MVP_Kmeans_byStateYes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "\n",
    "from sklearn.preprocessing import scale\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder, StandardScaler, MinMaxScaler, RobustScaler\n",
    "\n",
    "from scipy.cluster import hierarchy\n",
    "from scipy.cluster.hierarchy import linkage, dendrogram\n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [],
   "source": [
    "auto=pd.read_csv('./auto_insurance/train.csv').drop('id', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Driving_License</th>\n",
       "      <th>Region_Code</th>\n",
       "      <th>Previously_Insured</th>\n",
       "      <th>Vehicle_Age</th>\n",
       "      <th>Vehicle_Damage</th>\n",
       "      <th>Annual_Premium</th>\n",
       "      <th>Policy_Sales_Channel</th>\n",
       "      <th>Vintage</th>\n",
       "      <th>Response</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>44</td>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>&gt; 2 Years</td>\n",
       "      <td>Yes</td>\n",
       "      <td>40454.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>217</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1-2 Year</td>\n",
       "      <td>No</td>\n",
       "      <td>33536.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>183</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Male</td>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>&gt; 2 Years</td>\n",
       "      <td>Yes</td>\n",
       "      <td>38294.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Male</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt; 1 Year</td>\n",
       "      <td>No</td>\n",
       "      <td>28619.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>203</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt; 1 Year</td>\n",
       "      <td>No</td>\n",
       "      <td>27496.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Age  Driving_License  Region_Code  Previously_Insured Vehicle_Age  \\\n",
       "0    Male   44                1         28.0                   0   > 2 Years   \n",
       "1    Male   76                1          3.0                   0    1-2 Year   \n",
       "2    Male   47                1         28.0                   0   > 2 Years   \n",
       "3    Male   21                1         11.0                   1    < 1 Year   \n",
       "4  Female   29                1         41.0                   1    < 1 Year   \n",
       "\n",
       "  Vehicle_Damage  Annual_Premium  Policy_Sales_Channel  Vintage  Response  \n",
       "0            Yes         40454.0                  26.0      217         1  \n",
       "1             No         33536.0                  26.0      183         0  \n",
       "2            Yes         38294.0                  26.0       27         1  \n",
       "3             No         28619.0                 152.0      203         0  \n",
       "4             No         27496.0                 152.0       39         0  "
      ]
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auto.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(381109, 11)"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auto.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gender                  0\n",
       "Age                     0\n",
       "Driving_License         0\n",
       "Region_Code             0\n",
       "Previously_Insured      0\n",
       "Vehicle_Age             0\n",
       "Vehicle_Damage          0\n",
       "Annual_Premium          0\n",
       "Policy_Sales_Channel    0\n",
       "Vintage                 0\n",
       "Response                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auto.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert categorical to numerical "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "\n",
    "auto['Gender'] = auto['Gender'].map( {'Female': 0, 'Male': 1} ).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "auto['Vehicle_Damage'] = auto['Vehicle_Damage'].map( {'Yes': 1, 'No': 0} ).astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assigned dummies "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [],
   "source": [
    "auto=pd.get_dummies(auto, columns=['Vehicle_Age'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Driving_License</th>\n",
       "      <th>Region_Code</th>\n",
       "      <th>Previously_Insured</th>\n",
       "      <th>Vehicle_Damage</th>\n",
       "      <th>Annual_Premium</th>\n",
       "      <th>Policy_Sales_Channel</th>\n",
       "      <th>Vintage</th>\n",
       "      <th>Response</th>\n",
       "      <th>Vehicle_Age_1-2 Year</th>\n",
       "      <th>Vehicle_Age_&lt; 1 Year</th>\n",
       "      <th>Vehicle_Age_&gt; 2 Years</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>44</td>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>40454.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>217</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <th>1</th>\n",
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       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>33536.0</td>\n",
       "      <td>26.0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>38294.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>28619.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>203</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>27496.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Age  Driving_License  Region_Code  Previously_Insured  \\\n",
       "0       1   44                1         28.0                   0   \n",
       "1       1   76                1          3.0                   0   \n",
       "2       1   47                1         28.0                   0   \n",
       "3       1   21                1         11.0                   1   \n",
       "4       0   29                1         41.0                   1   \n",
       "\n",
       "   Vehicle_Damage  Annual_Premium  Policy_Sales_Channel  Vintage  Response  \\\n",
       "0               1         40454.0                  26.0      217         1   \n",
       "1               0         33536.0                  26.0      183         0   \n",
       "2               1         38294.0                  26.0       27         1   \n",
       "3               0         28619.0                 152.0      203         0   \n",
       "4               0         27496.0                 152.0       39         0   \n",
       "\n",
       "   Vehicle_Age_1-2 Year  Vehicle_Age_< 1 Year  Vehicle_Age_> 2 Years  \n",
       "0                     0                     0                      1  \n",
       "1                     1                     0                      0  \n",
       "2                     0                     0                      1  \n",
       "3                     0                     1                      0  \n",
       "4                     0                     1                      0  "
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auto.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "auto.hist(figsize=(10, 10));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(381109, 13)"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auto.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Outliers detection and removal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing (statistical) outliers for Annual_Premium\n",
    "cols = [ 'Age','Annual_Premium'] # one or more\n",
    "\n",
    "Q1 = auto[cols].quantile(0.25)\n",
    "Q3 = auto[cols].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "\n",
    "auto = auto[~((auto[cols] < (Q1 - 1.5 * IQR)) |(auto[cols] > (Q3 + 1.5 * IQR))).any(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "attributes = ['Age','Annual_Premium']\n",
    "plt.rcParams['figure.figsize'] = [12,8]\n",
    "sns.boxplot(data = X[attributes], orient=\"v\", palette=\"Set2\" ,whis=1.5,saturation=1, width=0.7)\n",
    "plt.title(\"Outliers Variable Distribution\", fontsize = 14, fontweight = 'bold')\n",
    "plt.ylabel(\"Range\", fontweight = 'bold')\n",
    "plt.xlabel(\"Attributes\", fontweight = 'bold');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing (statistical) outliers for Annual_Premium\n",
    "cols = [ 'Annual_Premium'] # one or more\n",
    "\n",
    "Q1 = auto[cols].quantile(0.25)\n",
    "Q3 = auto[cols].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "\n",
    "auto = auto[~((auto[cols] < (Q1 - 1.5 * IQR)) |(auto[cols] > (Q3 + 1.5 * IQR))).any(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "attributes = ['Age','Annual_Premium','Vintage']\n",
    "plt.rcParams['figure.figsize'] = [12,8]\n",
    "sns.boxplot(data = auto[attributes], orient=\"v\", palette=\"Set2\" ,whis=1.5,saturation=1, width=0.7)\n",
    "plt.title(\"Outliers Variable Distribution\", fontsize = 14, fontweight = 'bold')\n",
    "plt.ylabel(\"Range\", fontweight = 'bold')\n",
    "plt.xlabel(\"Attributes\", fontweight = 'bold');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [],
   "source": [
    "auto=auto[auto.Response==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(53, 13)"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "autoYes=auto.groupby('Region_Code',as_index=False).agg('mean')\n",
    "autoYes.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=autoYes.drop(['Driving_License', 'Response'], axis=1)\n",
    "labels=X.Region_Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((53, 11), (53,))"
      ]
     },
     "execution_count": 276,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape, labels.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scaling with StandardScaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(53, 11)"
      ]
     },
     "execution_count": 277,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scale=StandardScaler()\n",
    "scaled_X=scale.fit_transform(X)\n",
    "scaled_X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3241698592991916"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyclustertend import hopkins\n",
    "hopkins(scaled_X,50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "from sklearn.metrics import silhouette_score, silhouette_samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc=[]\n",
    "K=range(2,10)\n",
    "for k in K:\n",
    "    kmeans=KMeans(n_clusters=k).fit(scaled_X)\n",
    "    score = silhouette_score(scaled_X, kmeans.labels_)\n",
    "    sc.append(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "\n",
    "ax.plot(range(2, 10), sc, color='blue')\n",
    "\n",
    "ax.set_title('Silhouette Coefficients for K_Means')\n",
    "ax.set_xlabel('Number of Clusters')\n",
    "ax.set_ylabel('Silhouette Coefficient')\n",
    "#plt.savefig('./images/Silhouette_score__Yes_customers',dsi=100);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 864x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from yellowbrick.cluster import KElbowVisualizer\n",
    "kmeans=KMeans(random_state=42)\n",
    "visual=KElbowVisualizer(kmeans, k=(1,10))\n",
    "visual.fit(scaled_X)\n",
    "visual.poof()\n",
    "#plt.savefig('./images/Yellowbrick_score__YES_customers',dsi=100);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(n_clusters=3, n_init=20)"
      ]
     },
     "execution_count": 310,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "km3 = KMeans(n_clusters=3, n_init=20)\n",
    "km3.fit(scaled_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, 2, 2, 0, 0, 2, 2, 2, 0, 2, 0, 0, 0, 0, 0, 2, 2, 2, 1, 0,\n",
       "       1, 2, 2, 0, 2, 0, 2, 2, 0, 2, 0, 2, 0, 2, 0, 0, 2, 2, 2, 2, 1, 2,\n",
       "       0, 2, 2, 2, 1, 0, 2, 1, 1], dtype=int32)"
      ]
     },
     "execution_count": 311,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "km3.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(53,)"
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b=pd.Series(km3.labels_)\n",
    "b.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.22708184, -0.41442507, -1.03025014,  0.38919304, -0.70340946,\n",
       "         0.11667182,  0.91798132,  0.10823699, -1.03213408,  1.11232124,\n",
       "        -0.61494415],\n",
       "       [ 0.22880216,  1.22183649,  1.28324659, -0.19065234,  0.78133605,\n",
       "        -1.29409302, -1.42090845,  1.09935153,  0.35607769, -1.0074578 ,\n",
       "         1.73875487],\n",
       "       [ 0.09554376, -0.0731006 ,  0.35803   , -0.22574804,  0.2736189 ,\n",
       "         0.31292229, -0.2336299 , -0.41735828,  0.64468946, -0.50286312,\n",
       "        -0.08561923]])"
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "km3.cluster_centers_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [],
   "source": [
    "X['ClusterID']=b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "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>Region_Code</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Previously_Insured</th>\n",
       "      <th>Vehicle_Damage</th>\n",
       "      <th>Annual_Premium</th>\n",
       "      <th>Policy_Sales_Channel</th>\n",
       "      <th>Vintage</th>\n",
       "      <th>Vehicle_Age_1-2 Year</th>\n",
       "      <th>Vehicle_Age_&lt; 1 Year</th>\n",
       "      <th>Vehicle_Age_&gt; 2 Years</th>\n",
       "      <th>ClusterID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.703488</td>\n",
       "      <td>49.296512</td>\n",
       "      <td>0.005814</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4159.738372</td>\n",
       "      <td>60.186047</td>\n",
       "      <td>157.924419</td>\n",
       "      <td>0.732558</td>\n",
       "      <td>0.017442</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.623853</td>\n",
       "      <td>44.779817</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.990826</td>\n",
       "      <td>3131.376147</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>157.889908</td>\n",
       "      <td>0.788991</td>\n",
       "      <td>0.110092</td>\n",
       "      <td>0.100917</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.651568</td>\n",
       "      <td>37.498258</td>\n",
       "      <td>0.020906</td>\n",
       "      <td>0.972125</td>\n",
       "      <td>25570.641115</td>\n",
       "      <td>117.616725</td>\n",
       "      <td>146.425087</td>\n",
       "      <td>0.630662</td>\n",
       "      <td>0.310105</td>\n",
       "      <td>0.059233</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.610213</td>\n",
       "      <td>40.331915</td>\n",
       "      <td>0.006809</td>\n",
       "      <td>0.971064</td>\n",
       "      <td>22951.654468</td>\n",
       "      <td>110.209362</td>\n",
       "      <td>154.451064</td>\n",
       "      <td>0.741277</td>\n",
       "      <td>0.211915</td>\n",
       "      <td>0.046809</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0.656028</td>\n",
       "      <td>40.471631</td>\n",
       "      <td>0.003546</td>\n",
       "      <td>0.975177</td>\n",
       "      <td>23448.751773</td>\n",
       "      <td>113.780142</td>\n",
       "      <td>155.996454</td>\n",
       "      <td>0.794326</td>\n",
       "      <td>0.152482</td>\n",
       "      <td>0.053191</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Region_Code    Gender        Age  Previously_Insured  Vehicle_Damage  \\\n",
       "0          0.0  0.703488  49.296512            0.005814        1.000000   \n",
       "1          1.0  0.623853  44.779817            0.009174        0.990826   \n",
       "2          2.0  0.651568  37.498258            0.020906        0.972125   \n",
       "3          3.0  0.610213  40.331915            0.006809        0.971064   \n",
       "4          4.0  0.656028  40.471631            0.003546        0.975177   \n",
       "\n",
       "   Annual_Premium  Policy_Sales_Channel     Vintage  Vehicle_Age_1-2 Year  \\\n",
       "0     4159.738372             60.186047  157.924419              0.732558   \n",
       "1     3131.376147             94.000000  157.889908              0.788991   \n",
       "2    25570.641115            117.616725  146.425087              0.630662   \n",
       "3    22951.654468            110.209362  154.451064              0.741277   \n",
       "4    23448.751773            113.780142  155.996454              0.794326   \n",
       "\n",
       "   Vehicle_Age_< 1 Year  Vehicle_Age_> 2 Years  ClusterID  \n",
       "0              0.017442               0.250000          2  \n",
       "1              0.110092               0.100917          2  \n",
       "2              0.310105               0.059233          1  \n",
       "3              0.211915               0.046809          0  \n",
       "4              0.152482               0.053191          0  "
      ]
     },
     "execution_count": 287,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "X['Region_Code'] = X['Region_Code'].replace(to_replace=[8,15,28,46,41,0,1,2,3,4,5,6,7,9,10,11,12,13,14,16,17,18,19,20,21,22,23,24,25,26,27,29,30,31,32,33,34,35,36,37,38,39,40,42,43,44,45,47,48,49,50,51,52],\n",
    "                                                                                value=['Columbia','Iowa','Nevada','Virginia','SDakota','Alabama','Alaska','Arizona','Arkanzas','California','Colorado','Connecticut','Delaware','Florida',\n",
    "                                                                                'Georgia', 'Hawaii', 'Idaho','Illinois','Indiana','Kansas','Kentucky', 'Luisiana','Maine','Maryland','Massachusetts','Michigan',\n",
    "                                                                                    'Minnesota','Mississippi', 'Missouri','Monatana','Nebraska','New Hampshire','New Jersey','New Mexico','New York','North Carolina','North Dakota','Ohio',\n",
    "                                                                                     'Oklahoma','Oregon','Pennsylvania', 'Rhode Island','South Carolina','Tennessee','Texas','Utah','Vermont','Washington','West Virginia','Wisconsin','Wyoming',\n",
    "                                                                                      'Puerto Rico', 'D.C.'])\n",
    "\n",
    "\n",
    "# X.rename({8:'W.DC', 15: 'Iowa', 0:'Alabama', 28:'Nevada', 46:'Virginia',41:'SDakota',1:'Alaska',2:'Arizona',3:'Arkanzas',4:'California',5:'Colorado',6:'Connecticut',7:'Delaware', 9:'Florida',\n",
    "#          10:'Georgia',11: 'Hawaii', 12:'Idaho',13:'Illinois',14:'Indiana',16:'Kansas',17:'Kentucky',18:'Luisiana',19:'Maine',20:'Maryland',21:'Massachusetts',22:'Michigan',23:'Minnesota',24:'Mississippi',25:'Missouri',26:'Monatana',27:'Nebraska',\n",
    "#          29:'New Hampshire',30:'New Jersey',31:'New Mexico',32:'New York',33:'North Carolina',34:'North Dakota',35:'Ohio',36:'Oklahoma',37:'Oregon',38:'Pennsylvania', 39:'Rhode Island',40:'South Carolina',\n",
    "#          42:'Tennessee',43:'Texas',44:'Utah',45:'Vermont',47:'Washington',48:'West Virginia',49:'Wisconsin',50:'Wyoming', 51:'Puerto Rico', 52:'D.C.'}, axis='columns',inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [],
   "source": [
    "def without_hue(plot, feature):\n",
    "    total = len(feature)\n",
    "    for p in ax.patches:\n",
    "        percentage = '{:.1f}%'.format(100 * p.get_height()/total)\n",
    "        x = p.get_x() + p.get_width() / 2 - 0.05\n",
    "        y = p.get_y() + p.get_height()\n",
    "        ax.annotate(percentage, (x, y), size = 12)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=X.ClusterID.value_counts().plot(kind='bar')\n",
    "#plt.savefig('./images/Cluster_proportion__YES_customers',dsi=100);\n",
    "plt.xticks(size=12)\n",
    "plt.yticks(size=12)\n",
    "plt.title('Clusters proportion')\n",
    "#plt.savefig('./images/Cluster_proportion__YES_customers',dsi=100);\n",
    "without_hue(ax, X.ClusterID)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='Age', y='Vintage', hue='ClusterID', data=X, palette='Set1');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='Age', y='Vehicle_Age_1-2 Year', hue='ClusterID', data=X, palette='Set1');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='Age',y='Annual_Premium', hue='ClusterID', data=X, palette='Set1');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = X[X.ClusterID == 0]\n",
    "sns.distplot(df['Age'],  kde=False, label='Cluster 0')\n",
    "\n",
    "df = X[X.ClusterID==1]\n",
    "sns.distplot(df['Age'],kde=False, label='Cluster 1')\n",
    "\n",
    "df = X[X.ClusterID==2]\n",
    "sns.distplot(df['Age'],kde=False, label='Cluster 2')\n",
    "\n",
    "# Plot formatting\n",
    "plt.legend(prop={'size': 12})\n",
    "plt.title('Age distribution')\n",
    "plt.xlabel('Age ')\n",
    "plt.ylabel('Count');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = X[X.ClusterID == 0]\n",
    "sns.distplot(df['Vintage'],  kde=False, label='Cluster 0')\n",
    "\n",
    "df = X[X.ClusterID==1]\n",
    "sns.distplot(df['Vintage'],kde=False, label='Cluster 1')\n",
    "\n",
    "df = X[X.ClusterID==2]\n",
    "sns.distplot(df['Vintage'],kde=False, label='Cluster 2')\n",
    "\n",
    "# Plot formatting\n",
    "plt.legend(prop={'size': 12})\n",
    "plt.title('Vintage distribution')\n",
    "plt.xlabel('Days ')\n",
    "plt.ylabel('Count');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = X[X.ClusterID == 0]\n",
    "sns.distplot(df['Annual_Premium'],  kde=False, label='Cluster 0')\n",
    "\n",
    "df = X[X.ClusterID==1]\n",
    "sns.distplot(df['Annual_Premium'],kde=False, label='Cluster 1')\n",
    "\n",
    "df = X[X.ClusterID==2]\n",
    "sns.distplot(df['Annual_Premium'],kde=False, label='Cluster 2')\n",
    "\n",
    "# Plot formatting\n",
    "plt.legend(prop={'size': 12})\n",
    "plt.title('Annual Premium distribution')\n",
    "plt.xlabel('Annual Premium ')\n",
    "plt.ylabel('Count');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = X[X.ClusterID == 0]\n",
    "sns.distplot(df['Vehicle_Age_1-2 Year'],  kde=False, label='Cluster 0')\n",
    "\n",
    "df = X[X.ClusterID==1]\n",
    "sns.distplot(df['Vehicle_Age_1-2 Year'],kde=False, label='Cluster 1')\n",
    "\n",
    "df = X[X.ClusterID==2]\n",
    "sns.distplot(df['Vehicle_Age_1-2 Year'],kde=False, label='Cluster 2')\n",
    "\n",
    "# Plot formatting\n",
    "plt.legend(prop={'size': 12})\n",
    "plt.title('Vehicle_Age_1-2 Year distribution')\n",
    "plt.xlabel('Vehicle_Age_1-2 Year ')\n",
    "plt.ylabel('Count');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2         Arizona\n",
       "5        Colorado\n",
       "6     Connecticut\n",
       "10        Georgia\n",
       "12          Idaho\n",
       "Name: Region_Code, dtype: object"
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#cluster_0=X[X['ClusterID'] ==0]\n",
    "X[X['ClusterID'] ==0]['Region_Code'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3      Arkanzas\n",
       "4    California\n",
       "7      Delaware\n",
       "8      Columbia\n",
       "9       Florida\n",
       "Name: Region_Code, dtype: object"
      ]
     },
     "execution_count": 264,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X[X['ClusterID'] ==1]['Region_Code'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           Alabama\n",
       "1            Alaska\n",
       "20         Maryland\n",
       "31       New Mexico\n",
       "48    West Virginia\n",
       "Name: Region_Code, dtype: object"
      ]
     },
     "execution_count": 266,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X[X['ClusterID'] ==2]['Region_Code'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region_Code</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Previously_Insured</th>\n",
       "      <th>Vehicle_Damage</th>\n",
       "      <th>Annual_Premium</th>\n",
       "      <th>Policy_Sales_Channel</th>\n",
       "      <th>Vehicle_Age_1-2 Year</th>\n",
       "      <th>Vehicle_Age_&lt; 1 Year</th>\n",
       "      <th>Vehicle_Age_&gt; 2 Years</th>\n",
       "      <th>ClusterID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>0.703488</td>\n",
       "      <td>49.296512</td>\n",
       "      <td>0.005814</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4159.738372</td>\n",
       "      <td>60.186047</td>\n",
       "      <td>0.732558</td>\n",
       "      <td>0.017442</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alaska</td>\n",
       "      <td>0.623853</td>\n",
       "      <td>44.779817</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.990826</td>\n",
       "      <td>3131.376147</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>0.788991</td>\n",
       "      <td>0.110092</td>\n",
       "      <td>0.100917</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>0.651568</td>\n",
       "      <td>37.498258</td>\n",
       "      <td>0.020906</td>\n",
       "      <td>0.972125</td>\n",
       "      <td>25570.641115</td>\n",
       "      <td>117.616725</td>\n",
       "      <td>0.630662</td>\n",
       "      <td>0.310105</td>\n",
       "      <td>0.059233</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Arkanzas</td>\n",
       "      <td>0.610213</td>\n",
       "      <td>40.331915</td>\n",
       "      <td>0.006809</td>\n",
       "      <td>0.971064</td>\n",
       "      <td>22951.654468</td>\n",
       "      <td>110.209362</td>\n",
       "      <td>0.741277</td>\n",
       "      <td>0.211915</td>\n",
       "      <td>0.046809</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>California</td>\n",
       "      <td>0.656028</td>\n",
       "      <td>40.471631</td>\n",
       "      <td>0.003546</td>\n",
       "      <td>0.975177</td>\n",
       "      <td>23448.751773</td>\n",
       "      <td>113.780142</td>\n",
       "      <td>0.794326</td>\n",
       "      <td>0.152482</td>\n",
       "      <td>0.053191</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Region_Code    Gender        Age  Previously_Insured  Vehicle_Damage  \\\n",
       "0     Alabama  0.703488  49.296512            0.005814        1.000000   \n",
       "1      Alaska  0.623853  44.779817            0.009174        0.990826   \n",
       "2     Arizona  0.651568  37.498258            0.020906        0.972125   \n",
       "3    Arkanzas  0.610213  40.331915            0.006809        0.971064   \n",
       "4  California  0.656028  40.471631            0.003546        0.975177   \n",
       "\n",
       "   Annual_Premium  Policy_Sales_Channel  Vehicle_Age_1-2 Year  \\\n",
       "0     4159.738372             60.186047              0.732558   \n",
       "1     3131.376147             94.000000              0.788991   \n",
       "2    25570.641115            117.616725              0.630662   \n",
       "3    22951.654468            110.209362              0.741277   \n",
       "4    23448.751773            113.780142              0.794326   \n",
       "\n",
       "   Vehicle_Age_< 1 Year  Vehicle_Age_> 2 Years  ClusterID  \n",
       "0              0.017442               0.250000          2  \n",
       "1              0.110092               0.100917          2  \n",
       "2              0.310105               0.059233          0  \n",
       "3              0.211915               0.046809          1  \n",
       "4              0.152482               0.053191          1  "
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hierarcial clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1440x1440 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1,ax2,ax3) = plt.subplots(3,1, figsize=(20,20))\n",
    "\n",
    "for linkage, cluster, ax in zip([hierarchy.complete(scaled_X), hierarchy.average(scaled_X),hierarchy.ward(scaled_X)], ['c1','c2','c3'],\n",
    "                                [ax1,ax2,ax3]):\n",
    "    cluster = hierarchy.dendrogram(linkage,ax=ax, color_threshold=0)\n",
    "\n",
    "ax1.set_title('Complete Linkage')\n",
    "ax2.set_title('Average Linkage')\n",
    "ax3.set_title('Ward');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,15))\n",
    "cut = hierarchy.dendrogram(hierarchy.ward(scaled_X),\n",
    "                            orientation='right', color_threshold=40, leaf_font_size=10)\n",
    "plt.vlines(10,0,plt.gca().yaxis.get_data_interval()[1], colors='r', linestyles='dashed')\n",
    "#plt.savefig('./images/ward_dendogram___Yes customers',dsi=100);"
   ]
  }
 ],
 "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}