ClusterAnalysisTelecom.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"/home/shiveshwar/Programs/Telecom/TelcomData.csv\",sep=\",\",index_col=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>State</th>\n",
       "      <th>VMail.Plan</th>\n",
       "      <th>International.Plan</th>\n",
       "      <th>Total.Day.Minutes</th>\n",
       "      <th>Total.Day.Calls</th>\n",
       "      <th>Total.Day.Charge</th>\n",
       "      <th>Total.Evening.Minutes</th>\n",
       "      <th>Total.Evening.Calls</th>\n",
       "      <th>Total.Evening.Charge</th>\n",
       "      <th>Total.Night.Minutes</th>\n",
       "      <th>Total.Night.Calls</th>\n",
       "      <th>Total.Night.Charge</th>\n",
       "      <th>Total.International.Minutes</th>\n",
       "      <th>Total.International.Calls</th>\n",
       "      <th>Total.International.Charge</th>\n",
       "      <th>Customer.Service.Calls</th>\n",
       "      <th>Number.VMail.Messages</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>OH</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>752.85</td>\n",
       "      <td>83</td>\n",
       "      <td>45.1710</td>\n",
       "      <td>1027.74</td>\n",
       "      <td>99</td>\n",
       "      <td>30.8322</td>\n",
       "      <td>851.61</td>\n",
       "      <td>85</td>\n",
       "      <td>17.0322</td>\n",
       "      <td>900.08</td>\n",
       "      <td>76</td>\n",
       "      <td>270.024</td>\n",
       "      <td>55</td>\n",
       "      <td>88</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>OK</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>862.92</td>\n",
       "      <td>84</td>\n",
       "      <td>51.7752</td>\n",
       "      <td>827.74</td>\n",
       "      <td>79</td>\n",
       "      <td>24.8322</td>\n",
       "      <td>932.64</td>\n",
       "      <td>86</td>\n",
       "      <td>18.6528</td>\n",
       "      <td>972.73</td>\n",
       "      <td>93</td>\n",
       "      <td>291.819</td>\n",
       "      <td>47</td>\n",
       "      <td>103</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>AL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>468.03</td>\n",
       "      <td>45</td>\n",
       "      <td>28.0818</td>\n",
       "      <td>588.86</td>\n",
       "      <td>57</td>\n",
       "      <td>17.6658</td>\n",
       "      <td>662.87</td>\n",
       "      <td>55</td>\n",
       "      <td>13.2574</td>\n",
       "      <td>513.69</td>\n",
       "      <td>62</td>\n",
       "      <td>154.107</td>\n",
       "      <td>33</td>\n",
       "      <td>64</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>MA</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>743.11</td>\n",
       "      <td>64</td>\n",
       "      <td>44.5866</td>\n",
       "      <td>582.09</td>\n",
       "      <td>46</td>\n",
       "      <td>17.4627</td>\n",
       "      <td>601.45</td>\n",
       "      <td>50</td>\n",
       "      <td>12.0290</td>\n",
       "      <td>699.86</td>\n",
       "      <td>55</td>\n",
       "      <td>209.958</td>\n",
       "      <td>37</td>\n",
       "      <td>60</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>MO</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>333.45</td>\n",
       "      <td>29</td>\n",
       "      <td>20.0070</td>\n",
       "      <td>439.42</td>\n",
       "      <td>42</td>\n",
       "      <td>13.1826</td>\n",
       "      <td>366.06</td>\n",
       "      <td>35</td>\n",
       "      <td>7.3212</td>\n",
       "      <td>367.30</td>\n",
       "      <td>34</td>\n",
       "      <td>110.190</td>\n",
       "      <td>22</td>\n",
       "      <td>34</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 State VMail.Plan International.Plan  Total.Day.Minutes  \\\n",
       "0           1    OH        Yes                Yes             752.85   \n",
       "1           2    OK         No                Yes             862.92   \n",
       "2           3    AL        Yes                Yes             468.03   \n",
       "3           4    MA        Yes                Yes             743.11   \n",
       "4           5    MO        Yes                 No             333.45   \n",
       "\n",
       "   Total.Day.Calls  Total.Day.Charge  Total.Evening.Minutes  \\\n",
       "0               83           45.1710                1027.74   \n",
       "1               84           51.7752                 827.74   \n",
       "2               45           28.0818                 588.86   \n",
       "3               64           44.5866                 582.09   \n",
       "4               29           20.0070                 439.42   \n",
       "\n",
       "   Total.Evening.Calls  Total.Evening.Charge  Total.Night.Minutes  \\\n",
       "0                   99               30.8322               851.61   \n",
       "1                   79               24.8322               932.64   \n",
       "2                   57               17.6658               662.87   \n",
       "3                   46               17.4627               601.45   \n",
       "4                   42               13.1826               366.06   \n",
       "\n",
       "   Total.Night.Calls  Total.Night.Charge  Total.International.Minutes  \\\n",
       "0                 85             17.0322                       900.08   \n",
       "1                 86             18.6528                       972.73   \n",
       "2                 55             13.2574                       513.69   \n",
       "3                 50             12.0290                       699.86   \n",
       "4                 35              7.3212                       367.30   \n",
       "\n",
       "   Total.International.Calls  Total.International.Charge  \\\n",
       "0                         76                     270.024   \n",
       "1                         93                     291.819   \n",
       "2                         62                     154.107   \n",
       "3                         55                     209.958   \n",
       "4                         34                     110.190   \n",
       "\n",
       "   Customer.Service.Calls  Number.VMail.Messages Churn  \n",
       "0                      55                     88    No  \n",
       "1                      47                    103    No  \n",
       "2                      33                     64   Yes  \n",
       "3                      37                     60    No  \n",
       "4                      22                     34    No  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "telecomdata = data.iloc[:,4:14]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "telecomdata_scale = preprocessing.scale(telecomdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "telecom_df = pd.DataFrame(telecomdata_scale)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.651866</td>\n",
       "      <td>5.039731</td>\n",
       "      <td>4.651866</td>\n",
       "      <td>6.890842</td>\n",
       "      <td>6.301794</td>\n",
       "      <td>6.890842</td>\n",
       "      <td>5.429648</td>\n",
       "      <td>5.162620</td>\n",
       "      <td>5.429648</td>\n",
       "      <td>5.753073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.553468</td>\n",
       "      <td>5.119161</td>\n",
       "      <td>5.553468</td>\n",
       "      <td>5.254667</td>\n",
       "      <td>4.715588</td>\n",
       "      <td>5.254667</td>\n",
       "      <td>6.089982</td>\n",
       "      <td>5.241514</td>\n",
       "      <td>6.089982</td>\n",
       "      <td>6.338132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.318858</td>\n",
       "      <td>2.021389</td>\n",
       "      <td>2.318858</td>\n",
       "      <td>3.300420</td>\n",
       "      <td>2.970762</td>\n",
       "      <td>3.300420</td>\n",
       "      <td>3.891557</td>\n",
       "      <td>2.795783</td>\n",
       "      <td>3.891557</td>\n",
       "      <td>2.641427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.572084</td>\n",
       "      <td>3.530560</td>\n",
       "      <td>4.572084</td>\n",
       "      <td>3.245035</td>\n",
       "      <td>2.098348</td>\n",
       "      <td>3.245035</td>\n",
       "      <td>3.391029</td>\n",
       "      <td>2.401311</td>\n",
       "      <td>3.391029</td>\n",
       "      <td>4.140677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.216491</td>\n",
       "      <td>0.750508</td>\n",
       "      <td>1.216491</td>\n",
       "      <td>2.077870</td>\n",
       "      <td>1.781107</td>\n",
       "      <td>2.077870</td>\n",
       "      <td>1.472775</td>\n",
       "      <td>1.217892</td>\n",
       "      <td>1.472775</td>\n",
       "      <td>1.462531</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6  \\\n",
       "0  4.651866  5.039731  4.651866  6.890842  6.301794  6.890842  5.429648   \n",
       "1  5.553468  5.119161  5.553468  5.254667  4.715588  5.254667  6.089982   \n",
       "2  2.318858  2.021389  2.318858  3.300420  2.970762  3.300420  3.891557   \n",
       "3  4.572084  3.530560  4.572084  3.245035  2.098348  3.245035  3.391029   \n",
       "4  1.216491  0.750508  1.216491  2.077870  1.781107  2.077870  1.472775   \n",
       "\n",
       "          7         8         9  \n",
       "0  5.162620  5.429648  5.753073  \n",
       "1  5.241514  6.089982  6.338132  \n",
       "2  2.795783  3.891557  2.641427  \n",
       "3  2.401311  3.391029  4.140677  \n",
       "4  1.217892  1.472775  1.462531  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "telecom_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# k-means cluster analysis for 1-9 clusters\n",
    "from scipy.spatial.distance import cdist\n",
    "from sklearn.cluster import KMeans\n",
    "import matplotlib.pylab as plt\n",
    "\n",
    "clusters=range(1,10)\n",
    "meandist=[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for k in clusters:\n",
    "    model=KMeans(n_clusters=k)\n",
    "    model.fit(telecomdata_scale)\n",
    "    meandist.append(sum(np.min(cdist(telecom_df, model.cluster_centers_, 'euclidean'), axis=1)) \n",
    "    / telecomdata_scale.shape[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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KXLqglhKN1ZOfjU1yZGZmZvmtjhONer0D8I9//IP+/fs3smvrNmLECC6++OK0wyg7X2d1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\nXUw2brwROnRIOyozM2tINQ1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1BKYDQ0IIY9OOp9wkzQB+GUK4Lu1YSklSF2AccRHB3wAv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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f122d453518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot to decide the number of cluster\n",
    "\n",
    "plt.plot(clusters, meandist)\n",
    "plt.xlabel('Number of clusters')\n",
    "plt.ylabel('Average distance')\n",
    "plt.title('Selecting k with the Elbow Method')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we will decide to form cluster 3 Cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(copy_x=True, init='k-means++', max_iter=300, n_clusters=3, n_init=10,\n",
       "    n_jobs=1, precompute_distances='auto', random_state=None, tol=0.0001,\n",
       "    verbose=0)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Final Model\n",
    "\n",
    "model_final = KMeans(n_clusters=3)\n",
    "model_final.fit(telecom_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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uN2VLl6ZLly5p665cuZJvv/uOzj4f7YF6QC//30XATiAZWAn86nIxcNAgIiIi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\nI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1yJTVXpibAaVhxMygFEuNoVEZamINoRQ1ZYro+BhrjLS/oyQzhq0q/fisyPu+nbhen7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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f122ac10198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot Cluster\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "pca_2 = PCA(2)\n",
    "plot_columns = pca_2.fit_transform(telecomdata_scale)\n",
    "plt.scatter(x=plot_columns[:,0], y=plot_columns[:,1], c=model_final.labels_)\n",
    "plt.xlabel('PC 1')\n",
    "plt.ylabel('PC 2')\n",
    "plt.title('Scatterplot of Principal for 3 Clusters')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Assigning the cluster to the dataset\n",
    "telecomdata['cluster'] = model_final.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f122d48e0b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "telecomdata['cluster'].hist()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total.Day.Minutes</th>\n",
       "      <th>Total.Day.Calls</th>\n",
       "      <th>Total.Day.Charge</th>\n",
       "      <th>Total.Evening.Minutes</th>\n",
       "      <th>Total.Evening.Calls</th>\n",
       "      <th>Total.Evening.Charge</th>\n",
       "      <th>Total.Night.Minutes</th>\n",
       "      <th>Total.Night.Calls</th>\n",
       "      <th>Total.Night.Charge</th>\n",
       "      <th>Total.International.Minutes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster</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>91.927493</td>\n",
       "      <td>9.814570</td>\n",
       "      <td>5.515650</td>\n",
       "      <td>91.984499</td>\n",
       "      <td>9.786660</td>\n",
       "      <td>2.759535</td>\n",
       "      <td>91.762271</td>\n",
       "      <td>9.789026</td>\n",
       "      <td>1.835245</td>\n",
       "      <td>95.112351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>221.407356</td>\n",
       "      <td>23.387731</td>\n",
       "      <td>13.284441</td>\n",
       "      <td>223.095331</td>\n",
       "      <td>23.470518</td>\n",
       "      <td>6.692860</td>\n",
       "      <td>222.200339</td>\n",
       "      <td>23.435378</td>\n",
       "      <td>4.444007</td>\n",
       "      <td>220.731132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>393.551402</td>\n",
       "      <td>41.342065</td>\n",
       "      <td>23.613084</td>\n",
       "      <td>392.361217</td>\n",
       "      <td>41.158706</td>\n",
       "      <td>11.770837</td>\n",
       "      <td>394.758428</td>\n",
       "      <td>41.382126</td>\n",
       "      <td>7.895169</td>\n",
       "      <td>390.073852</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Total.Day.Minutes  Total.Day.Calls  Total.Day.Charge  \\\n",
       "cluster                                                         \n",
       "0                91.927493         9.814570          5.515650   \n",
       "1               221.407356        23.387731         13.284441   \n",
       "2               393.551402        41.342065         23.613084   \n",
       "\n",
       "         Total.Evening.Minutes  Total.Evening.Calls  Total.Evening.Charge  \\\n",
       "cluster                                                                     \n",
       "0                    91.984499             9.786660              2.759535   \n",
       "1                   223.095331            23.470518              6.692860   \n",
       "2                   392.361217            41.158706             11.770837   \n",
       "\n",
       "         Total.Night.Minutes  Total.Night.Calls  Total.Night.Charge  \\\n",
       "cluster                                                               \n",
       "0                  91.762271           9.789026            1.835245   \n",
       "1                 222.200339          23.435378            4.444007   \n",
       "2                 394.758428          41.382126            7.895169   \n",
       "\n",
       "         Total.International.Minutes  \n",
       "cluster                               \n",
       "0                          95.112351  \n",
       "1                         220.731132  \n",
       "2                         390.073852  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cluster Chareteristics\n",
    "telecomdata.groupby(\"cluster\").mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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