Online Retail K-Means and Hierarchial Clustering in class.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sklearn\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.cluster import AgglomerativeClustering\n",
    "from scipy.cluster.hierarchy import linkage\n",
    "from scipy.cluster.hierarchy import dendrogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>2.75</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>536365</td>\n",
       "      <td>22752</td>\n",
       "      <td>SET 7 BABUSHKA NESTING BOXES</td>\n",
       "      <td>2</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>7.65</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>536365</td>\n",
       "      <td>21730</td>\n",
       "      <td>GLASS STAR FROSTED T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>4.25</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>536366</td>\n",
       "      <td>22633</td>\n",
       "      <td>HAND WARMER UNION JACK</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:28</td>\n",
       "      <td>1.85</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>536366</td>\n",
       "      <td>22632</td>\n",
       "      <td>HAND WARMER RED POLKA DOT</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:28</td>\n",
       "      <td>1.85</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>536367</td>\n",
       "      <td>84879</td>\n",
       "      <td>ASSORTED COLOUR BIRD ORNAMENT</td>\n",
       "      <td>32</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>1.69</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>536367</td>\n",
       "      <td>22745</td>\n",
       "      <td>POPPY'S PLAYHOUSE BEDROOM</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>2.10</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>536367</td>\n",
       "      <td>22748</td>\n",
       "      <td>POPPY'S PLAYHOUSE KITCHEN</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>2.10</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>536367</td>\n",
       "      <td>22749</td>\n",
       "      <td>FELTCRAFT PRINCESS CHARLOTTE DOLL</td>\n",
       "      <td>8</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>3.75</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>536367</td>\n",
       "      <td>22310</td>\n",
       "      <td>IVORY KNITTED MUG COSY</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>1.65</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>536367</td>\n",
       "      <td>84969</td>\n",
       "      <td>BOX OF 6 ASSORTED COLOUR TEASPOONS</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>4.25</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>536367</td>\n",
       "      <td>22623</td>\n",
       "      <td>BOX OF VINTAGE JIGSAW BLOCKS</td>\n",
       "      <td>3</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>4.95</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>536367</td>\n",
       "      <td>22622</td>\n",
       "      <td>BOX OF VINTAGE ALPHABET BLOCKS</td>\n",
       "      <td>2</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>9.95</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>536367</td>\n",
       "      <td>21754</td>\n",
       "      <td>HOME BUILDING BLOCK WORD</td>\n",
       "      <td>3</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>5.95</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>536367</td>\n",
       "      <td>21755</td>\n",
       "      <td>LOVE BUILDING BLOCK WORD</td>\n",
       "      <td>3</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>5.95</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>536367</td>\n",
       "      <td>21777</td>\n",
       "      <td>RECIPE BOX WITH METAL HEART</td>\n",
       "      <td>4</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>7.95</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   InvoiceNo StockCode                          Description  Quantity  \\\n",
       "0     536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1     536365     71053                  WHITE METAL LANTERN         6   \n",
       "2     536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3     536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4     536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "5     536365     22752         SET 7 BABUSHKA NESTING BOXES         2   \n",
       "6     536365     21730    GLASS STAR FROSTED T-LIGHT HOLDER         6   \n",
       "7     536366     22633               HAND WARMER UNION JACK         6   \n",
       "8     536366     22632            HAND WARMER RED POLKA DOT         6   \n",
       "9     536367     84879        ASSORTED COLOUR BIRD ORNAMENT        32   \n",
       "10    536367     22745           POPPY'S PLAYHOUSE BEDROOM          6   \n",
       "11    536367     22748            POPPY'S PLAYHOUSE KITCHEN         6   \n",
       "12    536367     22749    FELTCRAFT PRINCESS CHARLOTTE DOLL         8   \n",
       "13    536367     22310              IVORY KNITTED MUG COSY          6   \n",
       "14    536367     84969   BOX OF 6 ASSORTED COLOUR TEASPOONS         6   \n",
       "15    536367     22623        BOX OF VINTAGE JIGSAW BLOCKS          3   \n",
       "16    536367     22622       BOX OF VINTAGE ALPHABET BLOCKS         2   \n",
       "17    536367     21754             HOME BUILDING BLOCK WORD         3   \n",
       "18    536367     21755             LOVE BUILDING BLOCK WORD         3   \n",
       "19    536367     21777          RECIPE BOX WITH METAL HEART         4   \n",
       "\n",
       "         InvoiceDate  UnitPrice  CustomerID         Country  \n",
       "0   01-12-2010 08:26       2.55     17850.0  United Kingdom  \n",
       "1   01-12-2010 08:26       3.39     17850.0  United Kingdom  \n",
       "2   01-12-2010 08:26       2.75     17850.0  United Kingdom  \n",
       "3   01-12-2010 08:26       3.39     17850.0  United Kingdom  \n",
       "4   01-12-2010 08:26       3.39     17850.0  United Kingdom  \n",
       "5   01-12-2010 08:26       7.65     17850.0  United Kingdom  \n",
       "6   01-12-2010 08:26       4.25     17850.0  United Kingdom  \n",
       "7   01-12-2010 08:28       1.85     17850.0  United Kingdom  \n",
       "8   01-12-2010 08:28       1.85     17850.0  United Kingdom  \n",
       "9   01-12-2010 08:34       1.69     13047.0  United Kingdom  \n",
       "10  01-12-2010 08:34       2.10     13047.0  United Kingdom  \n",
       "11  01-12-2010 08:34       2.10     13047.0  United Kingdom  \n",
       "12  01-12-2010 08:34       3.75     13047.0  United Kingdom  \n",
       "13  01-12-2010 08:34       1.65     13047.0  United Kingdom  \n",
       "14  01-12-2010 08:34       4.25     13047.0  United Kingdom  \n",
       "15  01-12-2010 08:34       4.95     13047.0  United Kingdom  \n",
       "16  01-12-2010 08:34       9.95     13047.0  United Kingdom  \n",
       "17  01-12-2010 08:34       5.95     13047.0  United Kingdom  \n",
       "18  01-12-2010 08:34       5.95     13047.0  United Kingdom  \n",
       "19  01-12-2010 08:34       7.95     13047.0  United Kingdom  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retail = pd.read_csv('OnlineRetail.csv', sep = \",\", header = 0, encoding = 'ISO-8859-1')\n",
    "\n",
    "retail.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(541909, 8)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retail.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 541909 entries, 0 to 541908\n",
      "Data columns (total 8 columns):\n",
      " #   Column       Non-Null Count   Dtype  \n",
      "---  ------       --------------   -----  \n",
      " 0   InvoiceNo    541909 non-null  object \n",
      " 1   StockCode    541909 non-null  object \n",
      " 2   Description  540455 non-null  object \n",
      " 3   Quantity     541909 non-null  int64  \n",
      " 4   InvoiceDate  541909 non-null  object \n",
      " 5   UnitPrice    541909 non-null  float64\n",
      " 6   CustomerID   406829 non-null  float64\n",
      " 7   Country      541909 non-null  object \n",
      "dtypes: float64(2), int64(1), object(5)\n",
      "memory usage: 33.1+ MB\n"
     ]
    }
   ],
   "source": [
    "retail.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_null = round(100*retail.isnull().sum() / len(retail), 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InvoiceNo       0.00\n",
       "StockCode       0.00\n",
       "Description     0.27\n",
       "Quantity        0.00\n",
       "InvoiceDate     0.00\n",
       "UnitPrice       0.00\n",
       "CustomerID     24.93\n",
       "Country         0.00\n",
       "dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_null"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(406829, 8)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retail = retail.dropna()\n",
    "\n",
    "retail.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-13-01bc0005d4f0>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  retail['CustomerID'] = retail['CustomerID'].astype(str)\n"
     ]
    }
   ],
   "source": [
    "retail['CustomerID'] = retail['CustomerID'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>2.75</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                          Description  Quantity  \\\n",
       "0    536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1    536365     71053                  WHITE METAL LANTERN         6   \n",
       "2    536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3    536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4    536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "\n",
       "        InvoiceDate  UnitPrice CustomerID         Country  \n",
       "0  01-12-2010 08:26       2.55    17850.0  United Kingdom  \n",
       "1  01-12-2010 08:26       3.39    17850.0  United Kingdom  \n",
       "2  01-12-2010 08:26       2.75    17850.0  United Kingdom  \n",
       "3  01-12-2010 08:26       3.39    17850.0  United Kingdom  \n",
       "4  01-12-2010 08:26       3.39    17850.0  United Kingdom  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retail.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Amount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-15-8d12135a4675>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  retail['Amount'] = retail['Quantity'] * retail['UnitPrice']\n"
     ]
    }
   ],
   "source": [
    "retail['Amount'] = retail['Quantity'] * retail['UnitPrice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "      <th>Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>2.75</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>22.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>536365</td>\n",
       "      <td>22752</td>\n",
       "      <td>SET 7 BABUSHKA NESTING BOXES</td>\n",
       "      <td>2</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>7.65</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>536365</td>\n",
       "      <td>21730</td>\n",
       "      <td>GLASS STAR FROSTED T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:26</td>\n",
       "      <td>4.25</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>25.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>536366</td>\n",
       "      <td>22633</td>\n",
       "      <td>HAND WARMER UNION JACK</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:28</td>\n",
       "      <td>1.85</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>11.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>536366</td>\n",
       "      <td>22632</td>\n",
       "      <td>HAND WARMER RED POLKA DOT</td>\n",
       "      <td>6</td>\n",
       "      <td>01-12-2010 08:28</td>\n",
       "      <td>1.85</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>11.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>536367</td>\n",
       "      <td>84879</td>\n",
       "      <td>ASSORTED COLOUR BIRD ORNAMENT</td>\n",
       "      <td>32</td>\n",
       "      <td>01-12-2010 08:34</td>\n",
       "      <td>1.69</td>\n",
       "      <td>13047.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>54.08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                          Description  Quantity  \\\n",
       "0    536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1    536365     71053                  WHITE METAL LANTERN         6   \n",
       "2    536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3    536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4    536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "5    536365     22752         SET 7 BABUSHKA NESTING BOXES         2   \n",
       "6    536365     21730    GLASS STAR FROSTED T-LIGHT HOLDER         6   \n",
       "7    536366     22633               HAND WARMER UNION JACK         6   \n",
       "8    536366     22632            HAND WARMER RED POLKA DOT         6   \n",
       "9    536367     84879        ASSORTED COLOUR BIRD ORNAMENT        32   \n",
       "\n",
       "        InvoiceDate  UnitPrice CustomerID         Country  Amount  \n",
       "0  01-12-2010 08:26       2.55    17850.0  United Kingdom   15.30  \n",
       "1  01-12-2010 08:26       3.39    17850.0  United Kingdom   20.34  \n",
       "2  01-12-2010 08:26       2.75    17850.0  United Kingdom   22.00  \n",
       "3  01-12-2010 08:26       3.39    17850.0  United Kingdom   20.34  \n",
       "4  01-12-2010 08:26       3.39    17850.0  United Kingdom   20.34  \n",
       "5  01-12-2010 08:26       7.65    17850.0  United Kingdom   15.30  \n",
       "6  01-12-2010 08:26       4.25    17850.0  United Kingdom   25.50  \n",
       "7  01-12-2010 08:28       1.85    17850.0  United Kingdom   11.10  \n",
       "8  01-12-2010 08:28       1.85    17850.0  United Kingdom   11.10  \n",
       "9  01-12-2010 08:34       1.69    13047.0  United Kingdom   54.08  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retail.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "rfm_m = retail.groupby('CustomerID')['Amount'].sum()"
   ]
  },
  {
   "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>CustomerID</th>\n",
       "      <th>Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12346.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12347.0</td>\n",
       "      <td>4310.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12348.0</td>\n",
       "      <td>1797.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12349.0</td>\n",
       "      <td>1757.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12350.0</td>\n",
       "      <td>334.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CustomerID   Amount\n",
       "0    12346.0     0.00\n",
       "1    12347.0  4310.00\n",
       "2    12348.0  1797.24\n",
       "3    12349.0  1757.55\n",
       "4    12350.0   334.40"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm_m = rfm_m.reset_index()\n",
    "rfm_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CustomerID\n",
       "12346.0       0.00\n",
       "12347.0    4310.00\n",
       "12348.0    1797.24\n",
       "12349.0    1757.55\n",
       "12350.0     334.40\n",
       "Name: Amount, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm_m.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FREQUENCY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "rfm_f = retail.groupby('CustomerID')['InvoiceNo'].count()"
   ]
  },
  {
   "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>CustomerID</th>\n",
       "      <th>Frequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12346.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12347.0</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12348.0</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12349.0</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12350.0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CustomerID  Frequency\n",
       "0    12346.0          2\n",
       "1    12347.0        182\n",
       "2    12348.0         31\n",
       "3    12349.0         73\n",
       "4    12350.0         17"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm_f = rfm_f.reset_index()\n",
    "rfm_f.columns = ['CustomerID', 'Frequency']\n",
    "rfm_f.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>CustomerID</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Frequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12346.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12347.0</td>\n",
       "      <td>4310.00</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12348.0</td>\n",
       "      <td>1797.24</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12349.0</td>\n",
       "      <td>1757.55</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12350.0</td>\n",
       "      <td>334.40</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CustomerID   Amount  Frequency\n",
       "0    12346.0     0.00          2\n",
       "1    12347.0  4310.00        182\n",
       "2    12348.0  1797.24         31\n",
       "3    12349.0  1757.55         73\n",
       "4    12350.0   334.40         17"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm = pd.merge(rfm_m, rfm_f, on='CustomerID', how='inner')\n",
    "rfm.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-26-ec971941a2fc>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  retail['InvoiceDate'] = pd.to_datetime(retail['InvoiceDate'],format='%d-%m-%Y %H:%M')\n"
     ]
    }
   ],
   "source": [
    "retail['InvoiceDate'] = pd.to_datetime(retail['InvoiceDate'],format='%d-%m-%Y %H:%M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        2010-12-01 08:26:00\n",
       "1        2010-12-01 08:26:00\n",
       "2        2010-12-01 08:26:00\n",
       "3        2010-12-01 08:26:00\n",
       "4        2010-12-01 08:26:00\n",
       "                 ...        \n",
       "541904   2011-12-09 12:50:00\n",
       "541905   2011-12-09 12:50:00\n",
       "541906   2011-12-09 12:50:00\n",
       "541907   2011-12-09 12:50:00\n",
       "541908   2011-12-09 12:50:00\n",
       "Name: InvoiceDate, Length: 406829, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retail['InvoiceDate']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2011-12-09 12:50:00')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_date= max(retail['InvoiceDate'])\n",
    "max_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-29-62716a925d64>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  retail['Diff'] = max_date - retail['InvoiceDate']\n"
     ]
    },
    {
     "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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.30</td>\n",
       "      <td>373 days 04:24:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.34</td>\n",
       "      <td>373 days 04:24:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.75</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>22.00</td>\n",
       "      <td>373 days 04:24:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.34</td>\n",
       "      <td>373 days 04:24:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.34</td>\n",
       "      <td>373 days 04:24:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                          Description  Quantity  \\\n",
       "0    536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1    536365     71053                  WHITE METAL LANTERN         6   \n",
       "2    536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3    536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4    536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "\n",
       "          InvoiceDate  UnitPrice CustomerID         Country  Amount  \\\n",
       "0 2010-12-01 08:26:00       2.55    17850.0  United Kingdom   15.30   \n",
       "1 2010-12-01 08:26:00       3.39    17850.0  United Kingdom   20.34   \n",
       "2 2010-12-01 08:26:00       2.75    17850.0  United Kingdom   22.00   \n",
       "3 2010-12-01 08:26:00       3.39    17850.0  United Kingdom   20.34   \n",
       "4 2010-12-01 08:26:00       3.39    17850.0  United Kingdom   20.34   \n",
       "\n",
       "               Diff  \n",
       "0 373 days 04:24:00  \n",
       "1 373 days 04:24:00  \n",
       "2 373 days 04:24:00  \n",
       "3 373 days 04:24:00  \n",
       "4 373 days 04:24:00  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "retail['Diff'] = max_date - retail['InvoiceDate']\n",
    "retail.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>CustomerID</th>\n",
       "      <th>Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12346.0</td>\n",
       "      <td>325 days 02:33:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12347.0</td>\n",
       "      <td>1 days 20:58:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12348.0</td>\n",
       "      <td>74 days 23:37:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12349.0</td>\n",
       "      <td>18 days 02:59:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12350.0</td>\n",
       "      <td>309 days 20:49:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CustomerID              Diff\n",
       "0    12346.0 325 days 02:33:00\n",
       "1    12347.0   1 days 20:58:00\n",
       "2    12348.0  74 days 23:37:00\n",
       "3    12349.0  18 days 02:59:00\n",
       "4    12350.0 309 days 20:49:00"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm_p = retail.groupby('CustomerID')['Diff'].min()\n",
    "rfm_p = rfm_p.reset_index()\n",
    "rfm_p.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>CustomerID</th>\n",
       "      <th>Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12346.0</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12347.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12348.0</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12349.0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12350.0</td>\n",
       "      <td>309</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CustomerID  Diff\n",
       "0    12346.0   325\n",
       "1    12347.0     1\n",
       "2    12348.0    74\n",
       "3    12349.0    18\n",
       "4    12350.0   309"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm_p['Diff'] = rfm_p['Diff'].dt.days\n",
    "rfm_p.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "rfm = pd.merge(rfm, rfm_p, on='CustomerID', how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>CustomerID</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Recency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12346.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12347.0</td>\n",
       "      <td>4310.00</td>\n",
       "      <td>182</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12348.0</td>\n",
       "      <td>1797.24</td>\n",
       "      <td>31</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12349.0</td>\n",
       "      <td>1757.55</td>\n",
       "      <td>73</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12350.0</td>\n",
       "      <td>334.40</td>\n",
       "      <td>17</td>\n",
       "      <td>309</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CustomerID   Amount  Frequency  Recency\n",
       "0    12346.0     0.00          2      325\n",
       "1    12347.0  4310.00        182        1\n",
       "2    12348.0  1797.24         31       74\n",
       "3    12349.0  1757.55         73       18\n",
       "4    12350.0   334.40         17      309"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm.columns = ['CustomerID', 'Amount', 'Frequency', 'Recency']\n",
    "rfm.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Attributes')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "attributes = ['Amount','Frequency','Recency']\n",
    "plt.rcParams['figure.figsize'] = [10,8]\n",
    "sns.boxplot(data = rfm[attributes], orient=\"v\")\n",
    "\n",
    "plt.title(\"Outliers Variable Distribution\", fontsize = 14, fontweight = 'bold')\n",
    "plt.ylabel(\"Range\", fontweight = 'bold')\n",
    "plt.xlabel(\"Attributes\", fontweight = 'bold')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing (statistical) outliers for Amount\n",
    "Q1 = rfm.Amount.quantile(0.05)\n",
    "Q3 = rfm.Amount.quantile(0.95)\n",
    "IQR = Q3 - Q1\n",
    "rfm = rfm[(rfm.Amount >= Q1 - 1.5*IQR) & (rfm.Amount <= Q3 + 1.5*IQR)]\n",
    "\n",
    "# Removing (statistical) outliers for Recency\n",
    "Q1 = rfm.Recency.quantile(0.05)\n",
    "Q3 = rfm.Recency.quantile(0.95)\n",
    "IQR = Q3 - Q1\n",
    "rfm = rfm[(rfm.Recency >= Q1 - 1.5*IQR) & (rfm.Recency <= Q3 + 1.5*IQR)]\n",
    "\n",
    "# Removing (statistical) outliers for Frequency\n",
    "Q1 = rfm.Frequency.quantile(0.05)\n",
    "Q3 = rfm.Frequency.quantile(0.95)\n",
    "IQR = Q3 - Q1\n",
    "rfm = rfm[(rfm.Frequency >= Q1 - 1.5*IQR) & (rfm.Frequency <= Q3 + 1.5*IQR)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4293, 3)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "rfm_df = rfm[['Amount', 'Frequency', 'Recency']]\n",
    "\n",
    "# Instantiate\n",
    "scaler = StandardScaler()\n",
    "\n",
    "# fit_transform\n",
    "rfm_df_scaled = scaler.fit_transform(rfm_df)\n",
    "rfm_df_scaled.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>Amount</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Recency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.723738</td>\n",
       "      <td>-0.752888</td>\n",
       "      <td>2.301611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.731617</td>\n",
       "      <td>1.042467</td>\n",
       "      <td>-0.906466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.300128</td>\n",
       "      <td>-0.463636</td>\n",
       "      <td>-0.183658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.277517</td>\n",
       "      <td>-0.044720</td>\n",
       "      <td>-0.738141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.533235</td>\n",
       "      <td>-0.603275</td>\n",
       "      <td>2.143188</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Amount  Frequency   Recency\n",
       "0 -0.723738  -0.752888  2.301611\n",
       "1  1.731617   1.042467 -0.906466\n",
       "2  0.300128  -0.463636 -0.183658\n",
       "3  0.277517  -0.044720 -0.738141\n",
       "4 -0.533235  -0.603275  2.143188"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm_df_scaled = pd.DataFrame(rfm_df_scaled)\n",
    "rfm_df_scaled.columns = ['Amount', 'Frequency', 'Recency']\n",
    "rfm_df_scaled.head()"
   ]
  },
  {
   "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
}