Market_Basket_Opt.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: apyori in d:\\anaconda\\lib\\site-packages (1.1.2)\n"
     ]
    }
   ],
   "source": [
    "!pip install apyori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('Market_Basket_Optimisation.csv', header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>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": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "from apyori import apriori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.fillna(method='ffill', axis = 1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>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>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "      <td>eggs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "      <td>chutney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>turkey</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</td>\n",
       "      <td>avocado</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>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</td>\n",
       "      <td>green tea</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              eggs          eggs   \n",
       "2        chutney    chutney     chutney           chutney       chutney   \n",
       "3         turkey    avocado     avocado           avocado       avocado   \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              eggs       eggs            eggs          eggs          eggs   \n",
       "2           chutney    chutney         chutney       chutney       chutney   \n",
       "3           avocado    avocado         avocado       avocado       avocado   \n",
       "4         green tea  green tea       green tea     green tea     green tea   \n",
       "\n",
       "               10         11         12         13             14         15  \\\n",
       "0  low fat yogurt  green tea      honey      salad  mineral water     salmon   \n",
       "1            eggs       eggs       eggs       eggs           eggs       eggs   \n",
       "2         chutney    chutney    chutney    chutney        chutney    chutney   \n",
       "3         avocado    avocado    avocado    avocado        avocado    avocado   \n",
       "4       green tea  green tea  green tea  green tea      green tea  green tea   \n",
       "\n",
       "                  16               17         18         19  \n",
       "0  antioxydant juice  frozen smoothie    spinach  olive oil  \n",
       "1               eggs             eggs       eggs       eggs  \n",
       "2            chutney          chutney    chutney    chutney  \n",
       "3            avocado          avocado    avocado    avocado  \n",
       "4          green tea        green tea  green tea  green tea  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "transactions = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0, 7501):\n",
    "    transactions.append([str(data.values[i,j]) for j in range(0, 20)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = list(apriori(transactions, min_support = 0.003, min_confidence = 0.2, min_lift = 4, min_length = 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import shutil, os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    from SrtingIO import StringIO\n",
    "except ImportError:\n",
    "    from io import StringIO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "output = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from apyori import dump_as_json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "for RelationRecord in result:\n",
    "    o = StringIO()\n",
    "    apriori = dump_as_json(RelationRecord, o)\n",
    "    output.append(json.loads(o.getvalue()))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_df = pd.DataFrame(output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-46-0891b765a168>:1: FutureWarning: Passing a negative integer is deprecated in version 1.0 and will not be supported in future version. Instead, use None to not limit the column width.\n",
      "  pd.set_option('display.max_colwidth', -1)\n"
     ]
    }
   ],
   "source": [
    "pd.set_option('display.max_colwidth', -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display, HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>items</th>\n",
       "      <th>support</th>\n",
       "      <th>ordered_statistics</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[chicken, light cream]</td>\n",
       "      <td>0.004533</td>\n",
       "      <td>[{'items_base': ['light cream'], 'items_add': ['chicken'], 'confidence': 0.29059829059829057, 'lift': 4.84395061728395}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[escalope, pasta]</td>\n",
       "      <td>0.005866</td>\n",
       "      <td>[{'items_base': ['pasta'], 'items_add': ['escalope'], 'confidence': 0.3728813559322034, 'lift': 4.700811850163794}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[fromage blanc, honey]</td>\n",
       "      <td>0.003333</td>\n",
       "      <td>[{'items_base': ['fromage blanc'], 'items_add': ['honey'], 'confidence': 0.2450980392156863, 'lift': 5.164270764485569}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[olive oil, whole wheat pasta]</td>\n",
       "      <td>0.007999</td>\n",
       "      <td>[{'items_base': ['whole wheat pasta'], 'items_add': ['olive oil'], 'confidence': 0.2714932126696833, 'lift': 4.122410097642296}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[pasta, shrimp]</td>\n",
       "      <td>0.005066</td>\n",
       "      <td>[{'items_base': ['pasta'], 'items_add': ['shrimp'], 'confidence': 0.3220338983050847, 'lift': 4.506672147735896}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>[cake, frozen vegetables, tomatoes]</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>[{'items_base': ['cake', 'frozen vegetables'], 'items_add': ['tomatoes'], 'confidence': 0.2987012987012987, 'lift': 4.367560314928736}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>[cereals, ground beef, spaghetti]</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>[{'items_base': ['cereals', 'spaghetti'], 'items_add': ['ground beef'], 'confidence': 0.45999999999999996, 'lift': 4.681763907734057}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>[chocolate, ground beef, herb &amp; pepper]</td>\n",
       "      <td>0.003999</td>\n",
       "      <td>[{'items_base': ['chocolate', 'herb &amp; pepper'], 'items_add': ['ground beef'], 'confidence': 0.4411764705882354, 'lift': 4.4901827759597746}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>[eggs, ground beef, herb &amp; pepper]</td>\n",
       "      <td>0.004133</td>\n",
       "      <td>[{'items_base': ['eggs', 'ground beef'], 'items_add': ['herb &amp; pepper'], 'confidence': 0.2066666666666667, 'lift': 4.178454627133872}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>[french fries, ground beef, herb &amp; pepper]</td>\n",
       "      <td>0.003200</td>\n",
       "      <td>[{'items_base': ['french fries', 'ground beef'], 'items_add': ['herb &amp; pepper'], 'confidence': 0.23076923076923078, 'lift': 4.665768194070081}, {'items_base': ['french fries', 'herb &amp; pepper'], 'items_add': ['ground beef'], 'confidence': 0.46153846153846156, 'lift': 4.697421981004071}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>[ground beef, herb &amp; pepper, spaghetti]</td>\n",
       "      <td>0.006399</td>\n",
       "      <td>[{'items_base': ['herb &amp; pepper', 'spaghetti'], 'items_add': ['ground beef'], 'confidence': 0.3934426229508197, 'lift': 4.004359721511667}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>[ground beef, spaghetti, tomato sauce]</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>[{'items_base': ['tomato sauce'], 'items_add': ['ground beef', 'spaghetti'], 'confidence': 0.2169811320754717, 'lift': 5.535970992170453}, {'items_base': ['spaghetti', 'tomato sauce'], 'items_add': ['ground beef'], 'confidence': 0.4893617021276596, 'lift': 4.980599901844742}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>[milk, olive oil, soup]</td>\n",
       "      <td>0.003600</td>\n",
       "      <td>[{'items_base': ['milk', 'olive oil'], 'items_add': ['soup'], 'confidence': 0.2109375, 'lift': 4.174781497361478}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>[milk, soup, tomatoes]</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>[{'items_base': ['milk', 'tomatoes'], 'items_add': ['soup'], 'confidence': 0.21904761904761905, 'lift': 4.335293378565146}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>[mineral water, olive oil, whole wheat pasta]</td>\n",
       "      <td>0.003866</td>\n",
       "      <td>[{'items_base': ['mineral water', 'whole wheat pasta'], 'items_add': ['olive oil'], 'confidence': 0.4027777777777778, 'lift': 6.115862573099416}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>[chocolate, frozen vegetables, mineral water, shrimp]</td>\n",
       "      <td>0.003200</td>\n",
       "      <td>[{'items_base': ['chocolate', 'frozen vegetables', 'mineral water'], 'items_add': ['shrimp'], 'confidence': 0.32876712328767127, 'lift': 4.600899611531385}, {'items_base': ['chocolate', 'mineral water', 'shrimp'], 'items_add': ['frozen vegetables'], 'confidence': 0.4210526315789474, 'lift': 4.417224880382776}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>[frozen smoothie, milk, mineral water, spaghetti]</td>\n",
       "      <td>0.003200</td>\n",
       "      <td>[{'items_base': ['frozen smoothie', 'spaghetti'], 'items_add': ['milk', 'mineral water'], 'confidence': 0.20512820512820515, 'lift': 4.274074074074075}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>[frozen vegetables, ground beef, milk, mineral water]</td>\n",
       "      <td>0.003733</td>\n",
       "      <td>[{'items_base': ['frozen vegetables', 'ground beef'], 'items_add': ['milk', 'mineral water'], 'confidence': 0.22047244094488186, 'lift': 4.593788276465442}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>[frozen vegetables, ground beef, mineral water, spaghetti]</td>\n",
       "      <td>0.004399</td>\n",
       "      <td>[{'items_base': ['frozen vegetables', 'ground beef'], 'items_add': ['mineral water', 'spaghetti'], 'confidence': 0.25984251968503935, 'lift': 4.350622187851519}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>[frozen vegetables, milk, mineral water, olive oil]</td>\n",
       "      <td>0.003333</td>\n",
       "      <td>[{'items_base': ['frozen vegetables', 'olive oil'], 'items_add': ['milk', 'mineral water'], 'confidence': 0.29411764705882354, 'lift': 6.12826797385621}, {'items_base': ['frozen vegetables', 'milk', 'mineral water'], 'items_add': ['olive oil'], 'confidence': 0.30120481927710846, 'lift': 4.573557387444516}, {'items_base': ['milk', 'mineral water', 'olive oil'], 'items_add': ['frozen vegetables'], 'confidence': 0.39062500000000006, 'lift': 4.098011363636364}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>[frozen vegetables, milk, mineral water, soup]</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>[{'items_base': ['frozen vegetables', 'soup'], 'items_add': ['milk', 'mineral water'], 'confidence': 0.3833333333333333, 'lift': 7.987175925925926}, {'items_base': ['milk', 'soup'], 'items_add': ['frozen vegetables', 'mineral water'], 'confidence': 0.20175438596491227, 'lift': 5.646864362398533}, {'items_base': ['frozen vegetables', 'milk', 'mineral water'], 'items_add': ['soup'], 'confidence': 0.27710843373493976, 'lift': 5.484407286136631}, {'items_base': ['frozen vegetables', 'mineral water', 'soup'], 'items_add': ['milk'], 'confidence': 0.6052631578947368, 'lift': 4.670863114576565}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>[frozen vegetables, mineral water, shrimp, spaghetti]</td>\n",
       "      <td>0.003333</td>\n",
       "      <td>[{'items_base': ['mineral water', 'shrimp', 'spaghetti'], 'items_add': ['frozen vegetables'], 'confidence': 0.39062500000000006, 'lift': 4.098011363636364}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>[ground beef, mineral water, spaghetti, tomatoes]</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>[{'items_base': ['ground beef', 'tomatoes'], 'items_add': ['mineral water', 'spaghetti'], 'confidence': 0.26136363636363635, 'lift': 4.3760907061688314}]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(HTML(data_df.to_html()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}