Market-Basket-Analysis-Apyori-Association-Rule.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ce25cbce",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Needed Libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "45712695",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading the dataset\n",
    "df = pd.read_csv('store_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "09f2a25e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>shrimp</th>\n",
       "      <th>almonds</th>\n",
       "      <th>avocado</th>\n",
       "      <th>vegetables mix</th>\n",
       "      <th>green grapes</th>\n",
       "      <th>whole weat flour</th>\n",
       "      <th>yams</th>\n",
       "      <th>cottage cheese</th>\n",
       "      <th>energy drink</th>\n",
       "      <th>tomato juice</th>\n",
       "      <th>low fat yogurt</th>\n",
       "      <th>green tea</th>\n",
       "      <th>honey</th>\n",
       "      <th>salad</th>\n",
       "      <th>mineral water</th>\n",
       "      <th>salmon</th>\n",
       "      <th>antioxydant juice</th>\n",
       "      <th>frozen smoothie</th>\n",
       "      <th>spinach</th>\n",
       "      <th>olive oil</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>burgers</td>\n",
       "      <td>meatballs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chutney</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>turkey</td>\n",
       "      <td>avocado</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>mineral water</td>\n",
       "      <td>milk</td>\n",
       "      <td>energy bar</td>\n",
       "      <td>whole wheat rice</td>\n",
       "      <td>green tea</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>low fat yogurt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           shrimp    almonds     avocado    vegetables mix green grapes  \\\n",
       "0         burgers  meatballs        eggs               NaN          NaN   \n",
       "1         chutney        NaN         NaN               NaN          NaN   \n",
       "2          turkey    avocado         NaN               NaN          NaN   \n",
       "3   mineral water       milk  energy bar  whole wheat rice    green tea   \n",
       "4  low fat yogurt        NaN         NaN               NaN          NaN   \n",
       "\n",
       "  whole weat flour yams cottage cheese energy drink tomato juice  \\\n",
       "0              NaN  NaN            NaN          NaN          NaN   \n",
       "1              NaN  NaN            NaN          NaN          NaN   \n",
       "2              NaN  NaN            NaN          NaN          NaN   \n",
       "3              NaN  NaN            NaN          NaN          NaN   \n",
       "4              NaN  NaN            NaN          NaN          NaN   \n",
       "\n",
       "  low fat yogurt green tea honey salad mineral water salmon antioxydant juice  \\\n",
       "0            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
       "1            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
       "2            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
       "3            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
       "4            NaN       NaN   NaN   NaN           NaN    NaN               NaN   \n",
       "\n",
       "  frozen smoothie spinach  olive oil  \n",
       "0             NaN     NaN        NaN  \n",
       "1             NaN     NaN        NaN  \n",
       "2             NaN     NaN        NaN  \n",
       "3             NaN     NaN        NaN  \n",
       "4             NaN     NaN        NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a0bd1a81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7500, 20)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "16befcf8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove the Column Names\n",
    "df = pd.read_csv('store_data.csv',header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7b1326a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>shrimp</td>\n",
       "      <td>almonds</td>\n",
       "      <td>avocado</td>\n",
       "      <td>vegetables mix</td>\n",
       "      <td>green grapes</td>\n",
       "      <td>whole weat flour</td>\n",
       "      <td>yams</td>\n",
       "      <td>cottage cheese</td>\n",
       "      <td>energy drink</td>\n",
       "      <td>tomato juice</td>\n",
       "      <td>low fat yogurt</td>\n",
       "      <td>green tea</td>\n",
       "      <td>honey</td>\n",
       "      <td>salad</td>\n",
       "      <td>mineral water</td>\n",
       "      <td>salmon</td>\n",
       "      <td>antioxydant juice</td>\n",
       "      <td>frozen smoothie</td>\n",
       "      <td>spinach</td>\n",
       "      <td>olive oil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>burgers</td>\n",
       "      <td>meatballs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chutney</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>turkey</td>\n",
       "      <td>avocado</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mineral water</td>\n",
       "      <td>milk</td>\n",
       "      <td>energy bar</td>\n",
       "      <td>whole wheat rice</td>\n",
       "      <td>green tea</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              0          1           2                 3             4   \\\n",
       "0         shrimp    almonds     avocado    vegetables mix  green grapes   \n",
       "1        burgers  meatballs        eggs               NaN           NaN   \n",
       "2        chutney        NaN         NaN               NaN           NaN   \n",
       "3         turkey    avocado         NaN               NaN           NaN   \n",
       "4  mineral water       milk  energy bar  whole wheat rice     green tea   \n",
       "\n",
       "                 5     6               7             8             9   \\\n",
       "0  whole weat flour  yams  cottage cheese  energy drink  tomato juice   \n",
       "1               NaN   NaN             NaN           NaN           NaN   \n",
       "2               NaN   NaN             NaN           NaN           NaN   \n",
       "3               NaN   NaN             NaN           NaN           NaN   \n",
       "4               NaN   NaN             NaN           NaN           NaN   \n",
       "\n",
       "               10         11     12     13             14      15  \\\n",
       "0  low fat yogurt  green tea  honey  salad  mineral water  salmon   \n",
       "1             NaN        NaN    NaN    NaN            NaN     NaN   \n",
       "2             NaN        NaN    NaN    NaN            NaN     NaN   \n",
       "3             NaN        NaN    NaN    NaN            NaN     NaN   \n",
       "4             NaN        NaN    NaN    NaN            NaN     NaN   \n",
       "\n",
       "                  16               17       18         19  \n",
       "0  antioxydant juice  frozen smoothie  spinach  olive oil  \n",
       "1                NaN              NaN      NaN        NaN  \n",
       "2                NaN              NaN      NaN        NaN  \n",
       "3                NaN              NaN      NaN        NaN  \n",
       "4                NaN              NaN      NaN        NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "14902100",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7501, 20)\n"
     ]
    }
   ],
   "source": [
    "# Look at the shape\n",
    "print(df.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3594d45f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Converting pandas dataframe into a list of lists\n",
    "records = []\n",
    "for i in range(0, len(df)):\n",
    "    records.append([str(df.values[i,j]) for j in range(0, len(df.columns))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "44d02a53",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Import apyori library\n",
    "from apyori import apriori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "85d12142",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Build the Apyori model\n",
    "associations = apriori(records, min_support=(7 * 5) / len(df), min_confidence=0.2,\n",
    "                       min_lift=3, min_length=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "406e7e68",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Converting the associations to lists\n",
    "associations = list(associations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f8934fe5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "44\n"
     ]
    }
   ],
   "source": [
    "#Print out the number of rules\n",
    "print(len(associations))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "bd1aa1d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RelationRecord(items=frozenset({'escalope', 'mushroom cream sauce'}), support=0.005732568990801226, ordered_statistics=[OrderedStatistic(items_base=frozenset({'mushroom cream sauce'}), items_add=frozenset({'escalope'}), confidence=0.3006993006993007, lift=3.790832696715049)])\n"
     ]
    }
   ],
   "source": [
    "#Lets check the first association rule\n",
    "print(associations[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "984aaadf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rule: escalope -> mushroom cream sauce\n",
      "Support: 0.005732568990801226\n",
      "Confidence: 0.3006993006993007\n",
      "Lift: 3.790832696715049\n",
      "=====================================\n",
      "Rule: escalope -> pasta\n",
      "Support: 0.005865884548726837\n",
      "Confidence: 0.3728813559322034\n",
      "Lift: 4.700811850163794\n",
      "=====================================\n",
      "Rule: ground beef -> herb & pepper\n",
      "Support: 0.015997866951073192\n",
      "Confidence: 0.3234501347708895\n",
      "Lift: 3.2919938411349285\n",
      "=====================================\n",
      "Rule: ground beef -> tomato sauce\n",
      "Support: 0.005332622317024397\n",
      "Confidence: 0.3773584905660377\n",
      "Lift: 3.840659481324083\n",
      "=====================================\n",
      "Rule: olive oil -> whole wheat pasta\n",
      "Support: 0.007998933475536596\n",
      "Confidence: 0.2714932126696833\n",
      "Lift: 4.122410097642296\n",
      "=====================================\n",
      "Rule: shrimp -> pasta\n",
      "Support: 0.005065991201173177\n",
      "Confidence: 0.3220338983050847\n",
      "Lift: 4.506672147735896\n",
      "=====================================\n",
      "Rule: frozen vegetables -> shrimp\n",
      "Support: 0.005332622317024397\n",
      "Confidence: 0.23255813953488375\n",
      "Lift: 3.2545123221103784\n",
      "=====================================\n",
      "Rule: ground beef -> cooking oil\n",
      "Support: 0.004799360085321957\n",
      "Confidence: 0.5714285714285714\n",
      "Lift: 3.2819951870487856\n",
      "=====================================\n",
      "Rule: escalope -> nan\n",
      "Support: 0.005732568990801226\n",
      "Confidence: 0.3006993006993007\n",
      "Lift: 3.790832696715049\n",
      "=====================================\n",
      "Rule: escalope -> nan\n",
      "Support: 0.005865884548726837\n",
      "Confidence: 0.3728813559322034\n",
      "Lift: 4.700811850163794\n",
      "=====================================\n",
      "Rule: spaghetti -> ground beef\n",
      "Support: 0.008665511265164644\n",
      "Confidence: 0.31100478468899523\n",
      "Lift: 3.165328208890303\n",
      "=====================================\n",
      "Rule: olive oil -> milk\n",
      "Support: 0.004799360085321957\n",
      "Confidence: 0.20338983050847456\n",
      "Lift: 3.088314005352364\n",
      "=====================================\n",
      "Rule: frozen vegetables -> shrimp\n",
      "Support: 0.007199040127982935\n",
      "Confidence: 0.30508474576271183\n",
      "Lift: 3.200616332819722\n",
      "=====================================\n",
      "Rule: olive oil -> spaghetti\n",
      "Support: 0.005732568990801226\n",
      "Confidence: 0.20574162679425836\n",
      "Lift: 3.1240241752707125\n",
      "=====================================\n",
      "Rule: spaghetti -> frozen vegetables\n",
      "Support: 0.005999200106652446\n",
      "Confidence: 0.21531100478468898\n",
      "Lift: 3.0131489680782684\n",
      "=====================================\n",
      "Rule: spaghetti -> frozen vegetables\n",
      "Support: 0.006665777896280496\n",
      "Confidence: 0.23923444976076558\n",
      "Lift: 3.4980460188216425\n",
      "=====================================\n",
      "Rule: spaghetti -> ground beef\n",
      "Support: 0.005332622317024397\n",
      "Confidence: 0.3225806451612903\n",
      "Lift: 3.283144395325426\n",
      "=====================================\n",
      "Rule: ground beef -> herb & pepper\n",
      "Support: 0.006665777896280496\n",
      "Confidence: 0.39062500000000006\n",
      "Lift: 3.975682666214383\n",
      "=====================================\n",
      "Rule: ground beef -> nan\n",
      "Support: 0.015997866951073192\n",
      "Confidence: 0.3234501347708895\n",
      "Lift: 3.2919938411349285\n",
      "=====================================\n",
      "Rule: spaghetti -> ground beef\n",
      "Support: 0.006399146780429276\n",
      "Confidence: 0.3934426229508197\n",
      "Lift: 4.004359721511667\n",
      "=====================================\n",
      "Rule: olive oil -> ground beef\n",
      "Support: 0.004932675643247567\n",
      "Confidence: 0.22424242424242427\n",
      "Lift: 3.40494417862839\n",
      "=====================================\n",
      "Rule: ground beef -> nan\n",
      "Support: 0.005332622317024397\n",
      "Confidence: 0.3773584905660377\n",
      "Lift: 3.840659481324083\n",
      "=====================================\n",
      "Rule: spaghetti -> ground beef\n",
      "Support: 0.005999200106652446\n",
      "Confidence: 0.5232558139534884\n",
      "Lift: 3.005315360233627\n",
      "=====================================\n",
      "Rule: olive oil -> milk\n",
      "Support: 0.007199040127982935\n",
      "Confidence: 0.20300751879699247\n",
      "Lift: 3.0825089038385434\n",
      "=====================================\n",
      "Rule: olive oil -> soup\n",
      "Support: 0.005199306759098787\n",
      "Confidence: 0.22543352601156072\n",
      "Lift: 3.4230301186492245\n",
      "=====================================\n",
      "Rule: olive oil -> nan\n",
      "Support: 0.007998933475536596\n",
      "Confidence: 0.2714932126696833\n",
      "Lift: 4.13077198425009\n",
      "=====================================\n",
      "Rule: nan -> pasta\n",
      "Support: 0.005065991201173177\n",
      "Confidence: 0.3220338983050847\n",
      "Lift: 4.515095833993347\n",
      "=====================================\n",
      "Rule: olive oil -> spaghetti\n",
      "Support: 0.005065991201173177\n",
      "Confidence: 0.20105820105820105\n",
      "Lift: 3.0529100529100526\n",
      "=====================================\n",
      "Rule: nan -> frozen vegetables\n",
      "Support: 0.005332622317024397\n",
      "Confidence: 0.23255813953488375\n",
      "Lift: 3.260595522712454\n",
      "=====================================\n",
      "Rule: ground beef -> cooking oil\n",
      "Support: 0.004799360085321957\n",
      "Confidence: 0.5714285714285714\n",
      "Lift: 3.2819951870487856\n",
      "=====================================\n",
      "Rule: nan -> ground beef\n",
      "Support: 0.008665511265164644\n",
      "Confidence: 0.31100478468899523\n",
      "Lift: 3.165328208890303\n",
      "=====================================\n",
      "Rule: nan -> milk\n",
      "Support: 0.004799360085321957\n",
      "Confidence: 0.20338983050847456\n",
      "Lift: 3.094578333963626\n",
      "=====================================\n",
      "Rule: nan -> frozen vegetables\n",
      "Support: 0.007199040127982935\n",
      "Confidence: 0.30508474576271183\n",
      "Lift: 3.200616332819722\n",
      "=====================================\n",
      "Rule: nan -> olive oil\n",
      "Support: 0.005732568990801226\n",
      "Confidence: 0.20574162679425836\n",
      "Lift: 3.1303609383037156\n",
      "=====================================\n",
      "Rule: nan -> spaghetti\n",
      "Support: 0.005999200106652446\n",
      "Confidence: 0.21531100478468898\n",
      "Lift: 3.0187810222242093\n",
      "=====================================\n",
      "Rule: nan -> spaghetti\n",
      "Support: 0.006665777896280496\n",
      "Confidence: 0.23923444976076558\n",
      "Lift: 3.4980460188216425\n",
      "=====================================\n",
      "Rule: spaghetti -> ground beef\n",
      "Support: 0.005332622317024397\n",
      "Confidence: 0.3225806451612903\n",
      "Lift: 3.283144395325426\n",
      "=====================================\n",
      "Rule: ground beef -> nan\n",
      "Support: 0.006665777896280496\n",
      "Confidence: 0.39062500000000006\n",
      "Lift: 3.975682666214383\n",
      "=====================================\n",
      "Rule: spaghetti -> ground beef\n",
      "Support: 0.006399146780429276\n",
      "Confidence: 0.3934426229508197\n",
      "Lift: 4.004359721511667\n",
      "=====================================\n",
      "Rule: olive oil -> ground beef\n",
      "Support: 0.004932675643247567\n",
      "Confidence: 0.22424242424242427\n",
      "Lift: 3.4118507591124225\n",
      "=====================================\n",
      "Rule: spaghetti -> ground beef\n",
      "Support: 0.005999200106652446\n",
      "Confidence: 0.5232558139534884\n",
      "Lift: 3.005315360233627\n",
      "=====================================\n",
      "Rule: olive oil -> milk\n",
      "Support: 0.007199040127982935\n",
      "Confidence: 0.20300751879699247\n",
      "Lift: 3.088761457396025\n",
      "=====================================\n",
      "Rule: olive oil -> soup\n",
      "Support: 0.005199306759098787\n",
      "Confidence: 0.22543352601156072\n",
      "Lift: 3.429973384609973\n",
      "=====================================\n",
      "Rule: olive oil -> spaghetti\n",
      "Support: 0.005065991201173177\n",
      "Confidence: 0.20105820105820105\n",
      "Lift: 3.0591025682303568\n",
      "=====================================\n"
     ]
    }
   ],
   "source": [
    "# Print All Association rules\n",
    "for item in associations:\n",
    "    # first index of the inner list\n",
    "    # Contains base item and add item\n",
    "    pair = item[0]\n",
    "    items = [x for x in pair]\n",
    "    print(\"Rule: \" + items[0] + \" -> \" + items[1])\n",
    "    #second index of the inner list\n",
    "    print(\"Support: \" + str(item[1]))\n",
    "    #third index of the list located at 0th\n",
    "    #of the third index of the inner list\n",
    "    print(\"Confidence: \" + str(item[2][0][2]))\n",
    "    print(\"Lift: \" + str(item[2][0][3]))\n",
    "    print(\"=====================================\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95577e2b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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