{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "db3c2e94-9499-4d7d-bf0f-1ab892a61fa1",
   "metadata": {},
   "source": [
    "### ASSOCIATION RULES"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e642b4f-11cf-4bd5-bc7f-c97da0efc7e2",
   "metadata": {},
   "source": [
    "#### FACEPLATE DATASET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f82fe170-ad6b-42fc-962a-99c5466933ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "pip install mlxtend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a8e53481-02ba-450d-9d1f-ad2ecd8458cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pylab as plt\n",
    "from mlxtend.frequent_patterns import apriori, association_rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c6b19ec8-aa53-4b0f-b2ab-3c3e5c8eacbd",
   "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>Red</th>\n",
       "      <th>White</th>\n",
       "      <th>Blue</th>\n",
       "      <th>Orange</th>\n",
       "      <th>Green</th>\n",
       "      <th>Yellow</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transaction</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Red  White  Blue  Orange  Green  Yellow\n",
       "Transaction                                         \n",
       "1              1      1     0       0      1       0\n",
       "2              0      1     0       1      0       0\n",
       "3              0      1     1       0      0       0\n",
       "4              1      1     0       1      0       0\n",
       "5              1      0     1       0      0       0\n",
       "6              0      1     1       0      0       0\n",
       "7              1      0     1       0      0       0\n",
       "8              1      1     1       0      1       0\n",
       "9              1      1     1       0      0       0\n",
       "10             0      0     0       0      0       1"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(r'/Users/patriciaxufre/Documents/SBE - Disciplinas/2957 | ABA/2024-25/Datasets Examples/Faceplate.csv')\n",
    "df.set_index('Transaction', inplace = True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "97b4e61c-c99e-447c-b160-a9d9c4748fd2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.12/site-packages/mlxtend/frequent_patterns/fpcommon.py:161: DeprecationWarning: DataFrames with non-bool types result in worse computationalperformance and their support might be discontinued in the future.Please use a DataFrame with bool type\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>representativity</th>\n",
       "      <th>leverage</th>\n",
       "      <th>zhangs_metric</th>\n",
       "      <th>jaccard</th>\n",
       "      <th>certainty</th>\n",
       "      <th>kulczynski</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>(Red, White)</td>\n",
       "      <td>(Green)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>0.750000</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>(Green)</td>\n",
       "      <td>(Red, White)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.750000</td>\n",
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       "      <td>1.000000</td>\n",
       "      <td>0.750000</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(Green)</td>\n",
       "      <td>(Red)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>(Green, White)</td>\n",
       "      <td>(Red)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.666667</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>(Orange)</td>\n",
       "      <td>(White)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.428571</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.06</td>\n",
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       "      <td>0.285714</td>\n",
       "      <td>1.000000</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(Green)</td>\n",
       "      <td>(White)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.428571</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.642857</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>(Red, Green)</td>\n",
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       "      <td>0.2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.428571</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>0.666667</td>\n",
       "      <td>1.111111</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(Blue)</td>\n",
       "      <td>(Red)</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.111111</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.666667</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(Red)</td>\n",
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       "      <td>0.4</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.952381</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(White)</td>\n",
       "      <td>(Red)</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.571429</td>\n",
       "      <td>0.952381</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.02</td>\n",
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       "      <td>0.444444</td>\n",
       "      <td>-0.071429</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>(Blue)</td>\n",
       "      <td>(White)</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.952381</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.111111</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>-0.111111</td>\n",
       "      <td>0.619048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(White)</td>\n",
       "      <td>(Blue)</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.571429</td>\n",
       "      <td>0.952381</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.142857</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>-0.071429</td>\n",
       "      <td>0.619048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>(White, Blue)</td>\n",
       "      <td>(Red)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.250000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>-0.250000</td>\n",
       "      <td>0.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>(Red, White)</td>\n",
       "      <td>(Blue)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.250000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>-0.250000</td>\n",
       "      <td>0.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>(Red, Blue)</td>\n",
       "      <td>(White)</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.08</td>\n",
       "      <td>-0.400000</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>-0.666667</td>\n",
       "      <td>0.392857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       antecedents   consequents  support  confidence      lift  \\\n",
       "13    (Red, White)       (Green)      0.2    0.500000  2.500000   \n",
       "15         (Green)  (Red, White)      0.2    1.000000  2.500000   \n",
       "4          (Green)         (Red)      0.2    1.000000  1.666667   \n",
       "14  (Green, White)         (Red)      0.2    1.000000  1.666667   \n",
       "7         (Orange)       (White)      0.2    1.000000  1.428571   \n",
       "8          (Green)       (White)      0.2    1.000000  1.428571   \n",
       "12    (Red, Green)       (White)      0.2    1.000000  1.428571   \n",
       "2            (Red)        (Blue)      0.4    0.666667  1.111111   \n",
       "3           (Blue)         (Red)      0.4    0.666667  1.111111   \n",
       "0            (Red)       (White)      0.4    0.666667  0.952381   \n",
       "1          (White)         (Red)      0.4    0.571429  0.952381   \n",
       "5           (Blue)       (White)      0.4    0.666667  0.952381   \n",
       "6          (White)        (Blue)      0.4    0.571429  0.952381   \n",
       "10   (White, Blue)         (Red)      0.2    0.500000  0.833333   \n",
       "11    (Red, White)        (Blue)      0.2    0.500000  0.833333   \n",
       "9      (Red, Blue)       (White)      0.2    0.500000  0.714286   \n",
       "\n",
       "    representativity  leverage  zhangs_metric   jaccard  certainty  kulczynski  \n",
       "13               1.0      0.12       1.000000  0.500000   0.375000    0.750000  \n",
       "15               1.0      0.12       0.750000  0.500000   1.000000    0.750000  \n",
       "4                1.0      0.08       0.500000  0.333333   1.000000    0.666667  \n",
       "14               1.0      0.08       0.500000  0.333333   1.000000    0.666667  \n",
       "7                1.0      0.06       0.375000  0.285714   1.000000    0.642857  \n",
       "8                1.0      0.06       0.375000  0.285714   1.000000    0.642857  \n",
       "12               1.0      0.06       0.375000  0.285714   1.000000    0.642857  \n",
       "2                1.0      0.04       0.250000  0.500000   0.166667    0.666667  \n",
       "3                1.0      0.04       0.250000  0.500000   0.166667    0.666667  \n",
       "0                1.0     -0.02      -0.111111  0.444444  -0.111111    0.619048  \n",
       "1                1.0     -0.02      -0.142857  0.444444  -0.071429    0.619048  \n",
       "5                1.0     -0.02      -0.111111  0.444444  -0.111111    0.619048  \n",
       "6                1.0     -0.02      -0.142857  0.444444  -0.071429    0.619048  \n",
       "10               1.0     -0.04      -0.250000  0.250000  -0.250000    0.416667  \n",
       "11               1.0     -0.04      -0.250000  0.250000  -0.250000    0.416667  \n",
       "9                1.0     -0.08      -0.400000  0.222222  -0.666667    0.392857  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Frequent ItemSets\n",
    "itemsets = apriori(df, min_support = 0.2, use_colnames = True)\n",
    "# Association Rules\n",
    "rules = association_rules(itemsets, metric = 'confidence', min_threshold = 0.5)\n",
    "pd.DataFrame(rules.sort_values(by = ['lift'], ascending = False).drop(columns = ['antecedent support','consequent support','conviction']))\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca7d7ef3-8080-45fe-84cb-2b4e460db23c",
   "metadata": {},
   "source": [
    "#### BOOK CLUB DATASET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c3eb56d6-3b1c-4044-b70c-1ac81bd56384",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Seq#</th>\n",
       "      <th>ID#</th>\n",
       "      <th>Gender</th>\n",
       "      <th>M</th>\n",
       "      <th>R</th>\n",
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       "      <td>25</td>\n",
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       "      <td>29</td>\n",
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       "      <td>22</td>\n",
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       "      <td>1</td>\n",
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       "      <td>228</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
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       "      <th>4</th>\n",
       "      <td>5</td>\n",
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       "      <td>0</td>\n",
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       "<p>5 rows × 24 columns</p>\n",
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       "   Seq#  ID#  Gender    M   R  F  FirstPurch  ChildBks  YouthBks  CookBks  \\\n",
       "0     1   25       1  297  14  2          22         0         1        1   \n",
       "1     2   29       0  128   8  2          10         0         0        0   \n",
       "2     3   46       1  138  22  7          56         2         1        2   \n",
       "3     4   47       1  228   2  1           2         0         0        0   \n",
       "4     5   51       1  257  10  1          10         0         0        0   \n",
       "\n",
       "   ...  ItalCook  ItalAtlas  ItalArt  Florence  Related Purchase  Mcode  \\\n",
       "0  ...         0          0        0         0                 0      5   \n",
       "1  ...         0          0        0         0                 0      4   \n",
       "2  ...         1          0        0         0                 2      4   \n",
       "3  ...         0          0        0         0                 0      5   \n",
       "4  ...         0          0        0         0                 0      5   \n",
       "\n",
       "   Rcode  Fcode  Yes_Florence  No_Florence  \n",
       "0      4      2             0            1  \n",
       "1      3      2             0            1  \n",
       "2      4      3             0            1  \n",
       "3      1      1             0            1  \n",
       "4      3      1             0            1  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(r'/Users/patriciaxufre/Documents/SBE - Disciplinas/2957 | ABA/2024-25/Datasets Examples/CharlesBookClub.csv')\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c351597f-fca7-44de-bf56-b0d39d3a4371",
   "metadata": {},
   "outputs": [],
   "source": [
    "ignore = ['Seq#', 'ID#', 'Gender', 'M', 'R', 'F', 'FirstPurch', 'Related Purchase', 'Mcode', 'Rcode', 'Fcode', 'Yes_Florence', 'No_Florence']\n",
    "books = df.drop(columns = ignore)\n",
    "books[books>0] = 1 # it is a binary variable saying if that type of book was bought in the past\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ee121d6a-10f6-4019-98c2-eab67958f95a",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   ChildBks  YouthBks  CookBks  DoItYBks  RefBks  ArtBks  GeogBks  ItalCook  \\\n",
       "0         0         1        1         0       0       0        0         0   \n",
       "1         0         0        0         0       0       0        0         0   \n",
       "2         1         1        1         0       1       0        1         1   \n",
       "3         0         0        0         0       0       0        0         0   \n",
       "4         0         0        0         0       0       0        0         0   \n",
       "\n",
       "   ItalAtlas  ItalArt  Florence  \n",
       "0          0        0         0  \n",
       "1          0        0         0  \n",
       "2          0        0         0  \n",
       "3          0        0         0  \n",
       "4          0        0         0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "43eafcb8-1579-46e6-af4e-c2328c40643a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.12/site-packages/mlxtend/frequent_patterns/fpcommon.py:161: DeprecationWarning: DataFrames with non-bool types result in worse computationalperformance and their support might be discontinued in the future.Please use a DataFrame with bool type\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Frequent itemsets and Rules\n",
    "itemsets = apriori(books, min_support = 0.05, use_colnames = True)\n",
    "rules = association_rules(itemsets, metric = 'confidence', min_threshold = 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "418d33c4-150e-48b3-80db-ab28ec5694bf",
   "metadata": {},
   "outputs": [
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       "      <td>0.038865</td>\n",
       "      <td>0.699207</td>\n",
       "      <td>0.224154</td>\n",
       "      <td>0.554304</td>\n",
       "      <td>0.457631</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.042014</td>\n",
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       "      <td>0.240791</td>\n",
       "      <td>0.536821</td>\n",
       "      <td>0.462885</td>\n",
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       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>(GeogBks, RefBks)</td>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "      <td>0.05025</td>\n",
       "      <td>0.614679</td>\n",
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       "      <td>0.030467</td>\n",
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       "      <td>0.183729</td>\n",
       "      <td>0.491661</td>\n",
       "      <td>0.411162</td>\n",
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       "      <th>69</th>\n",
       "      <td>(GeogBks, YouthBks)</td>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "      <td>0.06325</td>\n",
       "      <td>0.605263</td>\n",
       "      <td>2.501087</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.037961</td>\n",
       "      <td>0.670211</td>\n",
       "      <td>0.223301</td>\n",
       "      <td>0.479239</td>\n",
       "      <td>0.433313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>(DoItYBks, GeogBks)</td>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "      <td>0.06050</td>\n",
       "      <td>0.599010</td>\n",
       "      <td>2.475248</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.036058</td>\n",
       "      <td>0.662959</td>\n",
       "      <td>0.214159</td>\n",
       "      <td>0.470989</td>\n",
       "      <td>0.424505</td>\n",
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       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>(GeogBks, ChildBks, CookBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.06325</td>\n",
       "      <td>0.577626</td>\n",
       "      <td>2.424452</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.037162</td>\n",
       "      <td>0.659782</td>\n",
       "      <td>0.222320</td>\n",
       "      <td>0.445521</td>\n",
       "      <td>0.421552</td>\n",
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       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>(CookBks, ChildBks, RefBks)</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>0.06125</td>\n",
       "      <td>0.591787</td>\n",
       "      <td>2.323013</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.034883</td>\n",
       "      <td>0.635276</td>\n",
       "      <td>0.206229</td>\n",
       "      <td>0.452247</td>\n",
       "      <td>0.416110</td>\n",
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       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>(DoItYBks, GeogBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.05450</td>\n",
       "      <td>0.539604</td>\n",
       "      <td>2.264864</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.030437</td>\n",
       "      <td>0.621215</td>\n",
       "      <td>0.191396</td>\n",
       "      <td>0.395607</td>\n",
       "      <td>0.384178</td>\n",
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       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>(CookBks, ChildBks, RefBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.05525</td>\n",
       "      <td>0.533816</td>\n",
       "      <td>2.240573</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.030591</td>\n",
       "      <td>0.617608</td>\n",
       "      <td>0.192845</td>\n",
       "      <td>0.388010</td>\n",
       "      <td>0.382858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>(DoItYBks, CookBks, ChildBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.06700</td>\n",
       "      <td>0.524462</td>\n",
       "      <td>2.201309</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.036564</td>\n",
       "      <td>0.625652</td>\n",
       "      <td>0.224080</td>\n",
       "      <td>0.375729</td>\n",
       "      <td>0.402840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>(CookBks, ChildBks, YouthBks)</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>0.06700</td>\n",
       "      <td>0.558333</td>\n",
       "      <td>2.191691</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.036430</td>\n",
       "      <td>0.617877</td>\n",
       "      <td>0.217709</td>\n",
       "      <td>0.407358</td>\n",
       "      <td>0.410668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>(ChildBks, RefBks)</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>0.07100</td>\n",
       "      <td>0.553606</td>\n",
       "      <td>2.173135</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.038328</td>\n",
       "      <td>0.619255</td>\n",
       "      <td>0.227564</td>\n",
       "      <td>0.401015</td>\n",
       "      <td>0.416155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>(GeogBks, ChildBks, CookBks)</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>0.06050</td>\n",
       "      <td>0.552511</td>\n",
       "      <td>2.168838</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.032605</td>\n",
       "      <td>0.605192</td>\n",
       "      <td>0.199177</td>\n",
       "      <td>0.399546</td>\n",
       "      <td>0.395000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>(GeogBks, ChildBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.07550</td>\n",
       "      <td>0.516239</td>\n",
       "      <td>2.166797</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.040656</td>\n",
       "      <td>0.630734</td>\n",
       "      <td>0.244337</td>\n",
       "      <td>0.364935</td>\n",
       "      <td>0.416567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>(GeogBks, CookBks)</td>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>0.08025</td>\n",
       "      <td>0.513600</td>\n",
       "      <td>2.155719</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.043023</td>\n",
       "      <td>0.635399</td>\n",
       "      <td>0.255370</td>\n",
       "      <td>0.361470</td>\n",
       "      <td>0.425216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>(ChildBks, YouthBks, RefBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.05525</td>\n",
       "      <td>0.891129</td>\n",
       "      <td>2.144715</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.029489</td>\n",
       "      <td>0.569017</td>\n",
       "      <td>0.130847</td>\n",
       "      <td>0.813737</td>\n",
       "      <td>0.512051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>(ChildBks, YouthBks)</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>0.08025</td>\n",
       "      <td>0.544068</td>\n",
       "      <td>2.135693</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.042674</td>\n",
       "      <td>0.623775</td>\n",
       "      <td>0.249224</td>\n",
       "      <td>0.388216</td>\n",
       "      <td>0.429541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>(CookBks, RefBks)</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>0.07450</td>\n",
       "      <td>0.533095</td>\n",
       "      <td>2.092619</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.038899</td>\n",
       "      <td>0.606952</td>\n",
       "      <td>0.232813</td>\n",
       "      <td>0.373492</td>\n",
       "      <td>0.412769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>(RefBks)</td>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "      <td>0.10350</td>\n",
       "      <td>0.505495</td>\n",
       "      <td>2.088820</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.053950</td>\n",
       "      <td>0.655468</td>\n",
       "      <td>0.301529</td>\n",
       "      <td>0.347618</td>\n",
       "      <td>0.466590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>(DoItYBks, CookBks, RefBks)</td>\n",
       "      <td>(ChildBks)</td>\n",
       "      <td>0.06125</td>\n",
       "      <td>0.822148</td>\n",
       "      <td>2.086669</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.031897</td>\n",
       "      <td>0.562688</td>\n",
       "      <td>0.150399</td>\n",
       "      <td>0.706514</td>\n",
       "      <td>0.488802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>(YouthBks)</td>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "      <td>0.12000</td>\n",
       "      <td>0.503673</td>\n",
       "      <td>2.081292</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.062344</td>\n",
       "      <td>0.682021</td>\n",
       "      <td>0.333102</td>\n",
       "      <td>0.345215</td>\n",
       "      <td>0.499770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>(DoItYBks, ChildBks, RefBks)</td>\n",
       "      <td>(CookBks)</td>\n",
       "      <td>0.06125</td>\n",
       "      <td>0.862676</td>\n",
       "      <td>2.076236</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.031749</td>\n",
       "      <td>0.557975</td>\n",
       "      <td>0.144033</td>\n",
       "      <td>0.765057</td>\n",
       "      <td>0.505044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>0.12775</td>\n",
       "      <td>0.527893</td>\n",
       "      <td>2.072198</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.066101</td>\n",
       "      <td>0.682613</td>\n",
       "      <td>0.346206</td>\n",
       "      <td>0.366511</td>\n",
       "      <td>0.514682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>(DoItYBks)</td>\n",
       "      <td>(CookBks, ChildBks)</td>\n",
       "      <td>0.12775</td>\n",
       "      <td>0.501472</td>\n",
       "      <td>2.072198</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.066101</td>\n",
       "      <td>0.694292</td>\n",
       "      <td>0.346206</td>\n",
       "      <td>0.342311</td>\n",
       "      <td>0.514682</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      antecedents          consequents  support  confidence  \\\n",
       "64             (YouthBks, RefBks)  (CookBks, ChildBks)  0.05525    0.680000   \n",
       "73             (DoItYBks, RefBks)  (CookBks, ChildBks)  0.06125    0.662162   \n",
       "60           (DoItYBks, YouthBks)  (CookBks, ChildBks)  0.06700    0.648910   \n",
       "80              (GeogBks, RefBks)  (CookBks, ChildBks)  0.05025    0.614679   \n",
       "69            (GeogBks, YouthBks)  (CookBks, ChildBks)  0.06325    0.605263   \n",
       "77            (DoItYBks, GeogBks)  (CookBks, ChildBks)  0.06050    0.599010   \n",
       "65   (GeogBks, ChildBks, CookBks)           (YouthBks)  0.06325    0.577626   \n",
       "72    (CookBks, ChildBks, RefBks)           (DoItYBks)  0.06125    0.591787   \n",
       "47            (DoItYBks, GeogBks)           (YouthBks)  0.05450    0.539604   \n",
       "61    (CookBks, ChildBks, RefBks)           (YouthBks)  0.05525    0.533816   \n",
       "56  (DoItYBks, CookBks, ChildBks)           (YouthBks)  0.06700    0.524462   \n",
       "59  (CookBks, ChildBks, YouthBks)           (DoItYBks)  0.06700    0.558333   \n",
       "34             (ChildBks, RefBks)           (DoItYBks)  0.07100    0.553606   \n",
       "76   (GeogBks, ChildBks, CookBks)           (DoItYBks)  0.06050    0.552511   \n",
       "19            (GeogBks, ChildBks)           (YouthBks)  0.07550    0.516239   \n",
       "45             (GeogBks, CookBks)           (YouthBks)  0.08025    0.513600   \n",
       "63   (ChildBks, YouthBks, RefBks)            (CookBks)  0.05525    0.891129   \n",
       "17           (ChildBks, YouthBks)           (DoItYBks)  0.08025    0.544068   \n",
       "51              (CookBks, RefBks)           (DoItYBks)  0.07450    0.533095   \n",
       "28                       (RefBks)  (CookBks, ChildBks)  0.10350    0.505495   \n",
       "70    (DoItYBks, CookBks, RefBks)           (ChildBks)  0.06125    0.822148   \n",
       "15                     (YouthBks)  (CookBks, ChildBks)  0.12000    0.503673   \n",
       "71   (DoItYBks, ChildBks, RefBks)            (CookBks)  0.06125    0.862676   \n",
       "24            (CookBks, ChildBks)           (DoItYBks)  0.12775    0.527893   \n",
       "25                     (DoItYBks)  (CookBks, ChildBks)  0.12775    0.501472   \n",
       "\n",
       "        lift  representativity  leverage  zhangs_metric   jaccard  certainty  \\\n",
       "64  2.809917               1.0  0.035588       0.701080  0.206157   0.577836   \n",
       "73  2.736207               1.0  0.038865       0.699207  0.224154   0.554304   \n",
       "60  2.681448               1.0  0.042014       0.699266  0.240791   0.536821   \n",
       "80  2.539995               1.0  0.030467       0.660276  0.183729   0.491661   \n",
       "69  2.501087               1.0  0.037961       0.670211  0.223301   0.479239   \n",
       "77  2.475248               1.0  0.036058       0.662959  0.214159   0.470989   \n",
       "65  2.424452               1.0  0.037162       0.659782  0.222320   0.445521   \n",
       "72  2.323013               1.0  0.034883       0.635276  0.206229   0.452247   \n",
       "47  2.264864               1.0  0.030437       0.621215  0.191396   0.395607   \n",
       "61  2.240573               1.0  0.030591       0.617608  0.192845   0.388010   \n",
       "56  2.201309               1.0  0.036564       0.625652  0.224080   0.375729   \n",
       "59  2.191691               1.0  0.036430       0.617877  0.217709   0.407358   \n",
       "34  2.173135               1.0  0.038328       0.619255  0.227564   0.401015   \n",
       "76  2.168838               1.0  0.032605       0.605192  0.199177   0.399546   \n",
       "19  2.166797               1.0  0.040656       0.630734  0.244337   0.364935   \n",
       "45  2.155719               1.0  0.043023       0.635399  0.255370   0.361470   \n",
       "63  2.144715               1.0  0.029489       0.569017  0.130847   0.813737   \n",
       "17  2.135693               1.0  0.042674       0.623775  0.249224   0.388216   \n",
       "51  2.092619               1.0  0.038899       0.606952  0.232813   0.373492   \n",
       "28  2.088820               1.0  0.053950       0.655468  0.301529   0.347618   \n",
       "70  2.086669               1.0  0.031897       0.562688  0.150399   0.706514   \n",
       "15  2.081292               1.0  0.062344       0.682021  0.333102   0.345215   \n",
       "71  2.076236               1.0  0.031749       0.557975  0.144033   0.765057   \n",
       "24  2.072198               1.0  0.066101       0.682613  0.346206   0.366511   \n",
       "25  2.072198               1.0  0.066101       0.694292  0.346206   0.342311   \n",
       "\n",
       "    kulczynski  \n",
       "64    0.454153  \n",
       "73    0.457631  \n",
       "60    0.462885  \n",
       "80    0.411162  \n",
       "69    0.433313  \n",
       "77    0.424505  \n",
       "65    0.421552  \n",
       "72    0.416110  \n",
       "47    0.384178  \n",
       "61    0.382858  \n",
       "56    0.402840  \n",
       "59    0.410668  \n",
       "34    0.416155  \n",
       "76    0.395000  \n",
       "19    0.416567  \n",
       "45    0.425216  \n",
       "63    0.512051  \n",
       "17    0.429541  \n",
       "51    0.412769  \n",
       "28    0.466590  \n",
       "70    0.488802  \n",
       "15    0.499770  \n",
       "71    0.505044  \n",
       "24    0.514682  \n",
       "25    0.514682  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display 25 rules with highest lift\n",
    "rules.sort_values(by = ['lift'], ascending = False). drop(columns = ['antecedent support', 'consequent support','conviction']).head(25) \n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a15b6fc-b439-4765-a76f-f920579d4e9f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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