P32. Unsupervised ML - Association Rules Data Mining (Titanic).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unsupervised ML - Association Rules Data Mining"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from mlxtend.frequent_patterns import apriori,association_rules\n",
    "from mlxtend.preprocessing import TransactionEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "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>Class</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Survived</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3rd</td>\n",
       "      <td>Male</td>\n",
       "      <td>Child</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3rd</td>\n",
       "      <td>Male</td>\n",
       "      <td>Child</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3rd</td>\n",
       "      <td>Male</td>\n",
       "      <td>Child</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3rd</td>\n",
       "      <td>Male</td>\n",
       "      <td>Child</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3rd</td>\n",
       "      <td>Male</td>\n",
       "      <td>Child</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2196</th>\n",
       "      <td>Crew</td>\n",
       "      <td>Female</td>\n",
       "      <td>Adult</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2197</th>\n",
       "      <td>Crew</td>\n",
       "      <td>Female</td>\n",
       "      <td>Adult</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2198</th>\n",
       "      <td>Crew</td>\n",
       "      <td>Female</td>\n",
       "      <td>Adult</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2199</th>\n",
       "      <td>Crew</td>\n",
       "      <td>Female</td>\n",
       "      <td>Adult</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2200</th>\n",
       "      <td>Crew</td>\n",
       "      <td>Female</td>\n",
       "      <td>Adult</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2201 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Class  Gender    Age Survived\n",
       "0      3rd    Male  Child       No\n",
       "1      3rd    Male  Child       No\n",
       "2      3rd    Male  Child       No\n",
       "3      3rd    Male  Child       No\n",
       "4      3rd    Male  Child       No\n",
       "...    ...     ...    ...      ...\n",
       "2196  Crew  Female  Adult      Yes\n",
       "2197  Crew  Female  Adult      Yes\n",
       "2198  Crew  Female  Adult      Yes\n",
       "2199  Crew  Female  Adult      Yes\n",
       "2200  Crew  Female  Adult      Yes\n",
       "\n",
       "[2201 rows x 4 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic=pd.read_csv('Database/Titanic.csv')\n",
    "titanic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# As the data is categorical format, we are using One Hot Encoding to convert into numerical format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Class_1st</th>\n",
       "      <th>Class_2nd</th>\n",
       "      <th>Class_3rd</th>\n",
       "      <th>Class_Crew</th>\n",
       "      <th>Gender_Female</th>\n",
       "      <th>Gender_Male</th>\n",
       "      <th>Age_Adult</th>\n",
       "      <th>Age_Child</th>\n",
       "      <th>Survived_No</th>\n",
       "      <th>Survived_Yes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</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>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</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>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</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>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</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>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2196</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2197</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2198</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2199</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2200</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2201 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Class_1st  Class_2nd  Class_3rd  Class_Crew  Gender_Female  Gender_Male  \\\n",
       "0             0          0          1           0              0            1   \n",
       "1             0          0          1           0              0            1   \n",
       "2             0          0          1           0              0            1   \n",
       "3             0          0          1           0              0            1   \n",
       "4             0          0          1           0              0            1   \n",
       "...         ...        ...        ...         ...            ...          ...   \n",
       "2196          0          0          0           1              1            0   \n",
       "2197          0          0          0           1              1            0   \n",
       "2198          0          0          0           1              1            0   \n",
       "2199          0          0          0           1              1            0   \n",
       "2200          0          0          0           1              1            0   \n",
       "\n",
       "      Age_Adult  Age_Child  Survived_No  Survived_Yes  \n",
       "0             0          1            1             0  \n",
       "1             0          1            1             0  \n",
       "2             0          1            1             0  \n",
       "3             0          1            1             0  \n",
       "4             0          1            1             0  \n",
       "...         ...        ...          ...           ...  \n",
       "2196          1          0            0             1  \n",
       "2197          1          0            0             1  \n",
       "2198          1          0            0             1  \n",
       "2199          1          0            0             1  \n",
       "2200          1          0            0             1  \n",
       "\n",
       "[2201 rows x 10 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic=pd.get_dummies(titanic)\n",
    "titanic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apriori Algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>0.147660</td>\n",
       "      <td>(Class_1st)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.129487</td>\n",
       "      <td>(Class_2nd)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.320763</td>\n",
       "      <td>(Class_3rd)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.402090</td>\n",
       "      <td>(Class_Crew)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.213539</td>\n",
       "      <td>(Gender_Female)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.786461</td>\n",
       "      <td>(Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.950477</td>\n",
       "      <td>(Age_Adult)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.676965</td>\n",
       "      <td>(Survived_No)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.323035</td>\n",
       "      <td>(Survived_Yes)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.144934</td>\n",
       "      <td>(Class_1st, Age_Adult)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.118582</td>\n",
       "      <td>(Class_2nd, Age_Adult)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.231713</td>\n",
       "      <td>(Class_3rd, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.284871</td>\n",
       "      <td>(Class_3rd, Age_Adult)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.239891</td>\n",
       "      <td>(Class_3rd, Survived_No)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.391640</td>\n",
       "      <td>(Class_Crew, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.402090</td>\n",
       "      <td>(Class_Crew, Age_Adult)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.305770</td>\n",
       "      <td>(Class_Crew, Survived_No)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.193094</td>\n",
       "      <td>(Gender_Female, Age_Adult)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.156293</td>\n",
       "      <td>(Survived_Yes, Gender_Female)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.757383</td>\n",
       "      <td>(Age_Adult, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.619718</td>\n",
       "      <td>(Survived_No, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.166742</td>\n",
       "      <td>(Survived_Yes, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.653339</td>\n",
       "      <td>(Age_Adult, Survived_No)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.297138</td>\n",
       "      <td>(Survived_Yes, Age_Adult)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.209905</td>\n",
       "      <td>(Class_3rd, Age_Adult, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.191731</td>\n",
       "      <td>(Class_3rd, Survived_No, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.216265</td>\n",
       "      <td>(Class_3rd, Age_Adult, Survived_No)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.391640</td>\n",
       "      <td>(Class_Crew, Age_Adult, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.304407</td>\n",
       "      <td>(Class_Crew, Survived_No, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.305770</td>\n",
       "      <td>(Class_Crew, Age_Adult, Survived_No)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.143571</td>\n",
       "      <td>(Survived_Yes, Age_Adult, Gender_Female)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.603816</td>\n",
       "      <td>(Age_Adult, Survived_No, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.153567</td>\n",
       "      <td>(Survived_Yes, Age_Adult, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.175829</td>\n",
       "      <td>(Class_3rd, Age_Adult, Survived_No, Gender_Male)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.304407</td>\n",
       "      <td>(Class_Crew, Age_Adult, Survived_No, Gender_Male)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     support                                           itemsets\n",
       "0   0.147660                                        (Class_1st)\n",
       "1   0.129487                                        (Class_2nd)\n",
       "2   0.320763                                        (Class_3rd)\n",
       "3   0.402090                                       (Class_Crew)\n",
       "4   0.213539                                    (Gender_Female)\n",
       "5   0.786461                                      (Gender_Male)\n",
       "6   0.950477                                        (Age_Adult)\n",
       "7   0.676965                                      (Survived_No)\n",
       "8   0.323035                                     (Survived_Yes)\n",
       "9   0.144934                             (Class_1st, Age_Adult)\n",
       "10  0.118582                             (Class_2nd, Age_Adult)\n",
       "11  0.231713                           (Class_3rd, Gender_Male)\n",
       "12  0.284871                             (Class_3rd, Age_Adult)\n",
       "13  0.239891                           (Class_3rd, Survived_No)\n",
       "14  0.391640                          (Class_Crew, Gender_Male)\n",
       "15  0.402090                            (Class_Crew, Age_Adult)\n",
       "16  0.305770                          (Class_Crew, Survived_No)\n",
       "17  0.193094                         (Gender_Female, Age_Adult)\n",
       "18  0.156293                      (Survived_Yes, Gender_Female)\n",
       "19  0.757383                           (Age_Adult, Gender_Male)\n",
       "20  0.619718                         (Survived_No, Gender_Male)\n",
       "21  0.166742                        (Survived_Yes, Gender_Male)\n",
       "22  0.653339                           (Age_Adult, Survived_No)\n",
       "23  0.297138                          (Survived_Yes, Age_Adult)\n",
       "24  0.209905                (Class_3rd, Age_Adult, Gender_Male)\n",
       "25  0.191731              (Class_3rd, Survived_No, Gender_Male)\n",
       "26  0.216265                (Class_3rd, Age_Adult, Survived_No)\n",
       "27  0.391640               (Class_Crew, Age_Adult, Gender_Male)\n",
       "28  0.304407             (Class_Crew, Survived_No, Gender_Male)\n",
       "29  0.305770               (Class_Crew, Age_Adult, Survived_No)\n",
       "30  0.143571           (Survived_Yes, Age_Adult, Gender_Female)\n",
       "31  0.603816              (Age_Adult, Survived_No, Gender_Male)\n",
       "32  0.153567             (Survived_Yes, Age_Adult, Gender_Male)\n",
       "33  0.175829   (Class_3rd, Age_Adult, Survived_No, Gender_Male)\n",
       "34  0.304407  (Class_Crew, Age_Adult, Survived_No, Gender_Male)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frequent_itemsets=apriori(titanic,min_support=0.1,use_colnames=True)\n",
    "frequent_itemsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>(Class_1st)</td>\n",
       "      <td>(Age_Adult)</td>\n",
       "      <td>0.147660</td>\n",
       "      <td>0.950477</td>\n",
       "      <td>0.144934</td>\n",
       "      <td>0.981538</td>\n",
       "      <td>1.032680</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>2.682493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(Age_Adult)</td>\n",
       "      <td>(Class_1st)</td>\n",
       "      <td>0.950477</td>\n",
       "      <td>0.147660</td>\n",
       "      <td>0.144934</td>\n",
       "      <td>0.152486</td>\n",
       "      <td>1.032680</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>1.005694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(Class_2nd)</td>\n",
       "      <td>(Age_Adult)</td>\n",
       "      <td>0.129487</td>\n",
       "      <td>0.950477</td>\n",
       "      <td>0.118582</td>\n",
       "      <td>0.915789</td>\n",
       "      <td>0.963505</td>\n",
       "      <td>-0.004492</td>\n",
       "      <td>0.588085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(Age_Adult)</td>\n",
       "      <td>(Class_2nd)</td>\n",
       "      <td>0.950477</td>\n",
       "      <td>0.129487</td>\n",
       "      <td>0.118582</td>\n",
       "      <td>0.124761</td>\n",
       "      <td>0.963505</td>\n",
       "      <td>-0.004492</td>\n",
       "      <td>0.994601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(Class_3rd)</td>\n",
       "      <td>(Gender_Male)</td>\n",
       "      <td>0.320763</td>\n",
       "      <td>0.786461</td>\n",
       "      <td>0.231713</td>\n",
       "      <td>0.722380</td>\n",
       "      <td>0.918520</td>\n",
       "      <td>-0.020555</td>\n",
       "      <td>0.769177</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>101</th>\n",
       "      <td>(Survived_No, Gender_Male)</td>\n",
       "      <td>(Class_Crew, Age_Adult)</td>\n",
       "      <td>0.619718</td>\n",
       "      <td>0.402090</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.491202</td>\n",
       "      <td>1.221623</td>\n",
       "      <td>0.055225</td>\n",
       "      <td>1.175143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>(Class_Crew)</td>\n",
       "      <td>(Age_Adult, Survived_No, Gender_Male)</td>\n",
       "      <td>0.402090</td>\n",
       "      <td>0.603816</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.757062</td>\n",
       "      <td>1.253795</td>\n",
       "      <td>0.061619</td>\n",
       "      <td>1.630802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>(Age_Adult)</td>\n",
       "      <td>(Class_Crew, Survived_No, Gender_Male)</td>\n",
       "      <td>0.950477</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.320268</td>\n",
       "      <td>1.052103</td>\n",
       "      <td>0.015075</td>\n",
       "      <td>1.023334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>(Survived_No)</td>\n",
       "      <td>(Class_Crew, Age_Adult, Gender_Male)</td>\n",
       "      <td>0.676965</td>\n",
       "      <td>0.391640</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.449664</td>\n",
       "      <td>1.148157</td>\n",
       "      <td>0.039280</td>\n",
       "      <td>1.105434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>(Gender_Male)</td>\n",
       "      <td>(Class_Crew, Age_Adult, Survived_No)</td>\n",
       "      <td>0.786461</td>\n",
       "      <td>0.305770</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.387060</td>\n",
       "      <td>1.265851</td>\n",
       "      <td>0.063931</td>\n",
       "      <td>1.132622</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>106 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    antecedents                             consequents  \\\n",
       "0                   (Class_1st)                             (Age_Adult)   \n",
       "1                   (Age_Adult)                             (Class_1st)   \n",
       "2                   (Class_2nd)                             (Age_Adult)   \n",
       "3                   (Age_Adult)                             (Class_2nd)   \n",
       "4                   (Class_3rd)                           (Gender_Male)   \n",
       "..                          ...                                     ...   \n",
       "101  (Survived_No, Gender_Male)                 (Class_Crew, Age_Adult)   \n",
       "102                (Class_Crew)   (Age_Adult, Survived_No, Gender_Male)   \n",
       "103                 (Age_Adult)  (Class_Crew, Survived_No, Gender_Male)   \n",
       "104               (Survived_No)    (Class_Crew, Age_Adult, Gender_Male)   \n",
       "105               (Gender_Male)    (Class_Crew, Age_Adult, Survived_No)   \n",
       "\n",
       "     antecedent support  consequent support   support  confidence      lift  \\\n",
       "0              0.147660            0.950477  0.144934    0.981538  1.032680   \n",
       "1              0.950477            0.147660  0.144934    0.152486  1.032680   \n",
       "2              0.129487            0.950477  0.118582    0.915789  0.963505   \n",
       "3              0.950477            0.129487  0.118582    0.124761  0.963505   \n",
       "4              0.320763            0.786461  0.231713    0.722380  0.918520   \n",
       "..                  ...                 ...       ...         ...       ...   \n",
       "101            0.619718            0.402090  0.304407    0.491202  1.221623   \n",
       "102            0.402090            0.603816  0.304407    0.757062  1.253795   \n",
       "103            0.950477            0.304407  0.304407    0.320268  1.052103   \n",
       "104            0.676965            0.391640  0.304407    0.449664  1.148157   \n",
       "105            0.786461            0.305770  0.304407    0.387060  1.265851   \n",
       "\n",
       "     leverage  conviction  \n",
       "0    0.004587    2.682493  \n",
       "1    0.004587    1.005694  \n",
       "2   -0.004492    0.588085  \n",
       "3   -0.004492    0.994601  \n",
       "4   -0.020555    0.769177  \n",
       "..        ...         ...  \n",
       "101  0.055225    1.175143  \n",
       "102  0.061619    1.630802  \n",
       "103  0.015075    1.023334  \n",
       "104  0.039280    1.105434  \n",
       "105  0.063931    1.132622  \n",
       "\n",
       "[106 rows x 9 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rules=association_rules(frequent_itemsets,metric='lift',min_threshold=0.7)\n",
    "rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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": 22,
   "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>66</th>\n",
       "      <td>(Gender_Female, Age_Adult)</td>\n",
       "      <td>(Survived_Yes)</td>\n",
       "      <td>0.193094</td>\n",
       "      <td>0.323035</td>\n",
       "      <td>0.143571</td>\n",
       "      <td>0.743529</td>\n",
       "      <td>2.301699</td>\n",
       "      <td>0.081195</td>\n",
       "      <td>2.639542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>(Survived_Yes)</td>\n",
       "      <td>(Gender_Female, Age_Adult)</td>\n",
       "      <td>0.323035</td>\n",
       "      <td>0.193094</td>\n",
       "      <td>0.143571</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>2.301699</td>\n",
       "      <td>0.081195</td>\n",
       "      <td>1.452431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>(Gender_Female)</td>\n",
       "      <td>(Survived_Yes)</td>\n",
       "      <td>0.213539</td>\n",
       "      <td>0.323035</td>\n",
       "      <td>0.156293</td>\n",
       "      <td>0.731915</td>\n",
       "      <td>2.265745</td>\n",
       "      <td>0.087312</td>\n",
       "      <td>2.525187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>(Survived_Yes)</td>\n",
       "      <td>(Gender_Female)</td>\n",
       "      <td>0.323035</td>\n",
       "      <td>0.213539</td>\n",
       "      <td>0.156293</td>\n",
       "      <td>0.483826</td>\n",
       "      <td>2.265745</td>\n",
       "      <td>0.087312</td>\n",
       "      <td>1.523634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>(Survived_Yes, Age_Adult)</td>\n",
       "      <td>(Gender_Female)</td>\n",
       "      <td>0.297138</td>\n",
       "      <td>0.213539</td>\n",
       "      <td>0.143571</td>\n",
       "      <td>0.483180</td>\n",
       "      <td>2.262724</td>\n",
       "      <td>0.080121</td>\n",
       "      <td>1.521732</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>(Class_3rd)</td>\n",
       "      <td>(Gender_Male)</td>\n",
       "      <td>0.320763</td>\n",
       "      <td>0.786461</td>\n",
       "      <td>0.231713</td>\n",
       "      <td>0.722380</td>\n",
       "      <td>0.918520</td>\n",
       "      <td>-0.020555</td>\n",
       "      <td>0.769177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>(Age_Adult, Survived_No, Gender_Male)</td>\n",
       "      <td>(Class_3rd)</td>\n",
       "      <td>0.603816</td>\n",
       "      <td>0.320763</td>\n",
       "      <td>0.175829</td>\n",
       "      <td>0.291196</td>\n",
       "      <td>0.907823</td>\n",
       "      <td>-0.017853</td>\n",
       "      <td>0.958286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>(Class_3rd)</td>\n",
       "      <td>(Age_Adult, Survived_No, Gender_Male)</td>\n",
       "      <td>0.320763</td>\n",
       "      <td>0.603816</td>\n",
       "      <td>0.175829</td>\n",
       "      <td>0.548159</td>\n",
       "      <td>0.907823</td>\n",
       "      <td>-0.017853</td>\n",
       "      <td>0.876820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>(Age_Adult, Gender_Male)</td>\n",
       "      <td>(Class_3rd)</td>\n",
       "      <td>0.757383</td>\n",
       "      <td>0.320763</td>\n",
       "      <td>0.209905</td>\n",
       "      <td>0.277145</td>\n",
       "      <td>0.864016</td>\n",
       "      <td>-0.033036</td>\n",
       "      <td>0.939658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>(Class_3rd)</td>\n",
       "      <td>(Age_Adult, Gender_Male)</td>\n",
       "      <td>0.320763</td>\n",
       "      <td>0.757383</td>\n",
       "      <td>0.209905</td>\n",
       "      <td>0.654391</td>\n",
       "      <td>0.864016</td>\n",
       "      <td>-0.033036</td>\n",
       "      <td>0.701998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>106 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              antecedents  \\\n",
       "66             (Gender_Female, Age_Adult)   \n",
       "67                         (Survived_Yes)   \n",
       "19                        (Gender_Female)   \n",
       "18                         (Survived_Yes)   \n",
       "64              (Survived_Yes, Age_Adult)   \n",
       "..                                    ...   \n",
       "4                             (Class_3rd)   \n",
       "81  (Age_Adult, Survived_No, Gender_Male)   \n",
       "88                            (Class_3rd)   \n",
       "30               (Age_Adult, Gender_Male)   \n",
       "31                            (Class_3rd)   \n",
       "\n",
       "                              consequents  antecedent support  \\\n",
       "66                         (Survived_Yes)            0.193094   \n",
       "67             (Gender_Female, Age_Adult)            0.323035   \n",
       "19                         (Survived_Yes)            0.213539   \n",
       "18                        (Gender_Female)            0.323035   \n",
       "64                        (Gender_Female)            0.297138   \n",
       "..                                    ...                 ...   \n",
       "4                           (Gender_Male)            0.320763   \n",
       "81                            (Class_3rd)            0.603816   \n",
       "88  (Age_Adult, Survived_No, Gender_Male)            0.320763   \n",
       "30                            (Class_3rd)            0.757383   \n",
       "31               (Age_Adult, Gender_Male)            0.320763   \n",
       "\n",
       "    consequent support   support  confidence      lift  leverage  conviction  \n",
       "66            0.323035  0.143571    0.743529  2.301699  0.081195    2.639542  \n",
       "67            0.193094  0.143571    0.444444  2.301699  0.081195    1.452431  \n",
       "19            0.323035  0.156293    0.731915  2.265745  0.087312    2.525187  \n",
       "18            0.213539  0.156293    0.483826  2.265745  0.087312    1.523634  \n",
       "64            0.213539  0.143571    0.483180  2.262724  0.080121    1.521732  \n",
       "..                 ...       ...         ...       ...       ...         ...  \n",
       "4             0.786461  0.231713    0.722380  0.918520 -0.020555    0.769177  \n",
       "81            0.320763  0.175829    0.291196  0.907823 -0.017853    0.958286  \n",
       "88            0.603816  0.175829    0.548159  0.907823 -0.017853    0.876820  \n",
       "30            0.320763  0.209905    0.277145  0.864016 -0.033036    0.939658  \n",
       "31            0.757383  0.209905    0.654391  0.864016 -0.033036    0.701998  \n",
       "\n",
       "[106 rows x 9 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rules.sort_values('lift',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>(Class_1st)</td>\n",
       "      <td>(Age_Adult)</td>\n",
       "      <td>0.147660</td>\n",
       "      <td>0.950477</td>\n",
       "      <td>0.144934</td>\n",
       "      <td>0.981538</td>\n",
       "      <td>1.032680</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>2.682493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(Age_Adult)</td>\n",
       "      <td>(Class_1st)</td>\n",
       "      <td>0.950477</td>\n",
       "      <td>0.147660</td>\n",
       "      <td>0.144934</td>\n",
       "      <td>0.152486</td>\n",
       "      <td>1.032680</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>1.005694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(Class_3rd)</td>\n",
       "      <td>(Survived_No)</td>\n",
       "      <td>0.320763</td>\n",
       "      <td>0.676965</td>\n",
       "      <td>0.239891</td>\n",
       "      <td>0.747875</td>\n",
       "      <td>1.104747</td>\n",
       "      <td>0.022745</td>\n",
       "      <td>1.281251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>(Survived_No)</td>\n",
       "      <td>(Class_3rd)</td>\n",
       "      <td>0.676965</td>\n",
       "      <td>0.320763</td>\n",
       "      <td>0.239891</td>\n",
       "      <td>0.354362</td>\n",
       "      <td>1.104747</td>\n",
       "      <td>0.022745</td>\n",
       "      <td>1.052040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>(Class_Crew)</td>\n",
       "      <td>(Gender_Male)</td>\n",
       "      <td>0.402090</td>\n",
       "      <td>0.786461</td>\n",
       "      <td>0.391640</td>\n",
       "      <td>0.974011</td>\n",
       "      <td>1.238474</td>\n",
       "      <td>0.075412</td>\n",
       "      <td>8.216621</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>101</th>\n",
       "      <td>(Survived_No, Gender_Male)</td>\n",
       "      <td>(Class_Crew, Age_Adult)</td>\n",
       "      <td>0.619718</td>\n",
       "      <td>0.402090</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.491202</td>\n",
       "      <td>1.221623</td>\n",
       "      <td>0.055225</td>\n",
       "      <td>1.175143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>(Class_Crew)</td>\n",
       "      <td>(Age_Adult, Survived_No, Gender_Male)</td>\n",
       "      <td>0.402090</td>\n",
       "      <td>0.603816</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.757062</td>\n",
       "      <td>1.253795</td>\n",
       "      <td>0.061619</td>\n",
       "      <td>1.630802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>(Age_Adult)</td>\n",
       "      <td>(Class_Crew, Survived_No, Gender_Male)</td>\n",
       "      <td>0.950477</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.320268</td>\n",
       "      <td>1.052103</td>\n",
       "      <td>0.015075</td>\n",
       "      <td>1.023334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>(Survived_No)</td>\n",
       "      <td>(Class_Crew, Age_Adult, Gender_Male)</td>\n",
       "      <td>0.676965</td>\n",
       "      <td>0.391640</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.449664</td>\n",
       "      <td>1.148157</td>\n",
       "      <td>0.039280</td>\n",
       "      <td>1.105434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>(Gender_Male)</td>\n",
       "      <td>(Class_Crew, Age_Adult, Survived_No)</td>\n",
       "      <td>0.786461</td>\n",
       "      <td>0.305770</td>\n",
       "      <td>0.304407</td>\n",
       "      <td>0.387060</td>\n",
       "      <td>1.265851</td>\n",
       "      <td>0.063931</td>\n",
       "      <td>1.132622</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>74 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    antecedents                             consequents  \\\n",
       "0                   (Class_1st)                             (Age_Adult)   \n",
       "1                   (Age_Adult)                             (Class_1st)   \n",
       "8                   (Class_3rd)                           (Survived_No)   \n",
       "9                 (Survived_No)                             (Class_3rd)   \n",
       "10                 (Class_Crew)                           (Gender_Male)   \n",
       "..                          ...                                     ...   \n",
       "101  (Survived_No, Gender_Male)                 (Class_Crew, Age_Adult)   \n",
       "102                (Class_Crew)   (Age_Adult, Survived_No, Gender_Male)   \n",
       "103                 (Age_Adult)  (Class_Crew, Survived_No, Gender_Male)   \n",
       "104               (Survived_No)    (Class_Crew, Age_Adult, Gender_Male)   \n",
       "105               (Gender_Male)    (Class_Crew, Age_Adult, Survived_No)   \n",
       "\n",
       "     antecedent support  consequent support   support  confidence      lift  \\\n",
       "0              0.147660            0.950477  0.144934    0.981538  1.032680   \n",
       "1              0.950477            0.147660  0.144934    0.152486  1.032680   \n",
       "8              0.320763            0.676965  0.239891    0.747875  1.104747   \n",
       "9              0.676965            0.320763  0.239891    0.354362  1.104747   \n",
       "10             0.402090            0.786461  0.391640    0.974011  1.238474   \n",
       "..                  ...                 ...       ...         ...       ...   \n",
       "101            0.619718            0.402090  0.304407    0.491202  1.221623   \n",
       "102            0.402090            0.603816  0.304407    0.757062  1.253795   \n",
       "103            0.950477            0.304407  0.304407    0.320268  1.052103   \n",
       "104            0.676965            0.391640  0.304407    0.449664  1.148157   \n",
       "105            0.786461            0.305770  0.304407    0.387060  1.265851   \n",
       "\n",
       "     leverage  conviction  \n",
       "0    0.004587    2.682493  \n",
       "1    0.004587    1.005694  \n",
       "8    0.022745    1.281251  \n",
       "9    0.022745    1.052040  \n",
       "10   0.075412    8.216621  \n",
       "..        ...         ...  \n",
       "101  0.055225    1.175143  \n",
       "102  0.061619    1.630802  \n",
       "103  0.015075    1.023334  \n",
       "104  0.039280    1.105434  \n",
       "105  0.063931    1.132622  \n",
       "\n",
       "[74 rows x 9 columns]"
      ]
     },
     "execution_count": 23,
     "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": 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
}