1. Customer Segmentation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Customer Analytics - Segmentation\n",
    "*Author: Shawn Sun*\n",
    "<br>\n",
    "*Date: 2021/02/25*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "\n",
    "#for standardizing\n",
    "from sklearn.preprocessing import StandardScaler \n",
    "#for hierarchical clustering\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage \n",
    "#for K-Means clustering \n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "# For saving the model\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_segmentation = pd.read_csv('segmentation data.csv', index_col = 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100000001</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>2</td>\n",
       "      <td>124670</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000002</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>150773</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000003</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>1</td>\n",
       "      <td>89210</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000004</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>171565</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000005</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>149031</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Sex  Marital status  Age  Education  Income  Occupation  \\\n",
       "ID                                                                   \n",
       "100000001    0               0   67          2  124670           1   \n",
       "100000002    1               1   22          1  150773           1   \n",
       "100000003    0               0   49          1   89210           0   \n",
       "100000004    0               0   45          1  171565           1   \n",
       "100000005    0               0   53          1  149031           1   \n",
       "\n",
       "           Settlement size  \n",
       "ID                          \n",
       "100000001                2  \n",
       "100000002                2  \n",
       "100000003                0  \n",
       "100000004                1  \n",
       "100000005                1  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_segmentation.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2000.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>2000.00000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.457000</td>\n",
       "      <td>0.496500</td>\n",
       "      <td>35.909000</td>\n",
       "      <td>1.03800</td>\n",
       "      <td>120954.419000</td>\n",
       "      <td>0.810500</td>\n",
       "      <td>0.739000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.498272</td>\n",
       "      <td>0.500113</td>\n",
       "      <td>11.719402</td>\n",
       "      <td>0.59978</td>\n",
       "      <td>38108.824679</td>\n",
       "      <td>0.638587</td>\n",
       "      <td>0.812533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>35832.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>97663.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>115548.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>138072.250000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>309364.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Sex  Marital status          Age   Education         Income  \\\n",
       "count  2000.000000     2000.000000  2000.000000  2000.00000    2000.000000   \n",
       "mean      0.457000        0.496500    35.909000     1.03800  120954.419000   \n",
       "std       0.498272        0.500113    11.719402     0.59978   38108.824679   \n",
       "min       0.000000        0.000000    18.000000     0.00000   35832.000000   \n",
       "25%       0.000000        0.000000    27.000000     1.00000   97663.250000   \n",
       "50%       0.000000        0.000000    33.000000     1.00000  115548.500000   \n",
       "75%       1.000000        1.000000    42.000000     1.00000  138072.250000   \n",
       "max       1.000000        1.000000    76.000000     3.00000  309364.000000   \n",
       "\n",
       "        Occupation  Settlement size  \n",
       "count  2000.000000      2000.000000  \n",
       "mean      0.810500         0.739000  \n",
       "std       0.638587         0.812533  \n",
       "min       0.000000         0.000000  \n",
       "25%       0.000000         0.000000  \n",
       "50%       1.000000         1.000000  \n",
       "75%       1.000000         1.000000  \n",
       "max       2.000000         2.000000  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_segmentation.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation estimate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Sex</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.566511</td>\n",
       "      <td>-0.182885</td>\n",
       "      <td>0.244838</td>\n",
       "      <td>-0.195146</td>\n",
       "      <td>-0.202491</td>\n",
       "      <td>-0.300803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marital status</th>\n",
       "      <td>0.566511</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.213178</td>\n",
       "      <td>0.374017</td>\n",
       "      <td>-0.073528</td>\n",
       "      <td>-0.029490</td>\n",
       "      <td>-0.097041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>-0.182885</td>\n",
       "      <td>-0.213178</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.654605</td>\n",
       "      <td>0.340610</td>\n",
       "      <td>0.108388</td>\n",
       "      <td>0.119751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>0.244838</td>\n",
       "      <td>0.374017</td>\n",
       "      <td>0.654605</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.233459</td>\n",
       "      <td>0.064524</td>\n",
       "      <td>0.034732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Income</th>\n",
       "      <td>-0.195146</td>\n",
       "      <td>-0.073528</td>\n",
       "      <td>0.340610</td>\n",
       "      <td>0.233459</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.680357</td>\n",
       "      <td>0.490881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Occupation</th>\n",
       "      <td>-0.202491</td>\n",
       "      <td>-0.029490</td>\n",
       "      <td>0.108388</td>\n",
       "      <td>0.064524</td>\n",
       "      <td>0.680357</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.571795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Settlement size</th>\n",
       "      <td>-0.300803</td>\n",
       "      <td>-0.097041</td>\n",
       "      <td>0.119751</td>\n",
       "      <td>0.034732</td>\n",
       "      <td>0.490881</td>\n",
       "      <td>0.571795</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Sex  Marital status       Age  Education    Income  \\\n",
       "Sex              1.000000        0.566511 -0.182885   0.244838 -0.195146   \n",
       "Marital status   0.566511        1.000000 -0.213178   0.374017 -0.073528   \n",
       "Age             -0.182885       -0.213178  1.000000   0.654605  0.340610   \n",
       "Education        0.244838        0.374017  0.654605   1.000000  0.233459   \n",
       "Income          -0.195146       -0.073528  0.340610   0.233459  1.000000   \n",
       "Occupation      -0.202491       -0.029490  0.108388   0.064524  0.680357   \n",
       "Settlement size -0.300803       -0.097041  0.119751   0.034732  0.490881   \n",
       "\n",
       "                 Occupation  Settlement size  \n",
       "Sex               -0.202491        -0.300803  \n",
       "Marital status    -0.029490        -0.097041  \n",
       "Age                0.108388         0.119751  \n",
       "Education          0.064524         0.034732  \n",
       "Income             0.680357         0.490881  \n",
       "Occupation         1.000000         0.571795  \n",
       "Settlement size    0.571795         1.000000  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_segmentation.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot a heatmap\n",
    "plt.figure(figsize = (12, 9))\n",
    "s = sns.heatmap(df_segmentation.corr(),\n",
    "               annot = True, #write the data value in each cell\n",
    "               cmap = 'RdBu', #color scheme\n",
    "               vmin = -1, \n",
    "               vmax = 1) #set the higher and lower bound\n",
    "s.set_yticklabels(s.get_yticklabels(), rotation = 0, fontsize = 12)\n",
    "s.set_xticklabels(s.get_xticklabels(), rotation = -45, fontsize = 12)\n",
    "plt.title('Correlation Heatmap')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize raw data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Visualization of raw data')"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter Plot: Income vs Age\n",
    "plt.figure(figsize = (12, 9))\n",
    "plt.scatter(df_segmentation.iloc[:, 2], df_segmentation.iloc[:, 4])\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Income')\n",
    "plt.title('Visualization of raw data')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Standardization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standardizing data, so that all features have equal weight\n",
    "scaler = StandardScaler() #Create an instance\n",
    "segmentation_std = scaler.fit_transform(df_segmentation) #Apply the fit transformation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hierarchical clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "hier_clust = linkage(segmentation_std, method = 'ward')\n",
    "# Perform Hierarchical Clustering\n",
    "# The results are returned as a linkage matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12,9))\n",
    "plt.title('Hierarchical Clustering Dendrogram')\n",
    "plt.xlabel('Observations')\n",
    "plt.ylabel('Distance')\n",
    "dendrogram(hier_clust,\n",
    "           truncate_mode = 'level', \n",
    "           p = 5, \n",
    "           show_leaf_counts = False, \n",
    "           no_labels = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## K-Means Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Perform K-means clustering\n",
    "# Consider 1 to 10 clusters\n",
    "wcss = []\n",
    "for i in range(1,11):\n",
    "    kmeans = KMeans(n_clusters = i, \n",
    "                    init = 'k-means++', \n",
    "                    # run the algortihm at many different starting points\n",
    "                    random_state = 42)\n",
    "    kmeans.fit(segmentation_std)\n",
    "    wcss.append(kmeans.inertia_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the Within Cluster Sum of Squares for the different number of clusters\n",
    "plt.figure(figsize = (10,8))\n",
    "plt.plot(range(1, 11), wcss, marker = 'o', linestyle = '--')\n",
    "plt.xlabel('Number of Clusters')\n",
    "plt.ylabel('WCSS')\n",
    "plt.title('K-means Clustering')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(n_clusters=4, random_state=42)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We choose 4 clusters to get K-means\n",
    "kmeans = KMeans(n_clusters = 4, init = 'k-means++', random_state = 42)\n",
    "# Divide data into 4 clusters\n",
    "kmeans.fit(segmentation_std)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## K-Means Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a new data frame with the original features and \n",
    "#  add a new column with the assigned clusters for each point\n",
    "df_segm_kmeans = df_segmentation.copy()\n",
    "df_segm_kmeans['Segment K-means'] = kmeans.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Segment K-means</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.501901</td>\n",
       "      <td>0.692015</td>\n",
       "      <td>55.703422</td>\n",
       "      <td>2.129278</td>\n",
       "      <td>158338.422053</td>\n",
       "      <td>1.129278</td>\n",
       "      <td>1.110266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.352814</td>\n",
       "      <td>0.019481</td>\n",
       "      <td>35.577922</td>\n",
       "      <td>0.746753</td>\n",
       "      <td>97859.852814</td>\n",
       "      <td>0.329004</td>\n",
       "      <td>0.043290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.029825</td>\n",
       "      <td>0.173684</td>\n",
       "      <td>35.635088</td>\n",
       "      <td>0.733333</td>\n",
       "      <td>141218.249123</td>\n",
       "      <td>1.271930</td>\n",
       "      <td>1.522807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.853901</td>\n",
       "      <td>0.997163</td>\n",
       "      <td>28.963121</td>\n",
       "      <td>1.068085</td>\n",
       "      <td>105759.119149</td>\n",
       "      <td>0.634043</td>\n",
       "      <td>0.422695</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Sex  Marital status        Age  Education  \\\n",
       "Segment K-means                                                   \n",
       "0                0.501901        0.692015  55.703422   2.129278   \n",
       "1                0.352814        0.019481  35.577922   0.746753   \n",
       "2                0.029825        0.173684  35.635088   0.733333   \n",
       "3                0.853901        0.997163  28.963121   1.068085   \n",
       "\n",
       "                        Income  Occupation  Settlement size  \n",
       "Segment K-means                                              \n",
       "0                158338.422053    1.129278         1.110266  \n",
       "1                 97859.852814    0.329004         0.043290  \n",
       "2                141218.249123    1.271930         1.522807  \n",
       "3                105759.119149    0.634043         0.422695  "
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate mean values for the clusters\n",
    "df_segm_analysis = df_segm_kmeans.groupby(['Segment K-means']).mean()\n",
    "df_segm_analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "      <th>N Obs</th>\n",
       "      <th>Prop Obs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Segment K-means</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.501901</td>\n",
       "      <td>0.692015</td>\n",
       "      <td>55.703422</td>\n",
       "      <td>2.129278</td>\n",
       "      <td>158338.422053</td>\n",
       "      <td>1.129278</td>\n",
       "      <td>1.110266</td>\n",
       "      <td>263</td>\n",
       "      <td>0.1315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.352814</td>\n",
       "      <td>0.019481</td>\n",
       "      <td>35.577922</td>\n",
       "      <td>0.746753</td>\n",
       "      <td>97859.852814</td>\n",
       "      <td>0.329004</td>\n",
       "      <td>0.043290</td>\n",
       "      <td>462</td>\n",
       "      <td>0.2310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.029825</td>\n",
       "      <td>0.173684</td>\n",
       "      <td>35.635088</td>\n",
       "      <td>0.733333</td>\n",
       "      <td>141218.249123</td>\n",
       "      <td>1.271930</td>\n",
       "      <td>1.522807</td>\n",
       "      <td>570</td>\n",
       "      <td>0.2850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.853901</td>\n",
       "      <td>0.997163</td>\n",
       "      <td>28.963121</td>\n",
       "      <td>1.068085</td>\n",
       "      <td>105759.119149</td>\n",
       "      <td>0.634043</td>\n",
       "      <td>0.422695</td>\n",
       "      <td>705</td>\n",
       "      <td>0.3525</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Sex  Marital status        Age  Education  \\\n",
       "Segment K-means                                                   \n",
       "0                0.501901        0.692015  55.703422   2.129278   \n",
       "1                0.352814        0.019481  35.577922   0.746753   \n",
       "2                0.029825        0.173684  35.635088   0.733333   \n",
       "3                0.853901        0.997163  28.963121   1.068085   \n",
       "\n",
       "                        Income  Occupation  Settlement size  N Obs  Prop Obs  \n",
       "Segment K-means                                                               \n",
       "0                158338.422053    1.129278         1.110266    263    0.1315  \n",
       "1                 97859.852814    0.329004         0.043290    462    0.2310  \n",
       "2                141218.249123    1.271930         1.522807    570    0.2850  \n",
       "3                105759.119149    0.634043         0.422695    705    0.3525  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute the size and proportions of the four clusters\n",
    "df_segm_analysis['N Obs'] = \\\n",
    "df_segm_kmeans[['Segment K-means','Sex']].groupby(['Segment K-means']).count()\n",
    "df_segm_analysis['Prop Obs'] = \\\n",
    "df_segm_analysis['N Obs'] / df_segm_analysis['N Obs'].sum()\n",
    "df_segm_analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "      <th>N Obs</th>\n",
       "      <th>Prop Obs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Segment K-means</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>well-off</th>\n",
       "      <td>0.501901</td>\n",
       "      <td>0.692015</td>\n",
       "      <td>55.703422</td>\n",
       "      <td>2.129278</td>\n",
       "      <td>158338.422053</td>\n",
       "      <td>1.129278</td>\n",
       "      <td>1.110266</td>\n",
       "      <td>263</td>\n",
       "      <td>0.1315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fewer-opportunities</th>\n",
       "      <td>0.352814</td>\n",
       "      <td>0.019481</td>\n",
       "      <td>35.577922</td>\n",
       "      <td>0.746753</td>\n",
       "      <td>97859.852814</td>\n",
       "      <td>0.329004</td>\n",
       "      <td>0.043290</td>\n",
       "      <td>462</td>\n",
       "      <td>0.2310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>standard</th>\n",
       "      <td>0.029825</td>\n",
       "      <td>0.173684</td>\n",
       "      <td>35.635088</td>\n",
       "      <td>0.733333</td>\n",
       "      <td>141218.249123</td>\n",
       "      <td>1.271930</td>\n",
       "      <td>1.522807</td>\n",
       "      <td>570</td>\n",
       "      <td>0.2850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>career focused</th>\n",
       "      <td>0.853901</td>\n",
       "      <td>0.997163</td>\n",
       "      <td>28.963121</td>\n",
       "      <td>1.068085</td>\n",
       "      <td>105759.119149</td>\n",
       "      <td>0.634043</td>\n",
       "      <td>0.422695</td>\n",
       "      <td>705</td>\n",
       "      <td>0.3525</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Sex  Marital status        Age  Education  \\\n",
       "Segment K-means                                                       \n",
       "well-off             0.501901        0.692015  55.703422   2.129278   \n",
       "fewer-opportunities  0.352814        0.019481  35.577922   0.746753   \n",
       "standard             0.029825        0.173684  35.635088   0.733333   \n",
       "career focused       0.853901        0.997163  28.963121   1.068085   \n",
       "\n",
       "                            Income  Occupation  Settlement size  N Obs  \\\n",
       "Segment K-means                                                          \n",
       "well-off             158338.422053    1.129278         1.110266    263   \n",
       "fewer-opportunities   97859.852814    0.329004         0.043290    462   \n",
       "standard             141218.249123    1.271930         1.522807    570   \n",
       "career focused       105759.119149    0.634043         0.422695    705   \n",
       "\n",
       "                     Prop Obs  \n",
       "Segment K-means                \n",
       "well-off               0.1315  \n",
       "fewer-opportunities    0.2310  \n",
       "standard               0.2850  \n",
       "career focused         0.3525  "
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Map the name of our clusters\n",
    "df_segm_analysis.rename({0:'well-off',\n",
    "                         1:'fewer-opportunities',\n",
    "                         2:'standard',\n",
    "                         3:'career focused'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "      <th>Segment K-means</th>\n",
       "      <th>Labels</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100000001</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>2</td>\n",
       "      <td>124670</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>well-off</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000002</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>150773</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>career focused</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000003</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>1</td>\n",
       "      <td>89210</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>fewer opportunities</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000004</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>171565</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>standard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000005</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>149031</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>standard</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Sex  Marital status  Age  Education  Income  Occupation  \\\n",
       "ID                                                                   \n",
       "100000001    0               0   67          2  124670           1   \n",
       "100000002    1               1   22          1  150773           1   \n",
       "100000003    0               0   49          1   89210           0   \n",
       "100000004    0               0   45          1  171565           1   \n",
       "100000005    0               0   53          1  149031           1   \n",
       "\n",
       "           Settlement size  Segment K-means               Labels  \n",
       "ID                                                                \n",
       "100000001                2                0             well-off  \n",
       "100000002                2                3       career focused  \n",
       "100000003                0                1  fewer opportunities  \n",
       "100000004                1                2             standard  \n",
       "100000005                1                2             standard  "
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add the segment labels to our table\n",
    "df_segm_kmeans['Labels'] = df_segm_kmeans['Segment K-means'].map({0:'well-off', \n",
    "                                                                  1:'fewer opportunities',\n",
    "                                                                  2:'standard', \n",
    "                                                                  3:'career focused'})\n",
    "df_segm_kmeans.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the results from the K-means algorithm\n",
    "# Color: the clusters it has been assigned to\n",
    "x_axis = df_segm_kmeans['Age']\n",
    "y_axis = df_segm_kmeans['Income']\n",
    "plt.figure(figsize = (10, 8))\n",
    "sns.scatterplot(x_axis, y_axis, hue = df_segm_kmeans['Labels'], palette = ['g', 'r', 'c', 'm'])\n",
    "plt.title('Segmentation K-means')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Note from the plot: we can only identify the well-off cluster, therefore we need to perform the clustering with PCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Employ PCA to find a subset of components, \n",
    "#  which explain the variance in the data.\n",
    "# Create an instance\n",
    "pca = PCA()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PCA()"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit PCA with our standardized data.\n",
    "pca.fit(segmentation_std)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.35696328, 0.26250923, 0.18821114, 0.0755775 , 0.05716512,\n",
       "       0.03954794, 0.02002579])"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Shows how much variance is explained by each of the seven individual components.\n",
    "pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Cumulative Explained Variance')"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the cumulative variance explained by total number of components.\n",
    "# On this graph we choose the subset of components we want to keep. \n",
    "# Generally, we want to keep around 80 % of the explained variance.\n",
    "plt.figure(figsize = (12,9))\n",
    "plt.plot(range(1,8), pca.explained_variance_ratio_.cumsum(), marker = 'o', linestyle = '--')\n",
    "plt.title('Explained Variance by Components')\n",
    "plt.xlabel('Number of Components')\n",
    "plt.ylabel('Cumulative Explained Variance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Choose 3 components\n",
    "pca = PCA(n_components = 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PCA(n_components=3)"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Fit the model the our data with the selected number of components\n",
    "pca.fit(segmentation_std)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PCA Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.31469524, -0.19170439,  0.32609979,  0.15684089,  0.52452463,\n",
       "         0.49205868,  0.46478852],\n",
       "       [ 0.45800608,  0.51263492,  0.31220793,  0.63980683,  0.12468314,\n",
       "         0.01465779, -0.06963165],\n",
       "       [-0.29301261, -0.44197739,  0.60954372,  0.27560461, -0.16566231,\n",
       "        -0.39550539, -0.29568503]])"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The components attribute shows the loadings of each component on each of the seven original features.\n",
    "# The loadings are the correlations between the components and the original features. \n",
    "pca.components_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Component 1</th>\n",
       "      <td>-0.314695</td>\n",
       "      <td>-0.191704</td>\n",
       "      <td>0.326100</td>\n",
       "      <td>0.156841</td>\n",
       "      <td>0.524525</td>\n",
       "      <td>0.492059</td>\n",
       "      <td>0.464789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Component 2</th>\n",
       "      <td>0.458006</td>\n",
       "      <td>0.512635</td>\n",
       "      <td>0.312208</td>\n",
       "      <td>0.639807</td>\n",
       "      <td>0.124683</td>\n",
       "      <td>0.014658</td>\n",
       "      <td>-0.069632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Component 3</th>\n",
       "      <td>-0.293013</td>\n",
       "      <td>-0.441977</td>\n",
       "      <td>0.609544</td>\n",
       "      <td>0.275605</td>\n",
       "      <td>-0.165662</td>\n",
       "      <td>-0.395505</td>\n",
       "      <td>-0.295685</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Sex  Marital status       Age  Education    Income  \\\n",
       "Component 1 -0.314695       -0.191704  0.326100   0.156841  0.524525   \n",
       "Component 2  0.458006        0.512635  0.312208   0.639807  0.124683   \n",
       "Component 3 -0.293013       -0.441977  0.609544   0.275605 -0.165662   \n",
       "\n",
       "             Occupation  Settlement size  \n",
       "Component 1    0.492059         0.464789  \n",
       "Component 2    0.014658        -0.069632  \n",
       "Component 3   -0.395505        -0.295685  "
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Put loadings into proper data frames\n",
    "df_pca_comp = pd.DataFrame(data = pca.components_,\n",
    "                           columns = df_segmentation.columns.values,\n",
    "                           index = ['Component 1', 'Component 2', 'Component 3'])\n",
    "df_pca_comp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5]),\n",
       " [Text(0.5, 0, 'Sex'),\n",
       "  Text(1.5, 0, 'Marital status'),\n",
       "  Text(2.5, 0, 'Age'),\n",
       "  Text(3.5, 0, 'Education'),\n",
       "  Text(4.5, 0, 'Income'),\n",
       "  Text(5.5, 0, 'Occupation'),\n",
       "  Text(6.5, 0, 'Settlement size')])"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heat Map for Principal Components against original features\n",
    "sns.heatmap(df_pca_comp,\n",
    "            vmin = -1, \n",
    "            vmax = 1,\n",
    "            cmap = 'RdBu',\n",
    "            annot = True)\n",
    "plt.yticks([0, 1, 2], \n",
    "           ['Component 1', 'Component 2', 'Component 3'],\n",
    "           rotation = 0,\n",
    "           fontsize = 9)\n",
    "plt.xticks(rotation=-45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.51474593,  0.83412239,  2.1748059 ],\n",
       "       [ 0.34493528,  0.59814564, -2.21160279],\n",
       "       [-0.65106267, -0.68009318,  2.2804186 ],\n",
       "       ...,\n",
       "       [-1.45229829, -2.23593665,  0.89657125],\n",
       "       [-2.24145254,  0.62710847, -0.53045631],\n",
       "       [-1.86688505, -2.45467234,  0.66262172]])"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Transform the 7 components to 3, for each obs\n",
    "scores_pca = pca.transform(segmentation_std)\n",
    "scores_pca"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## K-means clustering with PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fit K means using the transformed data from the PCA.\n",
    "wcss = []\n",
    "for i in range(1,11):\n",
    "    kmeans_pca = KMeans(n_clusters = i, init = 'k-means++', random_state = 42)\n",
    "    kmeans_pca.fit(scores_pca)\n",
    "    wcss.append(kmeans_pca.inertia_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the Within Cluster Sum of Squares for the K-means PCA model\n",
    "plt.figure(figsize = (10,8))\n",
    "plt.plot(range(1, 11), wcss, marker = 'o', linestyle = '--')\n",
    "plt.xlabel('Number of Clusters')\n",
    "plt.ylabel('WCSS')\n",
    "plt.title('K-means with PCA Clustering')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run K-means with number of clusters equals four\n",
    "# Same initializer and random state as before\n",
    "kmeans_pca = KMeans(n_clusters = 4, init = 'k-means++', random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(n_clusters=4, random_state=42)"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit our data with the k-means pca model\n",
    "kmeans_pca.fit(scores_pca)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## K-means clustering with PCA Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "      <th>Component 1</th>\n",
       "      <th>Component 2</th>\n",
       "      <th>Component 3</th>\n",
       "      <th>Segment K-means PCA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>2</td>\n",
       "      <td>124670</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2.514746</td>\n",
       "      <td>0.834122</td>\n",
       "      <td>2.174806</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>150773</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344935</td>\n",
       "      <td>0.598146</td>\n",
       "      <td>-2.211603</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>1</td>\n",
       "      <td>89210</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.651063</td>\n",
       "      <td>-0.680093</td>\n",
       "      <td>2.280419</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>171565</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.714316</td>\n",
       "      <td>-0.579927</td>\n",
       "      <td>0.730731</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>149031</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.626745</td>\n",
       "      <td>-0.440496</td>\n",
       "      <td>1.244909</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "      <td>123525</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.866034</td>\n",
       "      <td>0.298330</td>\n",
       "      <td>1.438958</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>117744</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.114957</td>\n",
       "      <td>0.794727</td>\n",
       "      <td>-1.079871</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>86400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.452298</td>\n",
       "      <td>-2.235937</td>\n",
       "      <td>0.896571</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>97968</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-2.241453</td>\n",
       "      <td>0.627108</td>\n",
       "      <td>-0.530456</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>68416</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.866885</td>\n",
       "      <td>-2.454672</td>\n",
       "      <td>0.662622</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Sex  Marital status  Age  Education  Income  Occupation  \\\n",
       "0       0               0   67          2  124670           1   \n",
       "1       1               1   22          1  150773           1   \n",
       "2       0               0   49          1   89210           0   \n",
       "3       0               0   45          1  171565           1   \n",
       "4       0               0   53          1  149031           1   \n",
       "...   ...             ...  ...        ...     ...         ...   \n",
       "1995    1               0   47          1  123525           0   \n",
       "1996    1               1   27          1  117744           1   \n",
       "1997    0               0   31          0   86400           0   \n",
       "1998    1               1   24          1   97968           0   \n",
       "1999    0               0   25          0   68416           0   \n",
       "\n",
       "      Settlement size  Component 1  Component 2  Component 3  \\\n",
       "0                   2     2.514746     0.834122     2.174806   \n",
       "1                   2     0.344935     0.598146    -2.211603   \n",
       "2                   0    -0.651063    -0.680093     2.280419   \n",
       "3                   1     1.714316    -0.579927     0.730731   \n",
       "4                   1     1.626745    -0.440496     1.244909   \n",
       "...               ...          ...          ...          ...   \n",
       "1995                0    -0.866034     0.298330     1.438958   \n",
       "1996                0    -1.114957     0.794727    -1.079871   \n",
       "1997                0    -1.452298    -2.235937     0.896571   \n",
       "1998                0    -2.241453     0.627108    -0.530456   \n",
       "1999                0    -1.866885    -2.454672     0.662622   \n",
       "\n",
       "      Segment K-means PCA  \n",
       "0                       3  \n",
       "1                       2  \n",
       "2                       0  \n",
       "3                       1  \n",
       "4                       1  \n",
       "...                   ...  \n",
       "1995                    0  \n",
       "1996                    2  \n",
       "1997                    0  \n",
       "1998                    2  \n",
       "1999                    0  \n",
       "\n",
       "[2000 rows x 11 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new data frame with the original features and add the PCA scores and assigned clusters.\n",
    "df_segm_pca_kmeans = pd.concat([df_segmentation.reset_index(drop = True), pd.DataFrame(scores_pca)], axis = 1)\n",
    "df_segm_pca_kmeans.columns.values[-3: ] = ['Component 1', 'Component 2', 'Component 3']\n",
    "# The last column we add contains the pca k-means clustering labels.\n",
    "df_segm_pca_kmeans['Segment K-means PCA'] = kmeans_pca.labels_\n",
    "df_segm_pca_kmeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "      <th>Component 1</th>\n",
       "      <th>Component 2</th>\n",
       "      <th>Component 3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Segment K-means PCA</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.307190</td>\n",
       "      <td>0.098039</td>\n",
       "      <td>35.383442</td>\n",
       "      <td>0.766885</td>\n",
       "      <td>93566.102397</td>\n",
       "      <td>0.248366</td>\n",
       "      <td>0.039216</td>\n",
       "      <td>-1.048838</td>\n",
       "      <td>-0.892116</td>\n",
       "      <td>1.010446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.027350</td>\n",
       "      <td>0.167521</td>\n",
       "      <td>35.700855</td>\n",
       "      <td>0.731624</td>\n",
       "      <td>141489.721368</td>\n",
       "      <td>1.266667</td>\n",
       "      <td>1.475214</td>\n",
       "      <td>1.367167</td>\n",
       "      <td>-1.050209</td>\n",
       "      <td>-0.247981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.900433</td>\n",
       "      <td>0.965368</td>\n",
       "      <td>28.913420</td>\n",
       "      <td>1.062049</td>\n",
       "      <td>107551.946609</td>\n",
       "      <td>0.676768</td>\n",
       "      <td>0.440115</td>\n",
       "      <td>-1.106918</td>\n",
       "      <td>0.706367</td>\n",
       "      <td>-0.778269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.505703</td>\n",
       "      <td>0.688213</td>\n",
       "      <td>55.722433</td>\n",
       "      <td>2.129278</td>\n",
       "      <td>158391.676806</td>\n",
       "      <td>1.129278</td>\n",
       "      <td>1.110266</td>\n",
       "      <td>1.706153</td>\n",
       "      <td>2.031716</td>\n",
       "      <td>0.838839</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Sex  Marital status        Age  Education  \\\n",
       "Segment K-means PCA                                                   \n",
       "0                    0.307190        0.098039  35.383442   0.766885   \n",
       "1                    0.027350        0.167521  35.700855   0.731624   \n",
       "2                    0.900433        0.965368  28.913420   1.062049   \n",
       "3                    0.505703        0.688213  55.722433   2.129278   \n",
       "\n",
       "                            Income  Occupation  Settlement size  Component 1  \\\n",
       "Segment K-means PCA                                                            \n",
       "0                     93566.102397    0.248366         0.039216    -1.048838   \n",
       "1                    141489.721368    1.266667         1.475214     1.367167   \n",
       "2                    107551.946609    0.676768         0.440115    -1.106918   \n",
       "3                    158391.676806    1.129278         1.110266     1.706153   \n",
       "\n",
       "                     Component 2  Component 3  \n",
       "Segment K-means PCA                            \n",
       "0                      -0.892116     1.010446  \n",
       "1                      -1.050209    -0.247981  \n",
       "2                       0.706367    -0.778269  \n",
       "3                       2.031716     0.838839  "
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the means by segments.\n",
    "df_segm_pca_kmeans_freq = df_segm_pca_kmeans.groupby(['Segment K-means PCA']).mean()\n",
    "df_segm_pca_kmeans_freq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "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>Sex</th>\n",
       "      <th>Marital status</th>\n",
       "      <th>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Income</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Settlement size</th>\n",
       "      <th>Component 1</th>\n",
       "      <th>Component 2</th>\n",
       "      <th>Component 3</th>\n",
       "      <th>N Obs</th>\n",
       "      <th>Prop Obs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Segment K-means PCA</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>fewer opportunities</th>\n",
       "      <td>0.307190</td>\n",
       "      <td>0.098039</td>\n",
       "      <td>35.383442</td>\n",
       "      <td>0.766885</td>\n",
       "      <td>93566.102397</td>\n",
       "      <td>0.248366</td>\n",
       "      <td>0.039216</td>\n",
       "      <td>-1.048838</td>\n",
       "      <td>-0.892116</td>\n",
       "      <td>1.010446</td>\n",
       "      <td>459</td>\n",
       "      <td>0.2295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>career focused</th>\n",
       "      <td>0.027350</td>\n",
       "      <td>0.167521</td>\n",
       "      <td>35.700855</td>\n",
       "      <td>0.731624</td>\n",
       "      <td>141489.721368</td>\n",
       "      <td>1.266667</td>\n",
       "      <td>1.475214</td>\n",
       "      <td>1.367167</td>\n",
       "      <td>-1.050209</td>\n",
       "      <td>-0.247981</td>\n",
       "      <td>585</td>\n",
       "      <td>0.2925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>standard</th>\n",
       "      <td>0.900433</td>\n",
       "      <td>0.965368</td>\n",
       "      <td>28.913420</td>\n",
       "      <td>1.062049</td>\n",
       "      <td>107551.946609</td>\n",
       "      <td>0.676768</td>\n",
       "      <td>0.440115</td>\n",
       "      <td>-1.106918</td>\n",
       "      <td>0.706367</td>\n",
       "      <td>-0.778269</td>\n",
       "      <td>693</td>\n",
       "      <td>0.3465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>well-off</th>\n",
       "      <td>0.505703</td>\n",
       "      <td>0.688213</td>\n",
       "      <td>55.722433</td>\n",
       "      <td>2.129278</td>\n",
       "      <td>158391.676806</td>\n",
       "      <td>1.129278</td>\n",
       "      <td>1.110266</td>\n",
       "      <td>1.706153</td>\n",
       "      <td>2.031716</td>\n",
       "      <td>0.838839</td>\n",
       "      <td>263</td>\n",
       "      <td>0.1315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Sex  Marital status        Age  Education  \\\n",
       "Segment K-means PCA                                                   \n",
       "fewer opportunities  0.307190        0.098039  35.383442   0.766885   \n",
       "career focused       0.027350        0.167521  35.700855   0.731624   \n",
       "standard             0.900433        0.965368  28.913420   1.062049   \n",
       "well-off             0.505703        0.688213  55.722433   2.129278   \n",
       "\n",
       "                            Income  Occupation  Settlement size  Component 1  \\\n",
       "Segment K-means PCA                                                            \n",
       "fewer opportunities   93566.102397    0.248366         0.039216    -1.048838   \n",
       "career focused       141489.721368    1.266667         1.475214     1.367167   \n",
       "standard             107551.946609    0.676768         0.440115    -1.106918   \n",
       "well-off             158391.676806    1.129278         1.110266     1.706153   \n",
       "\n",
       "                     Component 2  Component 3  N Obs  Prop Obs  \n",
       "Segment K-means PCA                                             \n",
       "fewer opportunities    -0.892116     1.010446    459    0.2295  \n",
       "career focused         -1.050209    -0.247981    585    0.2925  \n",
       "standard                0.706367    -0.778269    693    0.3465  \n",
       "well-off                2.031716     0.838839    263    0.1315  "
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the size of each cluster and its proportion to the entire data set.\n",
    "df_segm_pca_kmeans_freq['N Obs'] = df_segm_pca_kmeans[['Segment K-means PCA','Sex']].groupby(['Segment K-means PCA']).count()\n",
    "df_segm_pca_kmeans_freq['Prop Obs'] = df_segm_pca_kmeans_freq['N Obs'] / df_segm_pca_kmeans_freq['N Obs'].sum()\n",
    "df_segm_pca_kmeans_freq = df_segm_pca_kmeans_freq.rename({0:'fewer opportunities', \n",
    "                                                          1:'career focused',\n",
    "                                                          2:'standard', \n",
    "                                                          3:'well-off'})\n",
    "df_segm_pca_kmeans_freq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Label each cluster\n",
    "df_segm_pca_kmeans['Legend'] = df_segm_pca_kmeans['Segment K-means PCA'].map({2:'standard', \n",
    "                                                          1:'career focused',\n",
    "                                                          0:'fewer opportunities', \n",
    "                                                          3:'well-off'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot data by PCA components. \n",
    "# The Y axis is the first component, X axis is the second.\n",
    "x_axis = df_segm_pca_kmeans['Component 2']\n",
    "y_axis = df_segm_pca_kmeans['Component 1']\n",
    "plt.figure(figsize = (10, 8))\n",
    "sns.scatterplot(x_axis, y_axis, hue = df_segm_pca_kmeans['Legend'], palette = ['g', 'r', 'c', 'm'])\n",
    "plt.title('Clusters by PCA Components')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data export"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(scaler, open('scaler.pickle', 'wb'))\n",
    "pickle.dump(pca, open('pca.pickle', 'wb'))\n",
    "pickle.dump(kmeans_pca, open('kmeans_pca.pickle', 'wb'))"
   ]
  }
 ],
 "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": 4
}