Arvato Project Workbook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Capstone Project: Create a Customer Segmentation Report for Arvato Financial Services\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this project, I will analyze demographics data for customers of a mail-order sales company in Germany, comparing it against demographics information for the general population.<br> <br>\n",
    "\n",
    "Throughout this project, I will be focusing on the following:<br>\n",
    "\n",
    "1. Use unsupervised learning techniques to perform customer segmentation<br>\n",
    "2. Tdentifying the parts of the population that best describe the core customer base of the company.<br>\n",
    "3. Apply learning on a third dataset with demographics information for targets of a marketing campaign for the company and use a model to predict which individuals are most likely to convert into becoming customers for the company"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "import random\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from catboost import CatBoostClassifier\n",
    "from sklearn.pipeline import Pipeline\n",
    "\n",
    "\n",
    "import Helper as h"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 0: Get to Know the Data\n",
    "\n",
    "There are four data files associated with this project:\n",
    "\n",
    "- `Udacity_AZDIAS_052018.csv`: Demographics data for the general population of Germany; 891 211 persons (rows) x 366 features (columns).\n",
    "- `Udacity_CUSTOMERS_052018.csv`: Demographics data for customers of a mail-order company; 191 652 persons (rows) x 369 features (columns).\n",
    "- `Udacity_MAILOUT_052018_TRAIN.csv`: Demographics data for individuals who were targets of a marketing campaign; 42 982 persons (rows) x 367 (columns).\n",
    "- `Udacity_MAILOUT_052018_TEST.csv`: Demographics data for individuals who were targets of a marketing campaign; 42 833 persons (rows) x 366 (columns).\n",
    "\n",
    "Each row of the demographics files represents a single person, but also includes information outside of individuals, including information about their household, building, and neighborhood. The information from the first two files is used to figure out how customers (\"CUSTOMERS\") are similar to or differ from the general population at large (\"AZDIAS\"), then to make predictions on the other two files (\"MAILOUT\"), predicting which recipients are most likely to become a customer for the mail-order company.\n",
    "\n",
    "The \"CUSTOMERS\" file contains three extra columns ('CUSTOMER_GROUP', 'ONLINE_PURCHASE', and 'PRODUCT_GROUP'), which provide broad information about the customers depicted in the file. The original \"MAILOUT\" file included one additional column, \"RESPONSE\", which indicated whether or not each recipient became a customer of the company. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load in the data\n",
    "df_azdias = pd.read_csv('data/Udacity_AZDIAS_052018.csv', sep=';')\n",
    "df_customers = pd.read_csv('data/Udacity_CUSTOMERS_052018.csv', sep=';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LNR</th>\n",
       "      <th>AGER_TYP</th>\n",
       "      <th>AKT_DAT_KL</th>\n",
       "      <th>ALTER_HH</th>\n",
       "      <th>ALTER_KIND1</th>\n",
       "      <th>ALTER_KIND2</th>\n",
       "      <th>ALTER_KIND3</th>\n",
       "      <th>ALTER_KIND4</th>\n",
       "      <th>ALTERSKATEGORIE_FEIN</th>\n",
       "      <th>ANZ_HAUSHALTE_AKTIV</th>\n",
       "      <th>...</th>\n",
       "      <th>VK_ZG11</th>\n",
       "      <th>W_KEIT_KIND_HH</th>\n",
       "      <th>WOHNDAUER_2008</th>\n",
       "      <th>WOHNLAGE</th>\n",
       "      <th>ZABEOTYP</th>\n",
       "      <th>PRODUCT_GROUP</th>\n",
       "      <th>CUSTOMER_GROUP</th>\n",
       "      <th>ONLINE_PURCHASE</th>\n",
       "      <th>ANREDE_KZ</th>\n",
       "      <th>ALTERSKATEGORIE_GROB</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9626</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3</td>\n",
       "      <td>COSMETIC_AND_FOOD</td>\n",
       "      <td>MULTI_BUYER</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9628</td>\n",
       "      <td>-1</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>FOOD</td>\n",
       "      <td>SINGLE_BUYER</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 369 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    LNR  AGER_TYP  AKT_DAT_KL  ALTER_HH  ALTER_KIND1  ALTER_KIND2  \\\n",
       "0  9626         2         1.0      10.0          NaN          NaN   \n",
       "1  9628        -1         9.0      11.0          NaN          NaN   \n",
       "\n",
       "   ALTER_KIND3  ALTER_KIND4  ALTERSKATEGORIE_FEIN  ANZ_HAUSHALTE_AKTIV  ...  \\\n",
       "0          NaN          NaN                  10.0                  1.0  ...   \n",
       "1          NaN          NaN                   NaN                  NaN  ...   \n",
       "\n",
       "   VK_ZG11  W_KEIT_KIND_HH  WOHNDAUER_2008  WOHNLAGE  ZABEOTYP  \\\n",
       "0      2.0             6.0             9.0       7.0         3   \n",
       "1      3.0             0.0             9.0       NaN         3   \n",
       "\n",
       "       PRODUCT_GROUP  CUSTOMER_GROUP ONLINE_PURCHASE ANREDE_KZ  \\\n",
       "0  COSMETIC_AND_FOOD     MULTI_BUYER               0         1   \n",
       "1               FOOD    SINGLE_BUYER               0         1   \n",
       "\n",
       "  ALTERSKATEGORIE_GROB  \n",
       "0                    4  \n",
       "1                    4  \n",
       "\n",
       "[2 rows x 369 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_customers.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>LNR</th>\n",
       "      <th>AGER_TYP</th>\n",
       "      <th>AKT_DAT_KL</th>\n",
       "      <th>ALTER_HH</th>\n",
       "      <th>ALTER_KIND1</th>\n",
       "      <th>ALTER_KIND2</th>\n",
       "      <th>ALTER_KIND3</th>\n",
       "      <th>ALTER_KIND4</th>\n",
       "      <th>ALTERSKATEGORIE_FEIN</th>\n",
       "      <th>ANZ_HAUSHALTE_AKTIV</th>\n",
       "      <th>...</th>\n",
       "      <th>VK_DHT4A</th>\n",
       "      <th>VK_DISTANZ</th>\n",
       "      <th>VK_ZG11</th>\n",
       "      <th>W_KEIT_KIND_HH</th>\n",
       "      <th>WOHNDAUER_2008</th>\n",
       "      <th>WOHNLAGE</th>\n",
       "      <th>ZABEOTYP</th>\n",
       "      <th>ONLINE_PURCHASE</th>\n",
       "      <th>ANREDE_KZ</th>\n",
       "      <th>ALTERSKATEGORIE_GROB</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>191652.000000</td>\n",
       "      <td>191652.000000</td>\n",
       "      <td>145056.000000</td>\n",
       "      <td>145056.000000</td>\n",
       "      <td>11766.000000</td>\n",
       "      <td>5100.000000</td>\n",
       "      <td>1275.000000</td>\n",
       "      <td>236.000000</td>\n",
       "      <td>139810.000000</td>\n",
       "      <td>141725.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>143781.000000</td>\n",
       "      <td>143781.000000</td>\n",
       "      <td>143781.000000</td>\n",
       "      <td>137910.000000</td>\n",
       "      <td>145056.000000</td>\n",
       "      <td>141725.000000</td>\n",
       "      <td>191652.000000</td>\n",
       "      <td>191652.000000</td>\n",
       "      <td>191652.000000</td>\n",
       "      <td>191652.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>95826.500000</td>\n",
       "      <td>0.344359</td>\n",
       "      <td>1.747525</td>\n",
       "      <td>11.352009</td>\n",
       "      <td>12.337243</td>\n",
       "      <td>13.672353</td>\n",
       "      <td>14.647059</td>\n",
       "      <td>15.377119</td>\n",
       "      <td>10.331579</td>\n",
       "      <td>4.965863</td>\n",
       "      <td>...</td>\n",
       "      <td>4.374417</td>\n",
       "      <td>4.564769</td>\n",
       "      <td>3.168868</td>\n",
       "      <td>4.152716</td>\n",
       "      <td>8.646371</td>\n",
       "      <td>3.723133</td>\n",
       "      <td>2.576806</td>\n",
       "      <td>0.090247</td>\n",
       "      <td>1.376432</td>\n",
       "      <td>3.060907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>55325.311233</td>\n",
       "      <td>1.391672</td>\n",
       "      <td>1.966334</td>\n",
       "      <td>6.275026</td>\n",
       "      <td>4.006050</td>\n",
       "      <td>3.243335</td>\n",
       "      <td>2.753787</td>\n",
       "      <td>2.307653</td>\n",
       "      <td>4.134828</td>\n",
       "      <td>14.309694</td>\n",
       "      <td>...</td>\n",
       "      <td>2.924355</td>\n",
       "      <td>2.887035</td>\n",
       "      <td>2.233516</td>\n",
       "      <td>1.974375</td>\n",
       "      <td>1.154001</td>\n",
       "      <td>2.095540</td>\n",
       "      <td>1.168486</td>\n",
       "      <td>0.286536</td>\n",
       "      <td>0.484492</td>\n",
       "      <td>1.086254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>47913.750000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>95826.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>143739.250000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>191652.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>523.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 361 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 LNR       AGER_TYP     AKT_DAT_KL       ALTER_HH  \\\n",
       "count  191652.000000  191652.000000  145056.000000  145056.000000   \n",
       "mean    95826.500000       0.344359       1.747525      11.352009   \n",
       "std     55325.311233       1.391672       1.966334       6.275026   \n",
       "min         1.000000      -1.000000       1.000000       0.000000   \n",
       "25%     47913.750000      -1.000000       1.000000       8.000000   \n",
       "50%     95826.500000       0.000000       1.000000      11.000000   \n",
       "75%    143739.250000       2.000000       1.000000      16.000000   \n",
       "max    191652.000000       3.000000       9.000000      21.000000   \n",
       "\n",
       "        ALTER_KIND1  ALTER_KIND2  ALTER_KIND3  ALTER_KIND4  \\\n",
       "count  11766.000000  5100.000000  1275.000000   236.000000   \n",
       "mean      12.337243    13.672353    14.647059    15.377119   \n",
       "std        4.006050     3.243335     2.753787     2.307653   \n",
       "min        2.000000     2.000000     5.000000     8.000000   \n",
       "25%        9.000000    11.000000    13.000000    14.000000   \n",
       "50%       13.000000    14.000000    15.000000    16.000000   \n",
       "75%       16.000000    16.000000    17.000000    17.000000   \n",
       "max       18.000000    18.000000    18.000000    18.000000   \n",
       "\n",
       "       ALTERSKATEGORIE_FEIN  ANZ_HAUSHALTE_AKTIV  ...       VK_DHT4A  \\\n",
       "count         139810.000000        141725.000000  ...  143781.000000   \n",
       "mean              10.331579             4.965863  ...       4.374417   \n",
       "std                4.134828            14.309694  ...       2.924355   \n",
       "min                0.000000             0.000000  ...       1.000000   \n",
       "25%                9.000000             1.000000  ...       2.000000   \n",
       "50%               10.000000             1.000000  ...       4.000000   \n",
       "75%               13.000000             4.000000  ...       7.000000   \n",
       "max               25.000000           523.000000  ...      11.000000   \n",
       "\n",
       "          VK_DISTANZ        VK_ZG11  W_KEIT_KIND_HH  WOHNDAUER_2008  \\\n",
       "count  143781.000000  143781.000000   137910.000000   145056.000000   \n",
       "mean        4.564769       3.168868        4.152716        8.646371   \n",
       "std         2.887035       2.233516        1.974375        1.154001   \n",
       "min         1.000000       1.000000        0.000000        1.000000   \n",
       "25%         2.000000       1.000000        2.000000        9.000000   \n",
       "50%         4.000000       3.000000        5.000000        9.000000   \n",
       "75%         7.000000       4.000000        6.000000        9.000000   \n",
       "max        13.000000      11.000000        6.000000        9.000000   \n",
       "\n",
       "            WOHNLAGE       ZABEOTYP  ONLINE_PURCHASE      ANREDE_KZ  \\\n",
       "count  141725.000000  191652.000000    191652.000000  191652.000000   \n",
       "mean        3.723133       2.576806         0.090247       1.376432   \n",
       "std         2.095540       1.168486         0.286536       0.484492   \n",
       "min         0.000000       1.000000         0.000000       1.000000   \n",
       "25%         2.000000       1.000000         0.000000       1.000000   \n",
       "50%         3.000000       3.000000         0.000000       1.000000   \n",
       "75%         5.000000       3.000000         0.000000       2.000000   \n",
       "max         8.000000       6.000000         1.000000       2.000000   \n",
       "\n",
       "       ALTERSKATEGORIE_GROB  \n",
       "count         191652.000000  \n",
       "mean               3.060907  \n",
       "std                1.086254  \n",
       "min                1.000000  \n",
       "25%                3.000000  \n",
       "50%                3.000000  \n",
       "75%                4.000000  \n",
       "max                9.000000  \n",
       "\n",
       "[8 rows x 361 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_customers.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>LNR</th>\n",
       "      <th>AGER_TYP</th>\n",
       "      <th>AKT_DAT_KL</th>\n",
       "      <th>ALTER_HH</th>\n",
       "      <th>ALTER_KIND1</th>\n",
       "      <th>ALTER_KIND2</th>\n",
       "      <th>ALTER_KIND3</th>\n",
       "      <th>ALTER_KIND4</th>\n",
       "      <th>ALTERSKATEGORIE_FEIN</th>\n",
       "      <th>ANZ_HAUSHALTE_AKTIV</th>\n",
       "      <th>...</th>\n",
       "      <th>VHN</th>\n",
       "      <th>VK_DHT4A</th>\n",
       "      <th>VK_DISTANZ</th>\n",
       "      <th>VK_ZG11</th>\n",
       "      <th>W_KEIT_KIND_HH</th>\n",
       "      <th>WOHNDAUER_2008</th>\n",
       "      <th>WOHNLAGE</th>\n",
       "      <th>ZABEOTYP</th>\n",
       "      <th>ANREDE_KZ</th>\n",
       "      <th>ALTERSKATEGORIE_GROB</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>910215</td>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>910220</td>\n",
       "      <td>-1</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 366 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      LNR  AGER_TYP  AKT_DAT_KL  ALTER_HH  ALTER_KIND1  ALTER_KIND2  \\\n",
       "0  910215        -1         NaN       NaN          NaN          NaN   \n",
       "1  910220        -1         9.0       0.0          NaN          NaN   \n",
       "\n",
       "   ALTER_KIND3  ALTER_KIND4  ALTERSKATEGORIE_FEIN  ANZ_HAUSHALTE_AKTIV  ...  \\\n",
       "0          NaN          NaN                   NaN                  NaN  ...   \n",
       "1          NaN          NaN                  21.0                 11.0  ...   \n",
       "\n",
       "   VHN  VK_DHT4A  VK_DISTANZ  VK_ZG11  W_KEIT_KIND_HH  WOHNDAUER_2008  \\\n",
       "0  NaN       NaN         NaN      NaN             NaN             NaN   \n",
       "1  4.0       8.0        11.0     10.0             3.0             9.0   \n",
       "\n",
       "   WOHNLAGE ZABEOTYP ANREDE_KZ ALTERSKATEGORIE_GROB  \n",
       "0       NaN        3         1                    2  \n",
       "1       4.0        5         2                    1  \n",
       "\n",
       "[2 rows x 366 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_azdias.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LNR</th>\n",
       "      <th>AGER_TYP</th>\n",
       "      <th>AKT_DAT_KL</th>\n",
       "      <th>ALTER_HH</th>\n",
       "      <th>ALTER_KIND1</th>\n",
       "      <th>ALTER_KIND2</th>\n",
       "      <th>ALTER_KIND3</th>\n",
       "      <th>ALTER_KIND4</th>\n",
       "      <th>ALTERSKATEGORIE_FEIN</th>\n",
       "      <th>ANZ_HAUSHALTE_AKTIV</th>\n",
       "      <th>...</th>\n",
       "      <th>VHN</th>\n",
       "      <th>VK_DHT4A</th>\n",
       "      <th>VK_DISTANZ</th>\n",
       "      <th>VK_ZG11</th>\n",
       "      <th>W_KEIT_KIND_HH</th>\n",
       "      <th>WOHNDAUER_2008</th>\n",
       "      <th>WOHNLAGE</th>\n",
       "      <th>ZABEOTYP</th>\n",
       "      <th>ANREDE_KZ</th>\n",
       "      <th>ALTERSKATEGORIE_GROB</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8.912210e+05</td>\n",
       "      <td>891221.000000</td>\n",
       "      <td>817722.000000</td>\n",
       "      <td>817722.000000</td>\n",
       "      <td>81058.000000</td>\n",
       "      <td>29499.000000</td>\n",
       "      <td>6170.000000</td>\n",
       "      <td>1205.000000</td>\n",
       "      <td>628274.000000</td>\n",
       "      <td>798073.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>770025.000000</td>\n",
       "      <td>815304.000000</td>\n",
       "      <td>815304.000000</td>\n",
       "      <td>815304.000000</td>\n",
       "      <td>783619.000000</td>\n",
       "      <td>817722.000000</td>\n",
       "      <td>798073.000000</td>\n",
       "      <td>891221.000000</td>\n",
       "      <td>891221.000000</td>\n",
       "      <td>891221.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.372630e+05</td>\n",
       "      <td>-0.358435</td>\n",
       "      <td>4.421928</td>\n",
       "      <td>10.864126</td>\n",
       "      <td>11.745392</td>\n",
       "      <td>13.402658</td>\n",
       "      <td>14.476013</td>\n",
       "      <td>15.089627</td>\n",
       "      <td>13.700717</td>\n",
       "      <td>8.287263</td>\n",
       "      <td>...</td>\n",
       "      <td>2.417322</td>\n",
       "      <td>6.001214</td>\n",
       "      <td>7.532130</td>\n",
       "      <td>5.945972</td>\n",
       "      <td>3.933406</td>\n",
       "      <td>7.908791</td>\n",
       "      <td>4.052836</td>\n",
       "      <td>3.362438</td>\n",
       "      <td>1.522098</td>\n",
       "      <td>2.777398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.572735e+05</td>\n",
       "      <td>1.198724</td>\n",
       "      <td>3.638805</td>\n",
       "      <td>7.639683</td>\n",
       "      <td>4.097660</td>\n",
       "      <td>3.243300</td>\n",
       "      <td>2.712427</td>\n",
       "      <td>2.452932</td>\n",
       "      <td>5.079849</td>\n",
       "      <td>15.628087</td>\n",
       "      <td>...</td>\n",
       "      <td>1.166572</td>\n",
       "      <td>2.856091</td>\n",
       "      <td>3.247789</td>\n",
       "      <td>2.771464</td>\n",
       "      <td>1.964701</td>\n",
       "      <td>1.923137</td>\n",
       "      <td>1.949539</td>\n",
       "      <td>1.352704</td>\n",
       "      <td>0.499512</td>\n",
       "      <td>1.068775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.916530e+05</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.144580e+05</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.372630e+05</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.600680e+05</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.082873e+06</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>595.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 360 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                LNR       AGER_TYP     AKT_DAT_KL       ALTER_HH  \\\n",
       "count  8.912210e+05  891221.000000  817722.000000  817722.000000   \n",
       "mean   6.372630e+05      -0.358435       4.421928      10.864126   \n",
       "std    2.572735e+05       1.198724       3.638805       7.639683   \n",
       "min    1.916530e+05      -1.000000       1.000000       0.000000   \n",
       "25%    4.144580e+05      -1.000000       1.000000       0.000000   \n",
       "50%    6.372630e+05      -1.000000       3.000000      13.000000   \n",
       "75%    8.600680e+05      -1.000000       9.000000      17.000000   \n",
       "max    1.082873e+06       3.000000       9.000000      21.000000   \n",
       "\n",
       "        ALTER_KIND1   ALTER_KIND2  ALTER_KIND3  ALTER_KIND4  \\\n",
       "count  81058.000000  29499.000000  6170.000000  1205.000000   \n",
       "mean      11.745392     13.402658    14.476013    15.089627   \n",
       "std        4.097660      3.243300     2.712427     2.452932   \n",
       "min        2.000000      2.000000     4.000000     7.000000   \n",
       "25%        8.000000     11.000000    13.000000    14.000000   \n",
       "50%       12.000000     14.000000    15.000000    15.000000   \n",
       "75%       15.000000     16.000000    17.000000    17.000000   \n",
       "max       18.000000     18.000000    18.000000    18.000000   \n",
       "\n",
       "       ALTERSKATEGORIE_FEIN  ANZ_HAUSHALTE_AKTIV  ...            VHN  \\\n",
       "count         628274.000000        798073.000000  ...  770025.000000   \n",
       "mean              13.700717             8.287263  ...       2.417322   \n",
       "std                5.079849            15.628087  ...       1.166572   \n",
       "min                0.000000             0.000000  ...       0.000000   \n",
       "25%               11.000000             1.000000  ...       2.000000   \n",
       "50%               14.000000             4.000000  ...       2.000000   \n",
       "75%               17.000000             9.000000  ...       3.000000   \n",
       "max               25.000000           595.000000  ...       4.000000   \n",
       "\n",
       "            VK_DHT4A     VK_DISTANZ        VK_ZG11  W_KEIT_KIND_HH  \\\n",
       "count  815304.000000  815304.000000  815304.000000   783619.000000   \n",
       "mean        6.001214       7.532130       5.945972        3.933406   \n",
       "std         2.856091       3.247789       2.771464        1.964701   \n",
       "min         1.000000       1.000000       1.000000        0.000000   \n",
       "25%         3.000000       5.000000       4.000000        2.000000   \n",
       "50%         6.000000       8.000000       6.000000        4.000000   \n",
       "75%         9.000000      10.000000       8.000000        6.000000   \n",
       "max        11.000000      13.000000      11.000000        6.000000   \n",
       "\n",
       "       WOHNDAUER_2008       WOHNLAGE       ZABEOTYP      ANREDE_KZ  \\\n",
       "count   817722.000000  798073.000000  891221.000000  891221.000000   \n",
       "mean         7.908791       4.052836       3.362438       1.522098   \n",
       "std          1.923137       1.949539       1.352704       0.499512   \n",
       "min          1.000000       0.000000       1.000000       1.000000   \n",
       "25%          8.000000       3.000000       3.000000       1.000000   \n",
       "50%          9.000000       3.000000       3.000000       2.000000   \n",
       "75%          9.000000       5.000000       4.000000       2.000000   \n",
       "max          9.000000       8.000000       6.000000       2.000000   \n",
       "\n",
       "       ALTERSKATEGORIE_GROB  \n",
       "count         891221.000000  \n",
       "mean               2.777398  \n",
       "std                1.068775  \n",
       "min                1.000000  \n",
       "25%                2.000000  \n",
       "50%                3.000000  \n",
       "75%                4.000000  \n",
       "max                9.000000  \n",
       "\n",
       "[8 rows x 360 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_azdias.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Renaming the column names to understandble form."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop the extra column of customers dataset.\n",
    "df_customers.drop(columns=['CUSTOMER_GROUP', 'ONLINE_PURCHASE', 'PRODUCT_GROUP'], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perform Data cleaning and preprocessing steps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Customer columns with missing values\n",
    "plt.barh(np.arange(len(df_customers.columns)), df_customers.isnull().mean().sort_values(ascending=True))\n",
    "plt.xlabel('Percent of missing value')\n",
    "plt.ylabel('Features')\n",
    "plt.title('Missing values by column in CUSTOMER dataset')\n",
    "#plt.savefig('missing_customer', quality = 100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#azdias columns with missing values\n",
    "plt.barh(np.arange(len(df_azdias.columns)), df_azdias.isnull().mean().sort_values(ascending=True))\n",
    "plt.xlabel('Percent of missing value')\n",
    "plt.ylabel('Features')\n",
    "plt.title('Missing values by column in AZDIAS dataset')\n",
    "#plt.savefig('missing_azdias', quality = 100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see we have some types which have very high percentage of Null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ALTER_KIND1', 'ALTER_KIND2', 'ALTER_KIND3', 'ALTER_KIND4', 'EXTSEL992',\n",
       "       'KK_KUNDENTYP'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#columns with more than 30% missing values\n",
    "df_customers.columns[df_customers.isna().mean() > 0.3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ALTER_KIND1', 'ALTER_KIND2', 'ALTER_KIND3', 'ALTER_KIND4', 'EXTSEL992',\n",
       "       'KK_KUNDENTYP'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#columns with more than 30% missing values\n",
    "df_azdias.columns[df_azdias.isna().mean() > 0.3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's preprocess the data. The function in our helper class handles missing values, converts data formats."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_customers = h.data_pre_process(df_customers)\n",
    "df_azdias = h.data_pre_process(df_azdias)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['AGER_TYP', 'AKT_DAT_KL', 'ALTER_HH', 'ALTER_KIND1', 'ALTER_KIND2',\n",
       "       'ALTER_KIND3', 'ALTER_KIND4', 'ALTERSKATEGORIE_FEIN',\n",
       "       'ANZ_HAUSHALTE_AKTIV', 'ANZ_HH_TITEL',\n",
       "       ...\n",
       "       'VK_DHT4A', 'VK_DISTANZ', 'VK_ZG11', 'W_KEIT_KIND_HH', 'WOHNDAUER_2008',\n",
       "       'WOHNLAGE', 'ZABEOTYP', 'ANREDE_KZ', 'ALTERSKATEGORIE_GROB',\n",
       "       'YEAR_ADDED'],\n",
       "      dtype='object', length=365)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_customers.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "#renaming major columns for better understanbility\n",
    "df_azdias = df_azdias.rename(columns=h.column_transform_dict)\n",
    "df_customers = df_customers.rename(columns=h.column_transform_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaling = StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_customers_scaled = scaling.fit_transform(df_customers)\n",
    "df_azdias_scaled = scaling.fit_transform(df_azdias)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 1: Customer Segmentation Report\n",
    "\n",
    "In this analysis I have used PCA and k-means to describe the relationship between the demographics of the company's existing customers and the general population of Germany. <br> \n",
    "The aim is for me to be able to describe parts of the general population that are more likely to be part of the mail-order company's main customer base, and which parts of the general population are less so."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We will use PCA and K-means for our Unsupervised analysis of data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### PCA  <br>\n",
    "PCA is used to reduce the dimension of the data with minimum loss of information. As we have around 360 columns in our dataset, it will be easier to perform unsupervised analysis on reduced dimensions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "pca = PCA(random_state=123)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "customer_pca = pca.fit_transform(df_customers_scaled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "116"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of components required to maintain %80 variance:\n",
    "n_components = min(np.where(np.cumsum(pca.explained_variance_ratio_)>0.8)[0]+1)\n",
    "n_components"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa393a76b20>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax1 = fig.add_axes([0,0,1,1],True)\n",
    "ax2 = ax1.twinx()\n",
    "ax1.plot(pca.explained_variance_ratio_, label='Variance', color = 'orange')\n",
    "ax2.plot(np.cumsum(pca.explained_variance_ratio_), label='Cumulative Variance',color = 'Green');\n",
    "ax1.set_xlabel(\"Principal Component\")\n",
    "ax1.set_ylabel(\"Variance Explained (%)\")\n",
    "ax1.set_title('n_components needed for >%80 explained variance: {}'.format(n_components));\n",
    "ax1.axvline(n_components, linestyle='dashed', color='black')\n",
    "ax2.axhline(np.cumsum(pca.explained_variance_ratio_)[n_components], linestyle='dashed', color='black')\n",
    "fig.legend(loc=(0.6,0.2))\n",
    "#plt.savefig('PCA', quality = 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top 5 important features for component 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(sorted(zip(df_customers.columns, pca.components_[0]), key=lambda x: x[1])[-5:],\n",
    "            columns=['feature','coef'])\n",
    "for column in (df['feature'].values):\n",
    "    h.plot_comparison_charts(column,df_customers,df_azdias)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top 5 important features for component 1 with least coef"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1gAAAEYCAYAAABBWFftAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO3de5xdVX3//9dbLoIiN0kpEihYU230WxEjYm0tgkJAK7ZFC60SkUr9ClZbrULtVxClRdtqxQuWSiDgBSlqSRXEiFDrr+USFLlqiYiSGCASBPGCgp/fH3sNHIYzk0lyzsxk8no+Hucx+3z22nutfS6zzmfvddZJVSFJkiRJWn+PmuoGSJIkSdJMYYIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoI1AyT5SJL/N6B97Zrk3iSbtPuXJvmzQey77e/CJAsGtb+1qPddSX6Q5LbJrntdJakkT5rqdsw07fX9xKluhzTT2BdNqF77IgH2RTOdCdY0l+SWJD9N8qMkP0zy30lem+TB566qXltV75zgvl4wXpmq+l5VbVVVDwyg7Sck+dio/R9YVYvWd99r2Y5dgTcBc6vqV/us3yfJ8sls02RZmw8l6fx1kpvaa+57Sf4+yaPb+i8kObHPdgcnuS3JpknOTPLz1nGM3L7Ryu3WOuqR+C1Jju2zv31aubeOio9sv2mfbR7xWhtLe33fPJGy/STZqrX/wlHxPx113CO3SvL2VubSJD9r7+d7klyV5NiRx3isY2nPzc1JbujTnqcm+WKS1e1/xFVJDlrX45P6sS9af/ZF9kW91qcvSrJ5q+umJD9ux7AwyW5t/SPeY0leleSrPfePTPLN9p6+PckFSR6X7uTDyGPzi1GP40fattsmObU93j9Jcm2SI0bVd0vbdodR8a+3x2+krev9XE1HJlgbht+vqscBvwacDLwVOH3QlfT7ZzFD7ArcWVV3rOsOZvBj0+sU4CjgcOBxwIHAfsC5bf0i4BVJMmq7VwIfr6r72/33tI5j5Pb0UeW3raqtgEOA/5fkhaPWLwBWt3ZMR38E3Ae8MMmDH5Kq6uOjjnsr4I3A7cC/9mx/THs/70T3YetQ4II+j2uv5wG/AjwxybNGrfsPYAnwq63MXwD3rNcRSv3ZF60f+6KJsS9as/OAlwB/AmwDPB24iu5xWqMkvwf8HXBYe0//JvApePDkw0gf9nEe/ji+NsnmwJfo/g88p9X/18DJSf5qVFXfAQ7rqff/AI/p06T1fa6mn6ryNo1vwC3AC0bF9gJ+CTyt3T8TeFdb3gH4HPBDun8M/0WXSJ/dtvkpcC/wFmA3oIAjge8BX+mJbdr2dynw98AVdB/azge2b+v2AZb3ay8wH/g58ItW3zd69vdnbflRwN8C3wXuAM4CtmnrRtqxoLXtB8Dbxnmctmnbr2r7+9u2/xe0Y/5la8eZo7Z77Kj19wJPAE6g+wf2sXbcf9Ye9/9pj+1K4IPA5j37KuC1wE2tzIeAtHVPAv4TuLsdy6cm8NwX8KS2/CLg660ttwIn9JTborXzzlbvlcCOwEnAA8DP2nF9cJy65rSye42K70KXTOwLbNna/7ye9du1/T999GuxTx0jz+mmPbErgL8e9Xz8iC7p+Dkwb7zte9adAHxsgu+p3sf1zPY8fb7Veznw62vY/svtsf0a8OZxyj2jPe779MQupb3+e2K7Aj8BXjzWsQAL6Tq6z/Q+j3Tv96LrfKb8/5W3mXvDvsi+qOyLxtq+Z90JDLkv6nkt7bKW79dXAV9ty28G/n0CbXzE40j3Pr0DeOyo+B+353frnjb8LXBlT5l/BN7Wjn23QTxX0/XmFawNUFVdASwHfrfP6je1dbPo/rH9TbdJvZKuc/j96s4OvKdnm9+jO3txwBhVHg68mu6M+/10Z5fW1MYv0J0d+VT1PxsB3Zv9VcDzgScCW9F1FL1+B3gy3VmZtyf5zTGq/ABdx/bEdjyHA0dU1Zfozn59v7XjVaPa+eNR67eqqu+31QfTdWzb0n24fQD4S7oPDs9pbXrdqHa8GHgW8FvAy3noMX0n8EW6TmB2a+/a+HE7pm3pOrj/m+Slbd2Cduy7AI+n61h/WlVvo/tQc0w7rmPG2f9+dB9QrugNVtWtwGXAC6vqp3RnEHvP5r0c+GZVfWMtj4ckewNPA5b1hP+Q7h/0vwEXtWMbtkOBd9A9N8voPgz0leTX6D7Mfbzd+p7ZTLIt3WvnnVV16XiVV9X3gKX0fz+T5DF0Z+1G6jy0nUGE7oPMMuBjSV6aZMfx6pIGyb6oL/si+6J1NdG+6AXAFe0xWVeXAwckeUeS56ZnmPoEvBC4sL1me32aLsl+Tk/sMmDrJL+Z7vuUh9Il4etkjOdqWjLB2nB9H9i+T/wXdJ3Pr1XVL6rqv6ql/OM4oap+3P5p9XN2VV3X3kz/D3h5e6Osrz8F3ltVN1fVvcBxdB8ee4dAvKOqftr+aX6D7jL4w/S8aY+rqh9V1S3AP9ENF1gf/1NV/15Vv2xtuKqqLquq+1sd/0LXgfY6uap+2D40XwLs0eK/oLuc/oSq+llVfZW1UFWXVtW1rS3XAJ/sqfsXdJ3Zk6rqgdbOtR0itgPdmdB+Vrb10A3NOCTJFu3+4S3W683pvqMxchu9/gdJfkp3BvbDwL/3rFtA90HoAeATdK+HzdbyWNbWZ6vqiuqGlXych56zfl4JXFNVNwDnAE9N8ozeAm3YylnAdcB7HrmLvsZ6P0PX0d9H96Ho88BmdB9saO/t59OdKfwnYGWSrySZM8F6pfVlX9TYF9kXraeJ9kWPZ+zHaEKq6r/o+pY96fqVO5O8d4Lvp77PUWv3D3joORpxNt3z80LgRmBFn32uz3M1LZlgbbh2pht2Mdo/0GX2X0z3pfiJfBlwTWdBetd/l+4D3ug30Lp4Qttf7743pTvbOaJ3pqWf0J1ZHG2H1qbR+9p5Pdv3sMclyW8k+Vz7Uuc9dGdFRz8OY7X3LUCAK5Jcn+TVa9OQJM9OckmSVUnupjszOFL32XRn2M5J8v0k71mHjuAHdB+G+tmprad1xj8AXprk1+mGqnxiVPl/rKpte26jz/ztQPe4vInuatBm7Rh3oUsWPt7KnU93NuxFa3ksa2sir7ERh9PaV1Ur6IbajD6+twJPBRZM4APliLHez7T9n9s+TP2M7izhg3VW1fKqOqaqfp3ug9OP6RI8aTLYFz3Evsi+aH1MtC+6k7EfoxH3046nx2Z0STAAVXVhVf0+3QmSg+mu4k5kIpK+z1E7IbFDW9/rbLrvir2KsfumdXqupjMTrA1Q+5L7zsAjzjy1s2Zvqqon0n0B8q+SjHzpcawPe2v6ELhLz/KudG/QH9B9kHvwy4rtzMestdjv9+k+EPbu+366SQHWxg946Kxc7776nSXpZ6KPy6nAN4E5VbU13ZCX8SYmeGhHVbdV1Wuq6gnAnwMfztpNe/sJYDHdmOttgI+M1N3ODr+jquYCv003NGRk6MREP+B/GdglyV69wdbR7A1c3BM+q+3/FcBFVbW2zxft7OZ76cbMjwxteSXd/6T/SDeF8c10ndpkDM1YoyS/Tff9gOPaB5vbgGcDfzJypjvJPnTjyw+pqh9OcL+7AM+kG0Izet1suu8cvKKnzkOAgzJqZiZ4cBjNh+iGUEhDZV/0CPZF9kWT4UvAXq1/GMv36L6/1Gt3Hp78A9CuRl5M99hPpO/4EnBgkseOio9MAHXZqP1/l26yi4Povke8TsZ4rqYtE6wNSJKtk7yYbmjSx6rq2j5lXpzkSW2Y0t10Y7V/2VbfTjcufG29Isnc9l2QE4Hz2mXz/wW2SPKidpbqb4Hecby3A7ulZxrfUT4J/GWS3ZNsxUPj5O8fo3xfrS3nAielm2L014C/YuLjfG8HHp9kmzWUexzdF3vvTfIU4P9OtI1JXtbzz/Auus7ml+Ns0q/u1VX1s9bx/EnPvp+f5P+0DxX30HXwa/WcV9X/0nWUH0+yd5JNkjyV7mrJl6r7/sCIs+jGgL+GRw7JWFsnA29pwzwW0I0/36Pn9kd0ycTje7Z5dJItem4jr69HjYqvzZjyiVhAN1vf3J72PY3uC9cHJtmJ7r35xqr6+pp2luQx6WZyOp/uS7sX9Cn2Srr32ZN76vwNuu+2HJZku3Rj6J+U5FEt6Xo1ozo4aZDsi/qzL7IvavGh9kXtMVgCfDbJM9NNS/+4dD+bMHJF8lPAG5M8JZ15dH3DOfDglPaHtj4k7bn8PSbWd5xN1wf9W7pp1DdLcgDddyJPqKq7+2xzJLBvPfJ7W+ui97matkywNgz/keRHdMME3ga8FzhijLJz6M4u3Esbq1pVl7R1fw/8bbrxrW9ei/rPppvl5Ta6szh/AdDeRK8DPkp3hu7HdG+6Ef/W/t6Z5Gt99ruw7fsrdGc3fga8fi3a1ev1rf6b6c6mfqLtf42q6pt0HezN7bF5whhF30zXmfyIbtrtT61F+54FXJ7kXrqzf2+otfv9i9cBJ7bXwdt5aLpa6KbnPo+uQ7uRbtja2W3d++nGqd+VZE1fCD+G7rn8GN3r5wt0M239UW+hNub/v+lmWVrcZz9vycN/z2L0cIFen6fr5P+a7qzvh9oZ1pHbYrphRof1bHMv3QxKI7d9W/ywUfFvr+F4J6z9I3858IFR7fsO3WO9gK6T3xF4fx75W1gf6dndB9vzeDvwz3QfHOZXVb8POQvo3sO9dd5G9wFkAd3sVrvRvefvofve1310QzGkQbMvWjP7IvuiofVFPQ6hOyn3KboTGNcB8+jec9C9Ls6g+xmPu+mS0bdVN+kLdMf6GrqZJu+he6z/oapGhkWOqaruo0tsb6WbLOMeuv8Fb6uqfxhjm29X1dJxdrsuz9Vr1tTWqTQybackSZIkaT15BUuSJEmSBmRj+EVwaVpK8rvAhf3WVfeL5Rt0fZKk6c++SBo8hwhKkiRJ0oBsdFewdthhh9ptt92muhmSpFGuuuqqH1TVrDWX3HjYZ0nS9DVWv7XRJVi77bYbS5eON5GJJGkqJHnEb7Rs7OyzJGn6GqvfcpILSZIkSRoQEyxJkiRJGhATLEmSJEkaEBMsSZIkSRoQEyxJkiRJGhATLEmSJEkaEBMsSZIkSRqQoSZYSbZNcl6Sbya5MclzkmyfZEmSm9rf7VrZJDklybIk1yTZs2c/C1r5m5Is6Ik/M8m1bZtTkmSYxyNJkiRJ4xn2Faz3A1+oqqcATwduBI4FLq6qOcDF7T7AgcCcdjsKOBUgyfbA8cCzgb2A40eSslbmNT3bzR/y8UiSNmBJtkhyRZJvJLk+yTta/Mwk30lydbvt0eIDO/k31glGSdLMsumwdpxkG+B5wKsAqurnwM+THAzs04otAi4F3gocDJxVVQVc1q5+7dTKLqmq1W2/S4D5SS4Ftq6qy1r8LOClwIXDOiZJmqmWH/vfk17n7JN/e9LrBO4D9q2qe5NsBnw1yUi/8ddVdd6o8r0n/55Nd2Lv2T0n/+YBBVyVZHFV3cVDJ/8uBy6gO/l3IQ+dYDw5ybHt/luHeKySNGNN535rmFewdgdWAWck+XqSjyZ5LLBjVa1sZW4DdmzLOwO39my/vMXGiy/vE5ckqa/q3NvubtZuNc4mD578ayf0Rk7+HUA7+deSqpGTfzvRTv61E4YjJ/9G9rWoLS/qiUuSZpBhJlibAnsCp1bVM4Af89BwQKDr6Bi/YxuIJEclWZpk6apVq4ZdnSRpGkuySZKrgTvokqTL26qT2jDA9yV5dIsN8uTfWCcYR7fPPkuSNmDDTLCWA8t7Oq7z6BKu29sZPtrfO9r6FcAuPdvPbrHx4rP7xB+hqk6rqnlVNW/WrFnrdVCSpA1bVT1QVXvQ9Rt7JXkacBzwFOBZwPYMeejeeCcY7bMkacM2tASrqm4Dbk3y5BbaD7gBWAyMfBl4AXB+W14MHN6+ULw3cHc703cRsH+S7doXgvcHLmrr7kmyd/sC8eE9+5IkaVxV9UPgEmB+Va1swwDvA86gm1QJBnvyb6wTjJKkGWTYswi+Hvh4kmuAPYC/A04GXpjkJuAF7T50XwS+GVgG/CvwOoA2ucU7gSvb7cSRCS9amY+2bb6NE1xIksaRZFaSbdvylsALgW/2JD6h+27UdW2TQZ78G+sEoyRpBhnaLIIAVXU13QxLo+3Xp2wBR4+xn4XAwj7xpcDT1rOZkqSNx07AoiSb0J1kPLeqPpfky0lmAQGuBl7byl8AHER3Iu8nwBHQnfxLMnLyDx558u9MYEu6E38jJ/9OBs5NciTwXeDlQztKSdKUGWqCJUnSdFJV1wDP6BPfd4zyAzv5V1V30ucEoyRpZhn2EEFJkiRJ2miYYEmSJEnSgJhgSZIkSdKAmGBJkiRJ0oCYYEmSJEnSgJhgSZIkSdKAmGBJkiRJ0oCYYEmSJEnSgJhgSZIkSdKAmGBJkiRJ0oCYYEmSJEnSgJhgSZIkSdKAmGBJkiRJ0oCYYEmSJEnSgJhgSZIkSdKAmGBJkiRJ0oCYYEmSJEnSgJhgSZIkSdKAmGBJkiRJ0oCYYEmSJEnSgJhgSZIkSdKAmGBJkjYqSbZIckWSbyS5Psk7Wnz3JJcnWZbkU0k2b/FHt/vL2vrdevZ1XIt/K8kBPfH5LbYsybE98b51SJJmDhMsSdLG5j5g36p6OrAHMD/J3sC7gfdV1ZOAu4AjW/kjgbta/H2tHEnmAocCTwXmAx9OskmSTYAPAQcCc4HDWlnGqUOSNEOYYEmSNirVubfd3azdCtgXOK/FFwEvbcsHt/u09fslSYufU1X3VdV3gGXAXu22rKpurqqfA+cAB7dtxqpDkjRDmGBJkjY67UrT1cAdwBLg28APq+r+VmQ5sHNb3hm4FaCtvxt4fG981DZjxR8/Th29bTsqydIkS1etWrW+hypJmmRDTbCS3JLk2iRXJ1naYtsnWZLkpvZ3uxZPklPauPRrkuzZs58FrfxNSRb0xJ/Z9r+sbZthHo8kaWaoqgeqag9gNt0Vp6dMcZMeVFWnVdW8qpo3a9asqW6OJGktTcYVrOdX1R5VNa/dPxa4uKrmABe3+9CNVZ/TbkcBp0KXkAHHA8+m6wSPH0nKWpnX9Gw3f/iHI0maKarqh8AlwHOAbZNs2lbNBla05RXALgBt/TbAnb3xUduMFb9znDokSTPEVAwR7B3LPnqM+1ltbPxldJ3QTsABwJKqWl1Vd9EN5Zjf1m1dVZdVVQFn4Vh2SdIaJJmVZNu2vCXwQuBGukTrkFZsAXB+W17c7tPWf7n1O4uBQ9ssg7vTnei7ArgSmNNmDNycbiKMxW2bseqQJM0Qm665yHop4ItJCviXqjoN2LGqVrb1twE7tuW1Hcu+c1seHX+EJEfRXRVj1113XZ/jkSRt+HYCFrXZ/h4FnFtVn0tyA3BOkncBXwdOb+VPB85OsgxYTZcwUVXXJzkXuAG4Hzi6qh4ASHIMcBGwCbCwqq5v+3rrGHVIkmaIYSdYv1NVK5L8CrAkyTd7V1ZVteRrqFpidxrAvHnzhl6fJGn6qqprgGf0id9MNxR9dPxnwMvG2NdJwEl94hcAF0y0DknSzDHUIYJVtaL9vQP4LF2ncnsb3kf7e0crvrZj2Ve05dFxSZIkSZoSQ0uwkjw2yeNGloH9get4+Fj20WPcD2+zCe4N3N2GEl4E7J9kuza5xf7ARW3dPUn2brMHHo5j2SVJkiRNoWEOEdwR+GybOX1T4BNV9YUkVwLnJjkS+C7w8lb+AuAguh9q/AlwBEBVrU7yTrovDQOcWFWr2/LrgDOBLYEL202SJEmSpsTQEqw2zvzpfeJ3Avv1iRdw9Bj7Wggs7BNfCjxtvRsrSZIkSQMwFdO0S5IkSdKMZIIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSdpoJNklySVJbkhyfZI3tPgJSVYkubrdDurZ5rgky5J8K8kBPfH5LbYsybE98d2TXN7in0qyeYs/ut1f1tbvNnlHLkmaLCZYkqSNyf3Am6pqLrA3cHSSuW3d+6pqj3a7AKCtOxR4KjAf+HCSTZJsAnwIOBCYCxzWs593t309CbgLOLLFjwTuavH3tXKSpBnGBEuStNGoqpVV9bW2/CPgRmDncTY5GDinqu6rqu8Ay4C92m1ZVd1cVT8HzgEOThJgX+C8tv0i4KU9+1rUls8D9mvlJUkziAmWJGmj1IboPQO4vIWOSXJNkoVJtmuxnYFbezZb3mJjxR8P/LCq7h8Vf9i+2vq7W/nR7ToqydIkS1etWrVexyhJmnwmWJKkjU6SrYBPA2+sqnuAU4FfB/YAVgL/NFVtq6rTqmpeVc2bNWvWVDVDkrSOTLAkSRuVJJvRJVcfr6rPAFTV7VX1QFX9EvhXuiGAACuAXXo2n91iY8XvBLZNsumo+MP21dZv08pLkmYQEyxJ0kajfefpdODGqnpvT3ynnmJ/AFzXlhcDh7YZAHcH5gBXAFcCc9qMgZvTTYSxuKoKuAQ4pG2/ADi/Z18L2vIhwJdbeUnSDLLpmotIkjRjPBd4JXBtkqtb7G/oZgHcAyjgFuDPAarq+iTnAjfQzUB4dFU9AJDkGOAiYBNgYVVd3/b3VuCcJO8Cvk6X0NH+np1kGbCaLimTJM0wJliSpI1GVX0V6Ddz3wXjbHMScFKf+AX9tquqm3loiGFv/GfAy9amvZKkDY9DBCVJkiRpQIaeYLUfZPx6ks+1+2v9C/dJjmvxbyU5oCc+v8WWJTl22MciSZIkSeOZjCtYb6D7IccRa/UL90nm0o1TfyowH/hwS9o2AT4EHAjMpRs/P3cSjkeSJEmS+hpqgpVkNvAi4KPt/rr8wv3BwDlVdV9VfQdYRje2fS9gWVXdXFU/B85pZSVJkiRpSgz7CtY/A28Bftnur8sv3D8YH7XNWPFHSHJUkqVJlq5atWp9j0mSJEmS+hpagpXkxcAdVXXVsOqYqKo6rarmVdW8WbNmTXVzJEmSJM1Qw5ym/bnAS5IcBGwBbA28n/YL9+0qVb9fuF8+6hfuR+IjercZKy5JkiRJk25oV7Cq6riqml1Vu9FNUvHlqvpT1v4X7hcDh7ZZBncH5gBXAFcCc9qshJu3OhYP63gkSZIkaU2m4oeG1+oX7qvq+iTnAjcA9wNHV9UDAEmOAS4CNgEWVtX1k3okkiRJktRjUhKsqroUuLQtr/Uv3FfVScBJfeIXABcMsKmSJEmStM4m43ewJEmSJGmjYIIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSZIkSQNigiVJkiRJA2KCJUmSJEkDYoIlSZIkSQMyoQQrycUTiUmSNFnWpW9KskuSS5LckOT6JG9o8e2TLElyU/u7XYsnySlJliW5JsmePfta0MrflGRBT/yZSa5t25ySJOPVIUmaWcZNsJJskWR7YIck27XOYfskuwE7T0YDJUnqtZ590/3Am6pqLrA3cHSSucCxwMVVNQe4uN0HOBCY025HAae2NmwPHA88G9gLOL4nYToVeE3PdvNbfKw6JEkzyKZrWP/nwBuBJwBXAWnxe4APDrFdkiSNZZ37pqpaCaxsyz9KciNdUnYwsE8rtgi4FHhri59VVQVclmTbJDu1skuqajVAkiXA/CSXAltX1WUtfhbwUuDCceqQJM0g4yZYVfV+4P1JXl9VH5ikNkmSNKZB9U3titczgMuBHVvyBXAbsGNb3hm4tWez5S02Xnx5nzjj1DG6XUfRXS1j1113XcujkiRNtTVdwQKgqj6Q5LeB3Xq3qaqzhtQuSZLGtT59U5KtgE8Db6yqe9rXpEa2ryQ1+BY/ZLw6quo04DSAefPmDbUdkqTBm1CCleRs4NeBq4EHWrgAEyxJ0pRY174pyWZ0ydXHq+ozLXx7kp2qamUbAnhHi68AdunZfHaLreCh4X4j8UtbfHaf8uPVIUmaQSaUYAHzgLltDLokSdPBWvdNbUa/04Ebq+q9PasWAwuAk9vf83vixyQ5h25Ci7tbgnQR8Hc9E1vsDxxXVauT3JNkb7qhh4cDH1hDHZKkGWSiCdZ1wK/SvhgsSdI0sC5903OBVwLXJrm6xf6GLuk5N8mRwHeBl7d1FwAHAcuAnwBHALRE6p3Ala3ciSMTXgCvA84EtqSb3OLCFh+rDknSDDLRBGsH4IYkVwD3jQSr6iVDaZUkSWu21n1TVX2Vh2YdHG2/PuULOHqMfS0EFvaJLwWe1id+Z786JEkzy0QTrBOG2QhJktbBCVPdAEmSRpvoLIL/OeyGSJK0NuybJEnT0URnEfwR3cxMAJsDmwE/rqqth9UwSZLGY98kSZqOJnoF63Ejy20GpoOBvYfVKEmS1sS+SZI0HT1qbTeozr8DBwyhPZIkrTX7JknSdDHRIYJ/2HP3UXS/PfKzNWyzBfAV4NGtnvOq6vgkuwPnAI8HrgJeWVU/T/Jouh+HfCZwJ/DHVXVL29dxwJF0PyT5F1V1UYvPB94PbAJ8tKpOnsjxSJI2fOvSN0mSNGwTnUXw93uW7wduoRuKMZ77gH2r6t4kmwFfTXIh8FfA+6rqnCQfoUucTm1/76qqJyU5FHg38MdJ5gKHAk8FngB8KclvtDo+BLwQWA5cmWRxVd0wwWOSJG3Y1qVvkiRpqCb6Hawj1nbH7bdD7m13N2u3AvYF/qTFF9FNs3sqXad4QoufB3ywZ0z9OVV1H/CdJMuAvVq5ZVV1M0CSc1pZEyxJ2gisS98kSdKwTeg7WElmJ/lskjva7dNJZk9gu02SXA3cASwBvg38sKrub0WWAzu35Z2BWwHa+rvphhE+GB+1zVjxfu04KsnSJEtXrVo1kUOWJE1z69o3SZI0TBOd5OIMYDHdEL0nAP/RYuOqqgeqag9gNt1Vp6esYzvXS1WdVlXzqmrerFmzpqIJkqTBW6e+SZKkYZpogjWrqs6oqvvb7UxgwplKVf0QuAR4DrBtkkUHb2IAABWKSURBVJGhibOBFW15BbALQFu/Dd1kFw/GR20zVlyStHFYr75JkqRhmGiCdWeSV7Qhf5skeQVd8jOmJLOSbNuWt6SbjOJGukTrkFZsAXB+W17c7tPWf7l9j2sxcGiSR7cZCOcAVwBXAnOS7J5kc7qJMBZP8HgkSRu+te6bJEkatonOIvhq4APA++gmqvhv4FVr2GYnYFGSTegSuXOr6nNJbgDOSfIu4OvA6a386cDZbRKL1XQJE1V1fZJz6SavuB84uqoeAEhyDHAR3TTtC6vq+gkejyRpw7cufZMkSUM10QTrRGBBVd0FkGR74B/pOre+quoa4Bl94jfz0CyAvfGfAS8bY18nASf1iV8AXDCxQ5AkzTBr3TdJkjRsEx0i+FsjHRhAVa2mT/IkSdIksm+SJE07E02wHpVku5E77SzhRK9+SZI0DPZNkqRpZ6Id0T8B/5Pk39r9l9FnyJ4kSZPIvkmSNO1MKMGqqrOSLAX2baE/rKobhtcsSZLGZ98kSZqOJjyUonVadlySpGnDvkmSNN1M9DtYkiRJkqQ1MMGSJG1UkixMckeS63piJyRZkeTqdjuoZ91xSZYl+VaSA3ri81tsWZJje+K7J7m8xT+VZPMWf3S7v6yt321yjliSNJlMsCRJG5szgfl94u+rqj3a7QKAJHPpfvj+qW2bDyfZJMkmwIeAA4G5wGGtLMC7276eBNwFHNniRwJ3tfj7WjlJ0gxjgiVJ2qhU1VeA1RMsfjBwTlXdV1XfAZYBe7Xbsqq6uap+DpwDHJwkdJNunNe2XwS8tGdfi9ryecB+rbwkaQYxwZIkqXNMkmvaEMKR39faGbi1p8zyFhsr/njgh1V1/6j4w/bV1t/dyj9MkqOSLE2ydNWqVYM5MknSpPEHGaV19IKzjpv0Or90+N9Pep3SRuJU4J1Atb//BLx6KhpSVacBpwHMmzevpqINkqR15xUsSdJGr6pur6oHquqXwL/SDQEEWAHs0lN0douNFb8T2DbJpqPiD9tXW79NKy9JmkFMsCRJG70kO/Xc/QNgZIbBxcChbQbA3YE5wBXAlcCcNmPg5nQTYSyuqgIuAQ5p2y8Azu/Z14K2fAjw5VZekjSDOERQkrRRSfJJYB9ghyTLgeOBfZLsQTdE8BbgzwGq6vok59L9mPH9wNFV9UDbzzHARcAmwMKqur5V8VbgnCTvAr4OnN7ipwNnJ1lGN8nGoUM+VEnSFDDBkiRtVKrqsD7h0/vERsqfBJzUJ34BcEGf+M08NMSwN/4z4GVr1VhJ0gbHIYKSJEmSNCAmWJIkSZI0ICZYkiRJkjQgJliSJEmSNCAmWJIkSZI0ICZYkiRJkjQgJliSJEmSNCAmWJIkSZI0ICZYkiRJkjQgJliSJEmSNCAmWJIkSZI0IENLsJLskuSSJDckuT7JG1p8+yRLktzU/m7X4klySpJlSa5JsmfPvha08jclWdATf2aSa9s2pyTJsI5HkiRJktZkmFew7gfeVFVzgb2Bo5PMBY4FLq6qOcDF7T7AgcCcdjsKOBW6hAw4Hng2sBdw/EhS1sq8pme7+UM8HkmSJEka19ASrKpaWVVfa8s/Am4EdgYOBha1YouAl7blg4GzqnMZsG2SnYADgCVVtbqq7gKWAPPbuq2r6rKqKuCsnn1JkiRJ0qSblO9gJdkNeAZwObBjVa1sq24DdmzLOwO39my2vMXGiy/vE+9X/1FJliZZumrVqvU6FkmSJEkay6bDriDJVsCngTdW1T29X5OqqkpSw25DVZ0GnAYwb968B+tbeeIHh131I+z09mMmvU5JkiRJk2OoV7CSbEaXXH28qj7Twre34X20v3e0+Apgl57NZ7fYePHZfeKSJEmSNCWGdgWrzeh3OnBjVb23Z9ViYAFwcvt7fk/8mCTn0E1ocXdVrUxyEfB3PRNb7A8cV1Wrk9yTZG+6oYeHAx8Y1vFI0iBd9p7vT3qde7/lCZNepyRJG5thDhF8LvBK4NokV7fY39AlVucmORL4LvDytu4C4CBgGfAT4AiAlki9E7iylTuxqla35dcBZwJbAhe2myRJkiRNiaElWFX1VWCs36Xar0/5Ao4eY18LgYV94kuBp61HMyVJkiRpYCZlFkFJkiRJ2hiYYEmSNipJFia5I8l1PbHtkyxJclP7u12LJ8kpSZYluSbJnj3bLGjlb0qyoCf+zCTXtm1Oad9JHrMOSdLMYoIlSdrYnAnMHxU7Fri4quYAF7f7AAcCc9rtKOBU6JIl4Hi6SZn2Ao7vSZhOBV7Ts938NdQhSZpBTLAkSRuVqvoKsHpU+GBgUVteBLy0J35WdS4Dtm0/MXIAsKSqVlfVXcASYH5bt3VVXda+W3zWqH31q0OSNIOYYEmSBDtW1cq2fBuwY1veGbi1p9zyFhsvvrxPfLw6HibJUUmWJlm6atWqdTwcSdJUGeY07ZIkbXCqqpLUVNVRVacBpwHMmzdvqO2QpIny9xsnzitYkiTB7W14H+3vHS2+Atilp9zsFhsvPrtPfLw6JEkziFewJEmCxcAC4OT29/ye+DFJzqGb0OLuqlqZ5CLg73omttgfOK6qVie5J8newOXA4cAH1lCHNClecNZxk17nlw7/+0mvU5pqJliSpI1Kkk8C+wA7JFlONxvgycC5SY4Evgu8vBW/ADgIWAb8BDgCoCVS7wSubOVOrKqRiTNeRzdT4ZbAhe3GOHVIkmYQEyxJ0kalqg4bY9V+fcoWcPQY+1kILOwTXwo8rU/8zn51SJJmFr+DJUmSJEkD4hWsaeR/3j36dy+H7zlv/cKk1ylJkiTNVF7BkiRJkqQBMcGSJEmSpAExwZIkSZKkATHBkiRJkqQBMcGSJEmSpAExwZIkSZKkAXGadkmSNhArT/zgpNe509uPmfQ6JWlD5hUsSZIkSRoQEyxJkiRJGhCHCEraKJywaMXk17lg50mvU5IkTS2vYEmSJEnSgJhgSZIkSdKAOERQG4y3nP78Sa/zPUdeMul1rqv9z/jIpNf5xSNeO+l1SpIkTWdDu4KVZGGSO5Jc1xPbPsmSJDe1v9u1eJKckmRZkmuS7NmzzYJW/qYkC3riz0xybdvmlCQZ1rFIkiRJ0kQMc4jgmcD8UbFjgYurag5wcbsPcCAwp92OAk6FLiEDjgeeDewFHD+SlLUyr+nZbnRdkiRJkjSphpZgVdVXgNWjwgcDi9ryIuClPfGzqnMZsG2SnYADgCVVtbqq7gKWAPPbuq2r6rKqKuCsnn1JkiRJ0pSY7O9g7VhVK9vybcCObXln4NaecstbbLz48j7xvpIcRXdljF133XU9mi9Jkkb8z7snf/DIc976hUmvU5LWxpTNItiuPNUk1XVaVc2rqnmzZs2ajColSZIkbYQmO8G6vQ3vo/29o8VXALv0lJvdYuPFZ/eJS5K0zpLc0iZQujrJ0hZzgiZJ0oRNdoK1GBjpaBYA5/fED2+d1d7A3W0o4UXA/km2ax3a/sBFbd09SfZundPhPfuSJGl9PL+q9qiqee2+EzRJkiZsaN/BSvJJYB9ghyTL6Tqbk4FzkxwJfBd4eSt+AXAQsAz4CXAEQFWtTvJO4MpW7sSqGpk443V0MxVuCVzYbpKmiRed8flJr/PzR7xo0uvURuFguv4MugmaLgXeSs8ETcBlSUYmaNqHNkETQJKRCZoupU3Q1OIjEzTZf0l6hBMWTf7grBMWjDmlgdbC0BKsqjpsjFX79SlbwNFj7GchsLBPfCnwtPVpoyRJoxTwxSQF/EtVncYkT9DkxEyStGGb7FkEtQE54wP7TnqdR7z+y5NepyT1+J2qWpHkV4AlSb7Zu7KqqiVfQ9OSutMA5s2bNymTQUmSBmfKZhGUJGm6qaoV7e8dwGfpvkPlBE2SpAkzwZIkCUjy2CSPG1mmm1jpOpygSZK0FhwiKElSZ0fgs23m9E2BT1TVF5JciRM0aR285fTnT3qd7znykkmvU9LDmWBJkgRU1c3A0/vE78QJmqSB2/+Mj0x6nV884rWTXqc2Pg4RlCRJkqQBMcGSJEmSpAFxiKAkSZI2ei864/OTXufnj3jRpNep4fMKliRJkiQNiFewJEnSjHDGB/ad9DqPeP2XJ71OSdObV7AkSZIkaUBMsCRJkiRpQEywJEmSJGlATLAkSZIkaUBMsCRJkiRpQEywJEmSJGlATLAkSZIkaUBMsCRJkiRpQEywJEmSJGlATLAkSZIkaUBMsCRJkiRpQEywJEmSJGlATLAkSZIkaUBMsCRJkiRpQEywJEmSJGlATLAkSZIkaUA2+AQryfwk30qyLMmxU90eSZLGY78lSTPbBp1gJdkE+BBwIDAXOCzJ3KltlSRJ/dlvSdLMt0EnWMBewLKqurmqfg6cAxw8xW2SJGks9luSNMOlqqa6DessySHA/Kr6s3b/lcCzq+qYUeWOAo5qd58MfGsA1e8A/GAA+xkU2zM+2zM+2zM+2zO+QbXn16pq1gD2M21NpN+yz5oStmd8tmfNplubbM/4htpvbTqAHU97VXUacNog95lkaVXNG+Q+14ftGZ/tGZ/tGZ/tGd90a8+Gzj5r8tme8dmeNZtubbI94xt2ezb0IYIrgF167s9uMUmSpiP7LUma4Tb0BOtKYE6S3ZNsDhwKLJ7iNkmSNBb7LUma4TboIYJVdX+SY4CLgE2AhVV1/SRVP9DhGwNge8Zne8Zne8Zne8Y33dozbU1hvzXdniPbMz7bM77p1h6Yfm2yPeMbans26EkuJEmSJGk62dCHCEqSJEnStGGCJUmSJEkDYoI1jiQLk9yR5Lox1ifJKUmWJbkmyZ5DbMsuSS5JckOS65O8YYrbs0WSK5J8o7XnHX3KPDrJp1p7Lk+y27Da01PnJkm+nuRz06Q9tyS5NsnVSZb2WT9pz1mrb9sk5yX5ZpIbkzxnqtqT5MntcRm53ZPkjVPVnlbfX7bX83VJPplki1HrJ+01lOQNrR3Xj35c2vqhPzb9/gcm2T7JkiQ3tb/bjbHtglbmpiQLBt029We/NW577LfW3Bb7rLHbYp+15vbYb42oKm9j3IDnAXsC142x/iDgQiDA3sDlQ2zLTsCebflxwP8Cc6ewPQG2asubAZcDe48q8zrgI235UOBTk/Cc/RXwCeBzfdZNRXtuAXYYZ/2kPWetvkXAn7XlzYFtp7I9PfVuAtxG94N9U/Wa3hn4DrBlu38u8KqpeA0BTwOuAx5DNxnRl4AnTfZj0+9/IPAe4Ni2fCzw7j7bbQ/c3P5u15a3m4zX0sZ+s98atz32W2tui33WxNpln/XI9thv9dy8gjWOqvoKsHqcIgcDZ1XnMmDbJDsNqS0rq+prbflHwI10b66pak9V1b3t7mbtNnrGlIPp/jkCnAfslyTDaA9AktnAi4CPjlFkUtszQZP2nCXZhu4fz+kAVfXzqvrhVLVnlP2Ab1fVd6e4PZsCWybZlK6T+H6f9kzGa+g36Tqen1TV/cB/An/Ypy1DfWzG+B/Y+xgsAl7aZ9MDgCVVtbqq7gKWAPMH2Tb1Z781bnvst9affVbHPuuR7Ld6mGCtn52BW3vuL+eRncfAtUu8z6A7+zZl7WnDGq4G7qB7UY7ZnvZmuxt4/LDaA/wz8Bbgl2Osn+z2QNd5fzHJVUmOGq9NzTCfs92BVcAZbTjKR5M8dgrb0+tQ4JN94pPWnqpaAfwj8D1gJXB3VX1xrPYM+TV0HfC7SR6f5DF0Z/12GVVmqp6rHatqZVu+DdixT5mpapvWzH7Lfms89lkTY5/1SPZbPUywNjBJtgI+Dbyxqu6ZyrZU1QNVtQcwG9grydOmqi1JXgzcUVVXTVUbxvA7VbUncCBwdJLnTWFbNqW7bH5qVT0D+DHdpfIple7HVl8C/NsUt2M7urNcuwNPAB6b5BVT0ZaquhF4N/BF4AvA1cADU9GW8VRV8cgrANLD2G/1N037LfusNbDP6s9+6+FMsNbPCh6enc9usaFIshldJ/XxqvrMVLdnRLtkfwmPvJT6YHva5ettgDuH1IznAi9JcgtwDrBvko9NYXuAB88wUVV3AJ8F9hqrTc0wn7PlwPKeM7bn0XVeU9WeEQcCX6uq2/usm8z2vAD4TlWtqqpfAJ8Bfnus9gz7NVRVp1fVM6vqecBddN9f6duWZlLe78DtI0M62t87+pSZqrZpzey3sN8ai33WhNhnjcF+6yEmWOtnMXB4mxVlb7rLsyvXtNG6aGNmTwdurKr3ToP2zEqybVveEngh8M0+7RmZheUQ4MvtzMHAVdVxVTW7qnaju3T/5aoafSZn0toDkOSxSR43sgzsT3cJfXSbJuU5q6rbgFuTPLmF9gNumKr29DiM/kMtJrs93wP2TvKY9n7bj+47I6PbMymvoSS/0v7uSjeO/RN92jLZz9VIvSOPwQLg/D5lLgL2T7JdO8u6f4tp6tlvYb/Vj33WhNlnjcF+q0cNeaaVDflG9wZaCfyC7kzKkcBrgde29QE+BHwbuBaYN8S2/A7dJc1r6C67Xk03vnWq2vNbwNdbe64D3t7iJwIvactb0F1CXwZcATxxkp63fWizMU1le4AnAt9ot+uBt7X4lDxnrb49gKXteft3uplyprI9j6U7m7ZNT2wq2/MOug9c1wFnA4+eqtcQ8F90Hya+Aew3FY/NGP8DHw9cDNxEN0vU9q3sPOCjPdu+uj1Oy4Ajhvm8eVvjc2a/VfZbE2iDfdaa22OfNX577LfaLW2HkiRJkqT15BBBSZIkSRoQEyxJkiRJGhATLEmSJEkaEBMsSZIkSRoQEyxJkiRJGhATLGkaSHJJkgNGxd6Y5NQxyl+aZN7ktE6SpIez35LGZoIlTQ+fpPuhyV6HMvaPGUqSNJXst6QxmGBJ08N5wIuSbA6QZDfgCcBhSZYmuT7JO/ptmOTenuVDkpzZlmcl+XSSK9vtucM+CEnSRsN+SxqDCZY0DVTVarpfWT+whQ4FzgXeVlXzgN8Cfi/Jb63Fbt8PvK+qngX8EfDRATZZkrQRs9+SxrbpVDdA0oNGhluc3/4eCbw8yVF079WdgLnANRPc3wuAuUlG7m+dZKuqunecbSRJmij7LakPEyxp+jgfeF+SPYHHAKuBNwPPqqq72hCKLfpsVz3LvesfBexdVT8bUnslSRs3+y2pD4cIStNEO0N3CbCQ7qzg1sCPgbuT7MhDwzBGuz3JbyZ5FPAHPfEvAq8fuZNkj6E0XJK0UbLfkvozwZKml08CTwc+WVXfAL4OfBP4BPD/jbHNscDngP8GVvbE/wKYl+SaJDcArx1aqyVJGyv7LWmUVNWaS0mSJEmS1sgrWJIkSZI0ICZYkiRJkjQgJliSJEmSNCAmWJIkSZI0ICZYkiRJkjQgJliSJEmSNCAmWJIkSZI0IP8/huGvNRpoD/sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(sorted(zip(df_customers.columns, pca.components_[0]), key=lambda x: x[1])[:5],\n",
    "            columns=['feature','coef'])\n",
    "for column in (df['feature'].values):\n",
    "    h.plot_comparison_charts(column,df_customers,df_azdias)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top 5 important features for component 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(sorted(zip(df_customers.columns, pca.components_[1]), key=lambda x: x[1])[-5:],\n",
    "            columns=['feature','coef'])\n",
    "for column in (df['feature'].values):\n",
    "    h.plot_comparison_charts(column,df_customers,df_azdias)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top 5 important features for component 2 with least coef"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(sorted(zip(df_customers.columns, pca.components_[1]), key=lambda x: x[1])[:5],\n",
    "            columns=['feature','coef'])\n",
    "for column in (df['feature'].values):\n",
    "    h.plot_comparison_charts(column,df_customers,df_azdias)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apply PCA to transform CUSTOMER and AZDIAS dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_customers_pca = pca.transform(df_customers_scaled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_azdias_pca = pca.transform(df_azdias_scaled)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### K-Means\n",
    "Define clusters of customers to identify their behaviour "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   centroids         score\n",
      "0         30  2.104340e+06\n",
      "1         25  2.291471e+06\n",
      "2         22  2.442962e+06\n",
      "3         20  2.560410e+06\n",
      "4         15  2.976282e+06\n",
      "5         11  3.537861e+06\n",
      "6         10  3.769443e+06\n",
      "7          5  6.467182e+06\n",
      "8          2  1.393745e+07\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Sum of Squared Errors')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Function to calculate K-Means score for a centroid\n",
    "def elbow_method(data, center):\n",
    "    kmeans = KMeans(n_clusters = center, n_init=10, max_iter=300, random_state=42)\n",
    "    model = kmeans.fit(data)\n",
    "    score = np.abs(model.score(data))\n",
    "    return score\n",
    "\n",
    "# Run possible number of cluster centroid through K-means score function\n",
    "score_pca = []\n",
    "centroids = [2,5,10,11,15,20,22,25,30]\n",
    "\n",
    "for x in centroids:\n",
    "    score_pca.append(elbow_method(df_customers_pca[:,:5],x))\n",
    "    \n",
    "# print score report\n",
    "print(pd.DataFrame(sorted(zip(centroids, score_pca), key=lambda x: x[1]),\n",
    "            columns=['centroids','score']))\n",
    "\n",
    "plt.plot(centroids,score_pca,linestyle='-',linewidth=3,marker='o')\n",
    "plt.xlabel('K-centroids')\n",
    "plt.ylabel('Sum of Squared Errors')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the plot above the error rate is decreasing less gradually after 10 clusters. As a result, we choose 10 as our final cluster number."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans = KMeans(10, random_state=123)\n",
    "clusters_pop = kmeans.fit_predict(df_azdias_pca)\n",
    "clusters_cust = kmeans.predict(df_customers_pca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'algorithm': 'auto',\n",
       " 'copy_x': True,\n",
       " 'init': 'k-means++',\n",
       " 'max_iter': 300,\n",
       " 'n_clusters': 10,\n",
       " 'n_init': 10,\n",
       " 'n_jobs': None,\n",
       " 'precompute_distances': 'auto',\n",
       " 'random_state': 123,\n",
       " 'tol': 0.0001,\n",
       " 'verbose': 0}"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans.get_params()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax=fig.add_axes([0,0,2,1], title='Azdias vs Customer distribution plot')\n",
    "sns.set(style=\"darkgrid\")\n",
    "sns.distplot(clusters_pop, label='Azdias',ax=ax)\n",
    "sns.distplot(clusters_cust, label='Customer', ax=ax)\n",
    "ax.legend()\n",
    "#plt.savefig('k_dist', quality = 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on cluster distribution histogram on both datasets, it is clear to see that Cluster 9 is outstanding for customers, which means people in this group is more likely to be part of the mail-order company’s main customer base than other groups."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 2: Supervised Learning Model\n",
    "\n",
    "After finding which parts of the population are more likely to be customers of the mail-order company, it's time to build a prediction model. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv('data/Udacity_MAILOUT_052018_TRAIN.csv', sep=';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 42962 entries, 0 to 42961\n",
      "Columns: 367 entries, LNR to ALTERSKATEGORIE_GROB\n",
      "dtypes: float64(267), int64(94), object(6)\n",
      "memory usage: 120.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df_train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_clean = h.data_pre_process_test(df_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = df_train_clean.iloc[:,df_train_clean.columns != 'RESPONSE']\n",
    "y_train = df_train_clean['RESPONSE']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler_model = StandardScaler()\n",
    "X_train = scaler_model.fit_transform(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Distribution of REPSONSE variable')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(y_train).set_title('Distribution of REPSONSE variable')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is clear from the above figure that the data is highly imbalanced."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6604681258910036\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "                   intercept_scaling=1, l1_ratio=None, max_iter=100,\n",
       "                   multi_class='auto', n_jobs=None, penalty='l2',\n",
       "                   random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\n",
       "                   warm_start=False)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# LogisticRegression\n",
    "lor = LogisticRegression(random_state=123)\n",
    "h.classifier_GS(lor, {}, X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# RandomForestClassifier\n",
    "rfc = RandomForestClassifier(random_state=123)\n",
    "h.classifier_GS(rfc, {}, X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7564488813568817\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "GradientBoostingClassifier(ccp_alpha=0.0, criterion='friedman_mse', init=None,\n",
       "                           learning_rate=0.1, loss='deviance', max_depth=3,\n",
       "                           max_features=None, max_leaf_nodes=None,\n",
       "                           min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                           min_samples_leaf=1, min_samples_split=2,\n",
       "                           min_weight_fraction_leaf=0.0, n_estimators=100,\n",
       "                           n_iter_no_change=None, presort='deprecated',\n",
       "                           random_state=123, subsample=1.0, tol=0.0001,\n",
       "                           validation_fraction=0.1, verbose=0,\n",
       "                           warm_start=False)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# GradientBoostingClassifier\n",
    "gbc = GradientBoostingClassifier(random_state=123)\n",
    "gbc = h.classifier_GS(gbc, {}, X_train, y_train)\n",
    "gbc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#catboost classifier\n",
    "catboost = CatBoostClassifier(random_state=123, silent=True)\n",
    "h.classifier_GS(catboost,{}, X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7702320870126916\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'depth': 2,\n",
       " 'l2_leaf_reg': 1,\n",
       " 'border_count': 3,\n",
       " 'silent': True,\n",
       " 'random_state': 123}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# tune the most promising classifier with the help of GridSearchCV\n",
    "# the result is our model that will be used with the test set\n",
    "cbc = CatBoostClassifier(random_state=123, silent=True)\n",
    "param_grid = {'depth' : [2,3],\n",
    "              'border_count': [3,5],\n",
    "              'l2_leaf_reg':[1,3]\n",
    "             }\n",
    "\n",
    "cbc_best_est = h.classifier_GS(cbc, param_grid, X_train, y_train)\n",
    "cbc_best_est\n",
    "\n",
    "cbc_best_est.get_params()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 3: Kaggle Competition\n",
    "\n",
    "After creating the model to predict which individuals are most likely to respond to a mailout campaign, it's time to test that model in competition through Kaggle  [here](http://www.kaggle.com/t/21e6d45d4c574c7fa2d868f0e8c83140).\n",
    "\n",
    "The entry to the competition should be a CSV file with two columns. The first column should be a copy of \"LNR\", which acts as an ID number for each individual in the \"TEST\" partition. The second column, \"RESPONSE\", should be some measure of how likely each individual became a customer.\n",
    "<br>\n",
    "\n",
    "Medium post with findings : https://medium.com/@vaibhav3m/effectively-target-customers-use-data-for-customer-segmentation-fb6425b593fd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "mailout_test = pd.read_csv('data/Udacity_MAILOUT_052018_TEST.csv', sep=';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 42833 entries, 0 to 42832\n",
      "Columns: 366 entries, LNR to ALTERSKATEGORIE_GROB\n",
      "dtypes: float64(267), int64(93), object(6)\n",
      "memory usage: 119.6+ MB\n"
     ]
    }
   ],
   "source": [
    "mailout_test.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_ids = mailout_test.LNR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test_processed = h.data_pre_process_test(mailout_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test_processed = scaler_model.fit_transform(df_test_processed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.95170983, 0.04829017],\n",
       "       [0.9718091 , 0.0281909 ],\n",
       "       [0.99720556, 0.00279444],\n",
       "       ...,\n",
       "       [0.98739398, 0.01260602],\n",
       "       [0.98328971, 0.01671029],\n",
       "       [0.98303055, 0.01696945]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict_prob = cbc_best_est.predict_proba(df_test_processed)\n",
    "predict_prob"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generate output file for the Kaggle competition"
   ]
  },
  {
   "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>LNR</th>\n",
       "      <th>RESPONSE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1754</td>\n",
       "      <td>0.048290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1770</td>\n",
       "      <td>0.028191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1465</td>\n",
       "      <td>0.002794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1470</td>\n",
       "      <td>0.002398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1478</td>\n",
       "      <td>0.000966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1782</td>\n",
       "      <td>0.002275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1485</td>\n",
       "      <td>0.002454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1519</td>\n",
       "      <td>0.025249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1835</td>\n",
       "      <td>0.020654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1522</td>\n",
       "      <td>0.004573</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    LNR  RESPONSE\n",
       "0  1754  0.048290\n",
       "1  1770  0.028191\n",
       "2  1465  0.002794\n",
       "3  1470  0.002398\n",
       "4  1478  0.000966\n",
       "5  1782  0.002275\n",
       "6  1485  0.002454\n",
       "7  1519  0.025249\n",
       "8  1835  0.020654\n",
       "9  1522  0.004573"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# generate prediction file for the competition\n",
    "result = pd.DataFrame({'LNR':test_ids, 'RESPONSE':predict_prob[:,1]})\n",
    "result.to_csv(path_or_buf='./predictions2.csv', index=False)\n",
    "result.head(10)"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}