0.605201  1.404179  0.073687    1.441240  \n",
       "2               0.4230   0.2560    0.593968  1.404179  0.073687    1.421069  \n",
       "\n",
       "[100 rows x 9 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rules.sort_values('lift',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "69c50932",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.576044</td>\n",
       "      <td>0.060308</td>\n",
       "      <td>1.731000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.390071</td>\n",
       "      <td>1.576044</td>\n",
       "      <td>0.060308</td>\n",
       "      <td>1.233750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.593968</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.421069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.605201</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.441240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2820</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1840</td>\n",
       "      <td>0.652482</td>\n",
       "      <td>1.542511</td>\n",
       "      <td>0.064714</td>\n",
       "      <td>1.660347</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>(CookBks, ArtBks)</td>\n",
       "      <td>(GeogBks)</td>\n",
       "      <td>0.1670</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.619760</td>\n",
       "      <td>2.245509</td>\n",
       "      <td>0.057408</td>\n",
       "      <td>1.904063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>(GeogBks, ArtBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.1275</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.811765</td>\n",
       "      <td>1.883445</td>\n",
       "      <td>0.048547</td>\n",
       "      <td>3.022812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(GeogBks, ArtBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.1275</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.240139</td>\n",
       "      <td>1.883445</td>\n",
       "      <td>0.048547</td>\n",
       "      <td>1.148237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>(GeogBks)</td>\n",
       "      <td>(CookBks, ArtBks)</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.1670</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>2.245509</td>\n",
       "      <td>0.057408</td>\n",
       "      <td>1.332800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>(ArtBks)</td>\n",
       "      <td>(CookBks, GeogBks)</td>\n",
       "      <td>0.2410</td>\n",
       "      <td>0.1925</td>\n",
       "      <td>0.1035</td>\n",
       "      <td>0.429461</td>\n",
       "      <td>2.230964</td>\n",
       "      <td>0.057107</td>\n",
       "      <td>1.415327</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          antecedents         consequents  antecedent support  \\\n",
       "0          (YouthBks)          (ChildBks)              0.2475   \n",
       "1          (ChildBks)          (YouthBks)              0.4230   \n",
       "2           (CookBks)          (ChildBks)              0.4310   \n",
       "3          (ChildBks)           (CookBks)              0.4230   \n",
       "4          (DoItYBks)          (ChildBks)              0.2820   \n",
       "..                ...                 ...                 ...   \n",
       "95  (CookBks, ArtBks)           (GeogBks)              0.1670   \n",
       "96  (GeogBks, ArtBks)           (CookBks)              0.1275   \n",
       "97          (CookBks)   (GeogBks, ArtBks)              0.4310   \n",
       "98          (GeogBks)   (CookBks, ArtBks)              0.2760   \n",
       "99           (ArtBks)  (CookBks, GeogBks)              0.2410   \n",
       "\n",
       "    consequent support  support  confidence      lift  leverage  conviction  \n",
       "0               0.4230   0.1650    0.666667  1.576044  0.060308    1.731000  \n",
       "1               0.2475   0.1650    0.390071  1.576044  0.060308    1.233750  \n",
       "2               0.4230   0.2560    0.593968  1.404179  0.073687    1.421069  \n",
       "3               0.4310   0.2560    0.605201  1.404179  0.073687    1.441240  \n",
       "4               0.4230   0.1840    0.652482  1.542511  0.064714    1.660347  \n",
       "..                 ...      ...         ...       ...       ...         ...  \n",
       "95              0.2760   0.1035    0.619760  2.245509  0.057408    1.904063  \n",
       "96              0.4310   0.1035    0.811765  1.883445  0.048547    3.022812  \n",
       "97              0.1275   0.1035    0.240139  1.883445  0.048547    1.148237  \n",
       "98              0.1670   0.1035    0.375000  2.245509  0.057408    1.332800  \n",
       "99              0.1925   0.1035    0.429461  2.230964  0.057107    1.415327  \n",
       "\n",
       "[100 rows x 9 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lift Ratio > 1 is a good influential rule in selecting the associated transactions\n",
    "rules[rules.lift>1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f454a9db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of obtained rule\n",
    "plt.scatter(rules['support'],rules['confidence'])\n",
    "plt.xlabel('support')\n",
    "plt.ylabel('confidence') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "575f3f9a",
   "metadata": {},
   "source": [
    "# 2. Association rules with 20% Support and 60% confidence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ca31ba21",
   "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>0.4230</td>\n",
       "      <td>(ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.2475</td>\n",
       "      <td>(YouthBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.4310</td>\n",
       "      <td>(CookBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.2820</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.2145</td>\n",
       "      <td>(RefBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.2410</td>\n",
       "      <td>(ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.2760</td>\n",
       "      <td>(GeogBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.2560</td>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   support             itemsets\n",
       "0   0.4230           (ChildBks)\n",
       "1   0.2475           (YouthBks)\n",
       "2   0.4310            (CookBks)\n",
       "3   0.2820           (DoItYBks)\n",
       "4   0.2145             (RefBks)\n",
       "5   0.2410             (ArtBks)\n",
       "6   0.2760            (GeogBks)\n",
       "7   0.2560  (CookBks, ChildBks)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With 20% Support\n",
    "frequent_itemsets2=apriori(book,min_support=0.20,use_colnames=True)\n",
    "frequent_itemsets2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "22ed5e60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.431</td>\n",
       "      <td>0.423</td>\n",
       "      <td>0.256</td>\n",
       "      <td>0.593968</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.421069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.423</td>\n",
       "      <td>0.431</td>\n",
       "      <td>0.256</td>\n",
       "      <td>0.605201</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.441240</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  antecedents consequents  antecedent support  consequent support  support  \\\n",
       "0   (CookBks)  (ChildBks)               0.431               0.423    0.256   \n",
       "1  (ChildBks)   (CookBks)               0.423               0.431    0.256   \n",
       "\n",
       "   confidence      lift  leverage  conviction  \n",
       "0    0.593968  1.404179  0.073687    1.421069  \n",
       "1    0.605201  1.404179  0.073687    1.441240  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With 60% confidence\n",
    "rules2=association_rules(frequent_itemsets2,metric='lift',min_threshold=0.6)\n",
    "rules2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e4bf7305",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZwAAAEGCAYAAABRvCMcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAX5ElEQVR4nO3df7AdZZ3n8ffHBNZAqSCBURIQtIAVXBS4xlFHJv4EkQVlnBF/lNTowsLClsyUaBh3LVf/WBFnZrdqcdgIuDM6KzsKxswgRNYVdBfR3ACBBIxkKIQQhIAiE8gIge/+cTrmcOsm9yQ53Tc5eb+qTp3TT/fT5/vQkA9Pn053qgpJktr2vOkuQJK0ezBwJEmdMHAkSZ0wcCRJnTBwJEmdmDndBXRh9uzZdcghh0x3GZK0S1m2bNkjVbX/sPa3WwTOIYccwvj4+HSXIUm7lCQ/H+b+PKUmSeqEgSNJ6oSBI0nqhIEjSeqEgSNJ6sRucZWatLNZdOsDXLxkFWsf28CB+8zighOO4N3HzJnusqRWGThSxxbd+gAXXn0HG55+BoAHHtvAhVffAWDoaKR5Sk3q2MVLVv02bDbZ8PQzXLxk1TRVJHXDwJE6tvaxDdvULo0KA0fq2IH7zNqmdmlUGDhSxy444Qhm7THjOW2z9pjBBSccMU0VSd3wogGpY5suDPAqNe1uDBxpGrz7mDkGjHY7nlKTJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHWi1cBJcmKSVUlWJ1mwhW3mJ7ktycokNw7aN8nHk1SS2W2OQZI0HK09niDJDOAS4O3AGmBpksVVdWffNvsAXwJOrKr7khwwSN8kBzXr7murfknScLU5w5kHrK6qe6rqKeBK4NQJ23wAuLqq7gOoqocH7PuXwCeAarF+SdIQtRk4c4D7+5bXNG39Dgf2TXJDkmVJPjxV3ySnAA9U1fKtfXmSs5KMJxlft27djoxDkjQEbT7xM5O0TZyRzASOA94KzAJ+lOTmLfVNshfwKeAdU315VS0EFgKMjY05E5KkadZm4KwBDupbngusnWSbR6rqCeCJJD8AXr2Vvq8ADgWWJ9nUfkuSeVX1i1ZGIUkaijZPqS0FDktyaJI9gdOBxRO2+TbwpiQzm9nL64C7ttS3qu6oqgOq6pCqOoReMB1r2EjSzq+1GU5VbUxyHrAEmAFcUVUrk5zdrL+0qu5Kch1wO/AscFlVrQCYrG9btUqS2peq0f95Y2xsrMbHx6e7DEnapSRZVlVjw9qfdxqQJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJEkdaLVwElyYpJVSVYnWbCFbeYnuS3JyiQ3TtU3ycVJfprk9iTfSrJPm2OQJA1Ha4GTZAZwCfBO4Ejg/UmOnLDNPsCXgFOq6ijgDwfoez3wqqo6GvgZcGFbY5AkDU+bM5x5wOqquqeqngKuBE6dsM0HgKur6j6Aqnp4qr5V9d2q2thsdzMwt8UxSJKGpM3AmQPc37e8pmnrdziwb5IbkixL8uFt6AvwEeDaIdUrSWrRzBb3nUnaapLvPw54KzAL+FGSmwfpm+RTwEbgbyf98uQs4CyAgw8+eJsKlyQNX5sznDXAQX3Lc4G1k2xzXVU9UVWPAD8AXj1V3yRnACcDH6yqiSEGQFUtrKqxqhrbf//9d3gwkqQd02bgLAUOS3Jokj2B04HFE7b5NvCmJDOT7AW8Drhra32TnAh8kt6FBk+2WL8kaYhaO6VWVRuTnAcsAWYAV1TVyiRnN+svraq7klwH3A48C1xWVSsAJuvb7Pq/Af8CuD4JwM1VdXZb45AkDUe2cEZqpIyNjdX4+Ph0lyFJu5Qky6pqbFj7804DkqROGDiSpE4YOJKkThg4kqROGDiSpE4YOJKkThg4kqROGDiSpE4YOJKkThg4kqROGDiSpE4YOJKkTgwcOEleluRtzedZSV7QXlmSpFEzUOAkORP4JvDfm6a5wKKWapIkjaBBZzjnAm8EHgeoqruBA9oqSpI0egYNnN9U1VObFpLMBEb/QTqSpKEZNHBuTPJnwKwkbwe+Afx9e2VJkkbNoIGzAFgH3AH8W+A7wH9oqyhJ0uiZOeB2s4ArqurLAElmNG1PtlWYJGm0DDrD+R69gNlkFvC/h1+OJGlUDRo4z6+q9ZsWms97tVOSJGkUDRo4TyQ5dtNCkuOADe2UJEkaRYP+hnM+8I0ka5vllwLva6UiSdJIGihwqmppkn8JHAEE+GlVPd1qZZKkkTLoDAfgtcAhTZ9jklBVf9NKVZKkkTNQ4CT5KvAK4Dbgmaa5AANHkjSQQWc4Y8CRVeXtbCRJ22XQq9RWAC/Z1p0nOTHJqiSrkyzYwjbzk9yWZGWSG6fqm+TFSa5Pcnfzvu+21iVJ6t6ggTMbuDPJkiSLN7221qG5G8ElwDuBI4H3Jzlywjb7AF8CTqmqo4A/HKDvAuB7VXUYvb+QOmmQSZJ2LoOeUvvMdux7HrC6qu4BSHIlcCpwZ982HwCurqr7AKrq4QH6ngrMb7b7a+AG4JPbUZ8kqUMDzXCq6kbgXmCP5vNS4JYpus0B7u9bXtO09Tsc2DfJDUmWJfnwAH1/p6oebOp6kC08lyfJWUnGk4yvW7duilIlSW3b3id+zmHqJ35mkraJFx3MBI4D3gWcAPzHJIcP2HerqmphVY1V1dj++++/LV0lSS1o84mfa4CD+pbnAmsn2ea6qnqiqh4BfgC8eoq+DyV5KUDz/jCSpJ1em0/8XAocluTQJHsCpwMTLzT4NvCmJDOT7AW8Drhrir6LgTOaz2c0+5Ak7eQGvWhg4hM//x1TPPGzqjYmOQ9YAsyg9zydlUnObtZfWlV3JbkOuB14FrisqlYATNa32fXngb9L8lHgPpor2yRJO7cM8nc5kzwP+CjwDnq/ryyhFw67xF8EHRsbq/Hx8ekuQ5J2KUmWVdXYsPY36M07nwW+3LwkSdpmWw2cJHewld9qqurooVckSRpJU81wTm7ez23ev9q8fxB4spWKJEkjaauBU1U/B0jyxqp6Y9+qBUn+H/DZNouTJI2OQS+L3jvJ721aSPIGYO92SpIkjaJBL4v+KHBFkhc1y48BH2mlIknSSBr0KrVlwKuTvJDepdS/brcsSdKomeoqtQ9V1deS/OmEdgCq6i9arE2SNEKmmuHs1by/oO1CJEmjbarAeUXzfmdVfaPtYiRJo2uqq9ROSrIHcGEXxUiSRtdUM5zrgEfoXRb9eF97gKqqF7ZWmSRppGx1hlNVF1TVi4BrquqFfa8XGDaSpG0x6COmT227EEnSaBv0EdOnJbk7ya+TPJ7knyacYpMkaasGvdPAF4B/XVV3tVmMJGl0DXovtYcMG0nSjhh0hjOe5H8Bi4DfbGqsqqvbKEqSNHoGDZwX0nv+zTv62gowcCRJAxn05p1/3HYhkqTRNuhVanOTfCvJw0keSnJVkrltFydJGh2DXjTwFWAxcCAwB/j7pk2SpIEMGjj7V9VXqmpj8/ofwP4t1iVJGjGDBs4jST6UZEbz+hDwaJuFSZJGy6CB8xHgj4BfAA8C7wW8kECSNLBBL4v+HHBGVf0KIMmLgS/SCyJJkqY06Azn6E1hA1BVvwSOmapTkhOTrEqyOsmCSdbPb+7Pdlvz+nTfuo8lWZFkZZLz+9pfk+TmZvvxJPMGHIMkaRoNOsN5XpJ9J8xwtto3yQzgEuDtwBpgaZLFVXXnhE1/WFUnT+j7KuBMYB7wFHBdkmuq6m5693X7T1V1bZKTmuX5A45DkjRNBp3h/DlwU5LPJfkscBO9P+i3Zh6wuqruqaqngCuBQR9z8Erg5qp6sqo2AjcC72nWFb07HwC8CFg74D4lSdNo0Ofh/A3wB8BDwDrgtKr66hTd5gD39y2vadomen2S5UmuTXJU07YCOD7Jfkn2Ak4CDmrWnQ9cnOR+er8jTfr46yRnNafcxtetWzf1ICVJrRr0lBrNqbCJp8O2JpPtZsLyLcDLqmp9c3psEXBYVd2V5CLgemA9sBzY2PQ5B/iTqroqyR8BlwNvm6TehcBCgLGxsYnfK0nq2KCn1LbHGjbPSgDmMuH0V1U9XlXrm8/fAfZIMrtZvryqjq2q44FfAnc33c5g801Dv0Hv1J0kaSfXZuAsBQ5LcmiSPYHT6d0e57eSvCRJms/zmnoebZYPaN4PBk4Dvt50Wwv8fvP5LWwOIknSTmzgU2rbqqo2JjkPWALMAK6oqpVJzm7WX0rvL5Cek2QjsAE4vao2nf66Ksl+wNPAuX2XZZ8J/NckM4F/Bs5qawySpOHJ5j/fR9fY2FiNj49PdxmStEtJsqyqxoa1vzZPqUmS9FsGjiSpEwaOJKkTBo4kqRMGjiSpEwaOJKkTBo4kqRMGjiSpEwaOJKkTBo4kqRMGjiSpEwaOJKkTBo4kqRMGjiSpEwaOJKkTBo4kqRMGjiSpEwaOJKkTBo4kqRMGjiSpEwaOJKkTBo4kqRMGjiSpEwaOJKkTBo4kqRMGjiSpE60GTpITk6xKsjrJgknWz0/y6yS3Na9P9637WJIVSVYmOX9Cv3/f7Hdlki+0OQZJ0nDMbGvHSWYAlwBvB9YAS5Msrqo7J2z6w6o6eULfVwFnAvOAp4DrklxTVXcneTNwKnB0Vf0myQFtjUGSNDxtznDmAaur6p6qegq4kl5QDOKVwM1V9WRVbQRuBN7TrDsH+HxV/Qagqh4ect2SpBa0GThzgPv7ltc0bRO9PsnyJNcmOappWwEcn2S/JHsBJwEHNesOB96U5MdJbkzy2sm+PMlZScaTjK9bt244I5IkbbfWTqkBmaStJizfArysqtYnOQlYBBxWVXcluQi4HlgPLAc2Nn1mAvsCvwu8Fvi7JC+vqufsu6oWAgsBxsbGJn6vJKljbc5w1rB5VgIwF1jbv0FVPV5V65vP3wH2SDK7Wb68qo6tquOBXwJ39+336ur5CfAsMLvFcUiShqDNwFkKHJbk0CR7AqcDi/s3SPKSJGk+z2vqebRZPqB5Pxg4Dfh6020R8JZm3eHAnsAjLY5DkjQErZ1Sq6qNSc4DlgAzgCuqamWSs5v1lwLvBc5JshHYAJzed2rsqiT7AU8D51bVr5r2K4ArkqygdwXbGRNPp0mSdj7ZHf6sHhsbq/Hx8ekuQ5J2KUmWVdXYsPbnnQYkSZ0wcCRJnTBwJEmdMHAkSZ0wcCRJnTBwJEmdMHAkSZ0wcCRJnTBwJEmdMHAkSZ0wcCRJnTBwJEmdMHAkSZ0wcCRJnTBwJEmdMHAkSZ0wcCRJnTBwJEmdMHAkSZ0wcCRJnTBwJEmdMHAkSZ0wcCRJnTBwJEmdMHAkSZ0wcCRJnWg1cJKcmGRVktVJFkyyfn6SXye5rXl9um/dx5KsSLIyyfmT9P14kkoyu80xSJKGY2ZbO04yA7gEeDuwBliaZHFV3Tlh0x9W1ckT+r4KOBOYBzwFXJfkmqq6u1l/ULPf+9qqX2rTolsf4OIlq1j72AYO3GcWF5xwBO8+Zs50lyW1qs0ZzjxgdVXdU1VPAVcCpw7Y95XAzVX1ZFVtBG4E3tO3/i+BTwA1zIKlLiy69QEuvPoOHnhsAwU88NgGLrz6Dhbd+sB0lya1qs3AmQPc37e8pmmb6PVJlie5NslRTdsK4Pgk+yXZCzgJOAggySnAA1W1fGtfnuSsJONJxtetW7fDg5GG5eIlq9jw9DPPadvw9DNcvGTVNFUkdaO1U2pAJmmbOCO5BXhZVa1PchKwCDisqu5KchFwPbAeWA5sbMLnU8A7pvryqloILAQYGxtzJqSdxtrHNmxTuzQq2pzhrKGZlTTmAmv7N6iqx6tqffP5O8Aemy4CqKrLq+rYqjoe+CVwN/AK4FBgeZJ7m33ekuQlLY5DGqoD95m1Te3SqGgzcJYChyU5NMmewOnA4v4NkrwkSZrP85p6Hm2WD2jeDwZOA75eVXdU1QFVdUhVHUIv1I6tql+0OA5pqC444Qhm7THjOW2z9pjBBSccMU0VSd1o7ZRaVW1Mch6wBJgBXFFVK5Oc3ay/FHgvcE6SjcAG4PSq2nT666ok+wFPA+dW1a/aqlXq0qar0bxKTbubbP7zfXSNjY3V+Pj4dJchSbuUJMuqamxY+/NOA5KkThg4kqROGDiSpE4YOJKkThg4kqRO7BZXqSVZB/x8uuuYYDbwyHQX0RHHOrp2p/HuTmOF3nj3rqr9h7XD3SJwdkZJxod5ueHOzLGOrt1pvLvTWKGd8XpKTZLUCQNHktQJA2f6LJzuAjrkWEfX7jTe3Wms0MJ4/Q1HktQJZziSpE4YOJKkThg4Q5DkxCSrkqxOsmCS9R9McnvzuinJqyesn5Hk1iT/0Nf2mSQPJLmteZ3UxVimsiNjTXJvkjua8Yz3tb84yfVJ7m7e9+1qPFNpabyjeGz3SfLNJD9NcleS1zfto3pstzTekTq2SY7oG8ttSR5Pcn6zbtuPbVX52oEXvWf9/CPwcmBPeo/DPnLCNm8A9m0+vxP48YT1fwr8T+Af+to+A3x8usc3zLEC9wKzJ9nvF4AFzecFwEXTPdaWxzuKx/avgX/TfN4T2GfEj+2Wxjtyx3bCfn4BvGx7j60znB03D1hdVfdU1VPAlcCp/RtU1U21+QFyN9N7NDYASeYC7wIu66jeHbFDY92KU+n9B0zz/u7hlLvD2hrvzmi7x5rkhcDxwOXNdk9V1WPNdiN3bKcY785oWP8evxX4x6radNeWbT62Bs6OmwPc37e8pmnbko8C1/Yt/xfgE8Czk2x7XjPFvWInORWxo2Mt4LtJliU5q6/9d6rqQYDm/YAh1buj2hovjNaxfTmwDvhKc2r4siR7N+tG8dhubbwwWse23+nA1/uWt/nYGjg7LpO0TXqteZI30zuYn2yWTwYerqplk2z+V8ArgNcADwJ/Poxid9B2j7Xxxqo6lt6U/dwkxw+/xKFqa7yjdmxnAscCf1VVxwBP0DvFsjNra7yjdmw3te8JnAJ8Y0cKMXB23BrgoL7lucDaiRslOZreabNTq+rRpvmNwClJ7qU3zX1Lkq8BVNVDVfVMVT0LfJnetHi67chYqaq1zfvDwLfYPKaHkry06ftS4OFWqt92rYx3BI/tGmBNVf24Wf4mvT+QYTSP7RbHO4LHdpN3ArdU1UN9bdt+bKf7B61d/UXv/3buAQ5l8w9yR03Y5mBgNfCGrexnPs+9aOClfZ//BLhyVx4rsDfwgr7PNwEnNssX89wfH78w3WNtebwjdWybdT8Ejmg+fwa4eFSP7RTjHblj26y/EvjjCW3bfGyn/cCPwgs4CfgZvStBPtW0nQ2c3Xy+DPgVcFvzGp9kH/N5buB8FbgDuB1Y3P8v8q44VnrnvZc3r5Wb+jbr9gO+B9zdvL94usfZ8nhH6tg2614DjDdjWsTmK55G7thOMd5RPLZ7AY8CL5qwz20+tt7aRpLUCX/DkSR1wsCRJHXCwJEkdcLAkSR1wsCRJHXCwJF2YUnOT7LXdNchDcLLoqVdVJJNdwEeq6pHprseaSrOcKTtkGTvJNckWZ5kRZL3Nc+/md2sH0tyQ/P5M0m+muT/NM8OObNpn5/kB0m+leTOJJcmeV6z7v3pPUtnRZKL+r53fZLPJvkx8CngQOD7Sb7f9T8DaVvNnO4CpF3UicDaqnoXQJIXARdtZfujgd+ld5ubW5Nc07TPA44Efg5cB5yW5KZmX8fR+9vf303y7qpa1PRfUVWfbr73I8CbneFoV+AMR9o+dwBvS3JRkjdV1a+n2P7bVbWhCYbvs/mmjj+p3nNKnqF36/ffA14L3FBV66pqI/C39J6/AvAMcNXQRyN1wBmOtB2q6mdJjqN3j6r/nOS7wEY2/0/c8yd22cLyZO2T3U5+k39uwkna5TjDkbZDkgOBJ6vqa8AX6d2e/l56p8EA/mBCl1OTPD/JfvRu1Lq0aZ+X5NDmt5v3Af8X+DHw+0lmNxcGvB+4cQul/BPwguGMSmqXMxxp+/wr4OIkzwJPA+cAs4DLk/wZvdDo9xPgGnq3gf9cVa1NcjjwI+Dzzf5+AHyrqp5NciG9U28BvlNV395CHQuBa5M8WFVvHu4QpeHysmipZUk+A6yvqi9OaJ8PfLyqTp6GsqTOeUpNktQJZziSpE44w5EkdcLAkSR1wsCRJHXCwJEkdcLAkSR14v8DBiRfpApHoBQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of obtained rule\n",
    "plt.scatter(rules2['support'],rules2['confidence'])\n",
    "plt.xlabel('support')\n",
    "plt.ylabel('confidence') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c028093",
   "metadata": {},
   "source": [
    "# 3. Association rules with 5% Support and 80% confidence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a32b1a36",
   "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>0.4230</td>\n",
       "      <td>(ChildBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.2475</td>\n",
       "      <td>(YouthBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.4310</td>\n",
       "      <td>(CookBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.2820</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.2145</td>\n",
       "      <td>(RefBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.0600</td>\n",
       "      <td>(CookBks, GeogBks, YouthBks, DoItYBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>0.0560</td>\n",
       "      <td>(CookBks, GeogBks, YouthBks, ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.0650</td>\n",
       "      <td>(CookBks, GeogBks, DoItYBks, ArtBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.0510</td>\n",
       "      <td>(CookBks, YouthBks, ChildBks, DoItYBks, GeogBks)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>0.0535</td>\n",
       "      <td>(CookBks, ArtBks, ChildBks, DoItYBks, GeogBks)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    support                                          itemsets\n",
       "0    0.4230                                        (ChildBks)\n",
       "1    0.2475                                        (YouthBks)\n",
       "2    0.4310                                         (CookBks)\n",
       "3    0.2820                                        (DoItYBks)\n",
       "4    0.2145                                          (RefBks)\n",
       "..      ...                                               ...\n",
       "95   0.0600            (CookBks, GeogBks, YouthBks, DoItYBks)\n",
       "96   0.0560              (CookBks, GeogBks, YouthBks, ArtBks)\n",
       "97   0.0650              (CookBks, GeogBks, DoItYBks, ArtBks)\n",
       "98   0.0510  (CookBks, YouthBks, ChildBks, DoItYBks, GeogBks)\n",
       "99   0.0535    (CookBks, ArtBks, ChildBks, DoItYBks, GeogBks)\n",
       "\n",
       "[100 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With 5% Support\n",
    "frequent_itemsets3=apriori(book,min_support=0.05,use_colnames=True)\n",
    "frequent_itemsets3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9497de20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.576044</td>\n",
       "      <td>0.060308</td>\n",
       "      <td>1.731000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.390071</td>\n",
       "      <td>1.576044</td>\n",
       "      <td>0.060308</td>\n",
       "      <td>1.233750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.593968</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.421069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.605201</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.441240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2820</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1840</td>\n",
       "      <td>0.652482</td>\n",
       "      <td>1.542511</td>\n",
       "      <td>0.064714</td>\n",
       "      <td>1.660347</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>657</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(GeogBks, ChildBks, DoItYBks, ArtBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.0595</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.124130</td>\n",
       "      <td>2.086217</td>\n",
       "      <td>0.027856</td>\n",
       "      <td>1.073789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>658</th>\n",
       "      <td>(ArtBks)</td>\n",
       "      <td>(CookBks, GeogBks, DoItYBks, ChildBks)</td>\n",
       "      <td>0.2410</td>\n",
       "      <td>0.0890</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.221992</td>\n",
       "      <td>2.494289</td>\n",
       "      <td>0.032051</td>\n",
       "      <td>1.170939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>659</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(CookBks, GeogBks, DoItYBks, ArtBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.0650</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.126478</td>\n",
       "      <td>1.945808</td>\n",
       "      <td>0.026005</td>\n",
       "      <td>1.070379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>660</th>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>(CookBks, GeogBks, ChildBks, ArtBks)</td>\n",
       "      <td>0.2820</td>\n",
       "      <td>0.0835</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.189716</td>\n",
       "      <td>2.272052</td>\n",
       "      <td>0.029953</td>\n",
       "      <td>1.131085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>661</th>\n",
       "      <td>(GeogBks)</td>\n",
       "      <td>(CookBks, ChildBks, DoItYBks, ArtBks)</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.0820</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.193841</td>\n",
       "      <td>2.363910</td>\n",
       "      <td>0.030868</td>\n",
       "      <td>1.138733</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>662 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    antecedents                             consequents  antecedent support  \\\n",
       "0    (YouthBks)                              (ChildBks)              0.2475   \n",
       "1    (ChildBks)                              (YouthBks)              0.4230   \n",
       "2     (CookBks)                              (ChildBks)              0.4310   \n",
       "3    (ChildBks)                               (CookBks)              0.4230   \n",
       "4    (DoItYBks)                              (ChildBks)              0.2820   \n",
       "..          ...                                     ...                 ...   \n",
       "657   (CookBks)   (GeogBks, ChildBks, DoItYBks, ArtBks)              0.4310   \n",
       "658    (ArtBks)  (CookBks, GeogBks, DoItYBks, ChildBks)              0.2410   \n",
       "659  (ChildBks)    (CookBks, GeogBks, DoItYBks, ArtBks)              0.4230   \n",
       "660  (DoItYBks)    (CookBks, GeogBks, ChildBks, ArtBks)              0.2820   \n",
       "661   (GeogBks)   (CookBks, ChildBks, DoItYBks, ArtBks)              0.2760   \n",
       "\n",
       "     consequent support  support  confidence      lift  leverage  conviction  \n",
       "0                0.4230   0.1650    0.666667  1.576044  0.060308    1.731000  \n",
       "1                0.2475   0.1650    0.390071  1.576044  0.060308    1.233750  \n",
       "2                0.4230   0.2560    0.593968  1.404179  0.073687    1.421069  \n",
       "3                0.4310   0.2560    0.605201  1.404179  0.073687    1.441240  \n",
       "4                0.4230   0.1840    0.652482  1.542511  0.064714    1.660347  \n",
       "..                  ...      ...         ...       ...       ...         ...  \n",
       "657              0.0595   0.0535    0.124130  2.086217  0.027856    1.073789  \n",
       "658              0.0890   0.0535    0.221992  2.494289  0.032051    1.170939  \n",
       "659              0.0650   0.0535    0.126478  1.945808  0.026005    1.070379  \n",
       "660              0.0835   0.0535    0.189716  2.272052  0.029953    1.131085  \n",
       "661              0.0820   0.0535    0.193841  2.363910  0.030868    1.138733  \n",
       "\n",
       "[662 rows x 9 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With 80% confidence\n",
    "rules3=association_rules(frequent_itemsets3,metric='lift',min_threshold=0.8)\n",
    "rules3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fb1014d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.576044</td>\n",
       "      <td>0.060308</td>\n",
       "      <td>1.731000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2475</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.390071</td>\n",
       "      <td>1.576044</td>\n",
       "      <td>0.060308</td>\n",
       "      <td>1.233750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.593968</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.421069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.2560</td>\n",
       "      <td>0.605201</td>\n",
       "      <td>1.404179</td>\n",
       "      <td>0.073687</td>\n",
       "      <td>1.441240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.2820</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.1840</td>\n",
       "      <td>0.652482</td>\n",
       "      <td>1.542511</td>\n",
       "      <td>0.064714</td>\n",
       "      <td>1.660347</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>657</th>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>(GeogBks, ChildBks, DoItYBks, ArtBks)</td>\n",
       "      <td>0.4310</td>\n",
       "      <td>0.0595</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.124130</td>\n",
       "      <td>2.086217</td>\n",
       "      <td>0.027856</td>\n",
       "      <td>1.073789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>658</th>\n",
       "      <td>(ArtBks)</td>\n",
       "      <td>(CookBks, GeogBks, DoItYBks, ChildBks)</td>\n",
       "      <td>0.2410</td>\n",
       "      <td>0.0890</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.221992</td>\n",
       "      <td>2.494289</td>\n",
       "      <td>0.032051</td>\n",
       "      <td>1.170939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>659</th>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>(CookBks, GeogBks, DoItYBks, ArtBks)</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.0650</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.126478</td>\n",
       "      <td>1.945808</td>\n",
       "      <td>0.026005</td>\n",
       "      <td>1.070379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>660</th>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>(CookBks, GeogBks, ChildBks, ArtBks)</td>\n",
       "      <td>0.2820</td>\n",
       "      <td>0.0835</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.189716</td>\n",
       "      <td>2.272052</td>\n",
       "      <td>0.029953</td>\n",
       "      <td>1.131085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>661</th>\n",
       "      <td>(GeogBks)</td>\n",
       "      <td>(CookBks, ChildBks, DoItYBks, ArtBks)</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.0820</td>\n",
       "      <td>0.0535</td>\n",
       "      <td>0.193841</td>\n",
       "      <td>2.363910</td>\n",
       "      <td>0.030868</td>\n",
       "      <td>1.138733</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>662 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    antecedents                             consequents  antecedent support  \\\n",
       "0    (YouthBks)                              (ChildBks)              0.2475   \n",
       "1    (ChildBks)                              (YouthBks)              0.4230   \n",
       "2     (CookBks)                              (ChildBks)              0.4310   \n",
       "3    (ChildBks)                               (CookBks)              0.4230   \n",
       "4    (DoItYBks)                              (ChildBks)              0.2820   \n",
       "..          ...                                     ...                 ...   \n",
       "657   (CookBks)   (GeogBks, ChildBks, DoItYBks, ArtBks)              0.4310   \n",
       "658    (ArtBks)  (CookBks, GeogBks, DoItYBks, ChildBks)              0.2410   \n",
       "659  (ChildBks)    (CookBks, GeogBks, DoItYBks, ArtBks)              0.4230   \n",
       "660  (DoItYBks)    (CookBks, GeogBks, ChildBks, ArtBks)              0.2820   \n",
       "661   (GeogBks)   (CookBks, ChildBks, DoItYBks, ArtBks)              0.2760   \n",
       "\n",
       "     consequent support  support  confidence      lift  leverage  conviction  \n",
       "0                0.4230   0.1650    0.666667  1.576044  0.060308    1.731000  \n",
       "1                0.2475   0.1650    0.390071  1.576044  0.060308    1.233750  \n",
       "2                0.4230   0.2560    0.593968  1.404179  0.073687    1.421069  \n",
       "3                0.4310   0.2560    0.605201  1.404179  0.073687    1.441240  \n",
       "4                0.4230   0.1840    0.652482  1.542511  0.064714    1.660347  \n",
       "..                  ...      ...         ...       ...       ...         ...  \n",
       "657              0.0595   0.0535    0.124130  2.086217  0.027856    1.073789  \n",
       "658              0.0890   0.0535    0.221992  2.494289  0.032051    1.170939  \n",
       "659              0.0650   0.0535    0.126478  1.945808  0.026005    1.070379  \n",
       "660              0.0835   0.0535    0.189716  2.272052  0.029953    1.131085  \n",
       "661              0.0820   0.0535    0.193841  2.363910  0.030868    1.138733  \n",
       "\n",
       "[662 rows x 9 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rules3[rules3.lift>1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "804a1b50",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization of obtained rule\n",
    "plt.scatter(rules3['support'],rules3['confidence'])\n",
    "plt.xlabel('support')\n",
    "plt.ylabel('confidence') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d36d3d7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}