Chapter 8 - Unsup. Learning - Clustering/Clustering-MasterTemplate.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "83708667-4fdc-1563-7b3a-06b6575d2865"
   },
   "source": [
    "\n",
    "\n",
    "# Clustering-Master Template\n",
    "\n",
    "This is a master template for implementing and working on several clustering techniques. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Content"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* [1. Introduction](#0)\n",
    "* [2. Getting Started - Load Libraries and Dataset](#1)\n",
    "    * [2.1. Load Libraries](#1.1)    \n",
    "    * [2.2. Load Dataset](#1.2)\n",
    "* [3. Exploratory Data Analysis](#2)\n",
    "    * [3.1 Descriptive Statistics](#2.1)    \n",
    "    * [3.2. Data Visualisation](#2.2)\n",
    "* [4. Data Preparation](#3)\n",
    "    * [4.1 Data Cleaning](#3.1)\n",
    "    * [4.3.Data Transformation](#3.2)  \n",
    "* [5.Evaluate Algorithms and Models](#5)        \n",
    "    * [5.1. k-Means Clustering](#5.1)\n",
    "        * [5.1.1 Finding right number of clusters](#5.1.1)\n",
    "    * [5.2. Hierarchial Clustering (Agglomerative Clustering)](#5.2)\n",
    "        * [5.2.1 Visualising the hierarchy](#5.2.1) \n",
    "    * [5.3. Affinity Propagation Clustering](#5.3)\n",
    "        * [5.3.1 Visualising the cluster](#5.2.1) \n",
    "    * [5.4. DBSCAN Clustering](#5.4)\n",
    "        * [5.3.1 Finding the right parameters](#5.4.1) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='0'></a>\n",
    "# 1. Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clustering can serve to better understand the data through the lens of categories learned from continuous variables. It also permits automatically categorizing new objects according to the learned criteria. Alternatively, clusters can be used to represent groups as prototypes, using e.g. the midpoint of a cluster as the best representatives of learned grouping. \n",
    "\n",
    "In this jupyter notebook, we will look at the following clustering techniques:\n",
    "1. K-means\n",
    "2. Hierarchical Clustering (Agglomerative Clustering)\n",
    "3. Affinity Propagation \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='1'></a>\n",
    "# 2. Getting Started- Loading the data and python packages"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='1.1'></a>\n",
    "## 2.1. Loading the python packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "_cell_guid": "5d8fee34-f454-2642-8b06-ed719f0317e1"
   },
   "outputs": [],
   "source": [
    "# Load libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from pandas import read_csv, set_option\n",
    "from pandas.plotting import scatter_matrix\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import datetime\n",
    "\n",
    "#Import Model Packages \n",
    "from sklearn.cluster import KMeans, AgglomerativeClustering,AffinityPropagation, DBSCAN\n",
    "from scipy.cluster.hierarchy import fcluster\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage, cophenet\n",
    "from scipy.spatial.distance import pdist\n",
    "from sklearn.metrics import adjusted_mutual_info_score\n",
    "from sklearn import cluster, covariance, manifold\n",
    "\n",
    "\n",
    "#Other Helper Packages and functions\n",
    "import matplotlib.ticker as ticker\n",
    "from itertools import cycle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='1.2'></a>\n",
    "## 2.2. Loading the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load dataset\n",
    "dataset = read_csv('Data_MasterTemplate.csv',index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Diable the warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(dataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "df6a4523-b385-69ee-c933-592826d81431"
   },
   "source": [
    "<a id='2'></a>\n",
    "# 3. Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='2.1'></a>\n",
    "## 3.1. Descriptive Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "_cell_guid": "52f85dc2-0f91-3c50-400e-ddc38bea966b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4804, 30)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# shape\n",
    "dataset.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MMM</th>\n",
       "      <th>AXP</th>\n",
       "      <th>AAPL</th>\n",
       "      <th>BA</th>\n",
       "      <th>CAT</th>\n",
       "      <th>CVX</th>\n",
       "      <th>CSCO</th>\n",
       "      <th>KO</th>\n",
       "      <th>DIS</th>\n",
       "      <th>DWDP</th>\n",
       "      <th>...</th>\n",
       "      <th>NKE</th>\n",
       "      <th>PFE</th>\n",
       "      <th>PG</th>\n",
       "      <th>TRV</th>\n",
       "      <th>UTX</th>\n",
       "      <th>UNH</th>\n",
       "      <th>VZ</th>\n",
       "      <th>V</th>\n",
       "      <th>WMT</th>\n",
       "      <th>WBA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</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",
       "      <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>2000-01-03</th>\n",
       "      <td>29.847</td>\n",
       "      <td>35.477</td>\n",
       "      <td>3.531</td>\n",
       "      <td>26.650</td>\n",
       "      <td>14.561</td>\n",
       "      <td>21.582</td>\n",
       "      <td>43.004</td>\n",
       "      <td>16.984</td>\n",
       "      <td>23.522</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.701</td>\n",
       "      <td>16.747</td>\n",
       "      <td>32.228</td>\n",
       "      <td>20.159</td>\n",
       "      <td>21.319</td>\n",
       "      <td>5.841</td>\n",
       "      <td>22.564</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.338</td>\n",
       "      <td>21.713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-04</th>\n",
       "      <td>28.661</td>\n",
       "      <td>34.134</td>\n",
       "      <td>3.233</td>\n",
       "      <td>26.610</td>\n",
       "      <td>14.372</td>\n",
       "      <td>21.582</td>\n",
       "      <td>40.577</td>\n",
       "      <td>17.041</td>\n",
       "      <td>24.900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.445</td>\n",
       "      <td>16.122</td>\n",
       "      <td>31.596</td>\n",
       "      <td>19.890</td>\n",
       "      <td>20.446</td>\n",
       "      <td>5.766</td>\n",
       "      <td>21.834</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.566</td>\n",
       "      <td>20.907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-05</th>\n",
       "      <td>30.122</td>\n",
       "      <td>33.959</td>\n",
       "      <td>3.280</td>\n",
       "      <td>28.474</td>\n",
       "      <td>14.914</td>\n",
       "      <td>22.049</td>\n",
       "      <td>40.895</td>\n",
       "      <td>17.228</td>\n",
       "      <td>25.782</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.702</td>\n",
       "      <td>16.416</td>\n",
       "      <td>31.326</td>\n",
       "      <td>20.086</td>\n",
       "      <td>20.255</td>\n",
       "      <td>5.753</td>\n",
       "      <td>22.564</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.503</td>\n",
       "      <td>21.097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-06</th>\n",
       "      <td>31.877</td>\n",
       "      <td>33.959</td>\n",
       "      <td>2.996</td>\n",
       "      <td>28.553</td>\n",
       "      <td>15.459</td>\n",
       "      <td>22.903</td>\n",
       "      <td>39.782</td>\n",
       "      <td>17.210</td>\n",
       "      <td>24.900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.678</td>\n",
       "      <td>16.973</td>\n",
       "      <td>32.438</td>\n",
       "      <td>20.122</td>\n",
       "      <td>20.998</td>\n",
       "      <td>5.964</td>\n",
       "      <td>22.449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.127</td>\n",
       "      <td>20.527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-07</th>\n",
       "      <td>32.510</td>\n",
       "      <td>34.434</td>\n",
       "      <td>3.138</td>\n",
       "      <td>29.382</td>\n",
       "      <td>15.962</td>\n",
       "      <td>23.306</td>\n",
       "      <td>42.129</td>\n",
       "      <td>18.342</td>\n",
       "      <td>24.506</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.678</td>\n",
       "      <td>18.123</td>\n",
       "      <td>35.024</td>\n",
       "      <td>20.922</td>\n",
       "      <td>21.831</td>\n",
       "      <td>6.663</td>\n",
       "      <td>22.283</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.535</td>\n",
       "      <td>21.052</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               MMM     AXP   AAPL      BA     CAT     CVX    CSCO      KO     DIS  DWDP  ...  \\\n",
       "Date                                                                                     ...   \n",
       "2000-01-03  29.847  35.477  3.531  26.650  14.561  21.582  43.004  16.984  23.522   NaN  ...   \n",
       "2000-01-04  28.661  34.134  3.233  26.610  14.372  21.582  40.577  17.041  24.900   NaN  ...   \n",
       "2000-01-05  30.122  33.959  3.280  28.474  14.914  22.049  40.895  17.228  25.782   NaN  ...   \n",
       "2000-01-06  31.877  33.959  2.996  28.553  15.459  22.903  39.782  17.210  24.900   NaN  ...   \n",
       "2000-01-07  32.510  34.434  3.138  29.382  15.962  23.306  42.129  18.342  24.506   NaN  ...   \n",
       "\n",
       "              NKE     PFE      PG     TRV     UTX    UNH      VZ   V     WMT     WBA  \n",
       "Date                                                                                  \n",
       "2000-01-03  4.701  16.747  32.228  20.159  21.319  5.841  22.564 NaN  47.338  21.713  \n",
       "2000-01-04  4.445  16.122  31.596  19.890  20.446  5.766  21.834 NaN  45.566  20.907  \n",
       "2000-01-05  4.702  16.416  31.326  20.086  20.255  5.753  22.564 NaN  44.503  21.097  \n",
       "2000-01-06  4.678  16.973  32.438  20.122  20.998  5.964  22.449 NaN  45.127  20.527  \n",
       "2000-01-07  4.678  18.123  35.024  20.922  21.831  6.663  22.283 NaN  48.535  21.052  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# peek at data\n",
    "set_option('display.width', 100)\n",
    "dataset.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "_cell_guid": "7bffeec0-5bbc-fffb-18f2-3da56b862ca3"
   },
   "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>MMM</th>\n",
       "      <th>AXP</th>\n",
       "      <th>AAPL</th>\n",
       "      <th>BA</th>\n",
       "      <th>CAT</th>\n",
       "      <th>CVX</th>\n",
       "      <th>CSCO</th>\n",
       "      <th>KO</th>\n",
       "      <th>DIS</th>\n",
       "      <th>DWDP</th>\n",
       "      <th>...</th>\n",
       "      <th>NKE</th>\n",
       "      <th>PFE</th>\n",
       "      <th>PG</th>\n",
       "      <th>TRV</th>\n",
       "      <th>UTX</th>\n",
       "      <th>UNH</th>\n",
       "      <th>VZ</th>\n",
       "      <th>V</th>\n",
       "      <th>WMT</th>\n",
       "      <th>WBA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>363.000</td>\n",
       "      <td>...</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>2741.000</td>\n",
       "      <td>4804.000</td>\n",
       "      <td>4804.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>86.769</td>\n",
       "      <td>49.659</td>\n",
       "      <td>49.107</td>\n",
       "      <td>85.482</td>\n",
       "      <td>56.697</td>\n",
       "      <td>61.735</td>\n",
       "      <td>21.653</td>\n",
       "      <td>24.984</td>\n",
       "      <td>46.368</td>\n",
       "      <td>64.897</td>\n",
       "      <td>...</td>\n",
       "      <td>23.724</td>\n",
       "      <td>20.737</td>\n",
       "      <td>49.960</td>\n",
       "      <td>55.961</td>\n",
       "      <td>62.209</td>\n",
       "      <td>64.418</td>\n",
       "      <td>27.193</td>\n",
       "      <td>53.323</td>\n",
       "      <td>50.767</td>\n",
       "      <td>41.697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>53.942</td>\n",
       "      <td>22.564</td>\n",
       "      <td>55.020</td>\n",
       "      <td>79.085</td>\n",
       "      <td>34.663</td>\n",
       "      <td>31.714</td>\n",
       "      <td>10.074</td>\n",
       "      <td>10.611</td>\n",
       "      <td>32.733</td>\n",
       "      <td>5.768</td>\n",
       "      <td>...</td>\n",
       "      <td>20.988</td>\n",
       "      <td>7.630</td>\n",
       "      <td>19.769</td>\n",
       "      <td>34.644</td>\n",
       "      <td>32.627</td>\n",
       "      <td>62.920</td>\n",
       "      <td>11.973</td>\n",
       "      <td>37.647</td>\n",
       "      <td>17.040</td>\n",
       "      <td>19.937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>25.140</td>\n",
       "      <td>8.713</td>\n",
       "      <td>0.828</td>\n",
       "      <td>17.463</td>\n",
       "      <td>9.247</td>\n",
       "      <td>17.566</td>\n",
       "      <td>6.842</td>\n",
       "      <td>11.699</td>\n",
       "      <td>11.018</td>\n",
       "      <td>49.090</td>\n",
       "      <td>...</td>\n",
       "      <td>2.595</td>\n",
       "      <td>8.041</td>\n",
       "      <td>16.204</td>\n",
       "      <td>13.287</td>\n",
       "      <td>14.521</td>\n",
       "      <td>5.175</td>\n",
       "      <td>11.210</td>\n",
       "      <td>9.846</td>\n",
       "      <td>30.748</td>\n",
       "      <td>17.317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>51.192</td>\n",
       "      <td>34.079</td>\n",
       "      <td>3.900</td>\n",
       "      <td>37.407</td>\n",
       "      <td>26.335</td>\n",
       "      <td>31.820</td>\n",
       "      <td>14.910</td>\n",
       "      <td>15.420</td>\n",
       "      <td>22.044</td>\n",
       "      <td>62.250</td>\n",
       "      <td>...</td>\n",
       "      <td>8.037</td>\n",
       "      <td>15.031</td>\n",
       "      <td>35.414</td>\n",
       "      <td>29.907</td>\n",
       "      <td>34.328</td>\n",
       "      <td>23.498</td>\n",
       "      <td>17.434</td>\n",
       "      <td>18.959</td>\n",
       "      <td>38.062</td>\n",
       "      <td>27.704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>63.514</td>\n",
       "      <td>42.274</td>\n",
       "      <td>23.316</td>\n",
       "      <td>58.437</td>\n",
       "      <td>53.048</td>\n",
       "      <td>56.942</td>\n",
       "      <td>18.578</td>\n",
       "      <td>20.563</td>\n",
       "      <td>29.521</td>\n",
       "      <td>66.586</td>\n",
       "      <td>...</td>\n",
       "      <td>14.147</td>\n",
       "      <td>18.643</td>\n",
       "      <td>46.735</td>\n",
       "      <td>39.824</td>\n",
       "      <td>55.715</td>\n",
       "      <td>42.924</td>\n",
       "      <td>21.556</td>\n",
       "      <td>45.207</td>\n",
       "      <td>42.782</td>\n",
       "      <td>32.706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>122.906</td>\n",
       "      <td>66.816</td>\n",
       "      <td>84.007</td>\n",
       "      <td>112.996</td>\n",
       "      <td>76.488</td>\n",
       "      <td>91.688</td>\n",
       "      <td>24.650</td>\n",
       "      <td>34.927</td>\n",
       "      <td>75.833</td>\n",
       "      <td>69.143</td>\n",
       "      <td>...</td>\n",
       "      <td>36.545</td>\n",
       "      <td>25.403</td>\n",
       "      <td>68.135</td>\n",
       "      <td>80.767</td>\n",
       "      <td>92.557</td>\n",
       "      <td>73.171</td>\n",
       "      <td>38.996</td>\n",
       "      <td>76.966</td>\n",
       "      <td>65.076</td>\n",
       "      <td>58.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>251.981</td>\n",
       "      <td>112.421</td>\n",
       "      <td>231.260</td>\n",
       "      <td>411.110</td>\n",
       "      <td>166.832</td>\n",
       "      <td>128.680</td>\n",
       "      <td>63.698</td>\n",
       "      <td>50.400</td>\n",
       "      <td>117.973</td>\n",
       "      <td>75.261</td>\n",
       "      <td>...</td>\n",
       "      <td>85.300</td>\n",
       "      <td>45.841</td>\n",
       "      <td>98.030</td>\n",
       "      <td>146.564</td>\n",
       "      <td>141.280</td>\n",
       "      <td>286.330</td>\n",
       "      <td>60.016</td>\n",
       "      <td>150.525</td>\n",
       "      <td>107.010</td>\n",
       "      <td>90.188</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            MMM       AXP      AAPL        BA       CAT       CVX      CSCO        KO       DIS  \\\n",
       "count  4804.000  4804.000  4804.000  4804.000  4804.000  4804.000  4804.000  4804.000  4804.000   \n",
       "mean     86.769    49.659    49.107    85.482    56.697    61.735    21.653    24.984    46.368   \n",
       "std      53.942    22.564    55.020    79.085    34.663    31.714    10.074    10.611    32.733   \n",
       "min      25.140     8.713     0.828    17.463     9.247    17.566     6.842    11.699    11.018   \n",
       "25%      51.192    34.079     3.900    37.407    26.335    31.820    14.910    15.420    22.044   \n",
       "50%      63.514    42.274    23.316    58.437    53.048    56.942    18.578    20.563    29.521   \n",
       "75%     122.906    66.816    84.007   112.996    76.488    91.688    24.650    34.927    75.833   \n",
       "max     251.981   112.421   231.260   411.110   166.832   128.680    63.698    50.400   117.973   \n",
       "\n",
       "          DWDP  ...       NKE       PFE        PG       TRV       UTX       UNH        VZ  \\\n",
       "count  363.000  ...  4804.000  4804.000  4804.000  4804.000  4804.000  4804.000  4804.000   \n",
       "mean    64.897  ...    23.724    20.737    49.960    55.961    62.209    64.418    27.193   \n",
       "std      5.768  ...    20.988     7.630    19.769    34.644    32.627    62.920    11.973   \n",
       "min     49.090  ...     2.595     8.041    16.204    13.287    14.521     5.175    11.210   \n",
       "25%     62.250  ...     8.037    15.031    35.414    29.907    34.328    23.498    17.434   \n",
       "50%     66.586  ...    14.147    18.643    46.735    39.824    55.715    42.924    21.556   \n",
       "75%     69.143  ...    36.545    25.403    68.135    80.767    92.557    73.171    38.996   \n",
       "max     75.261  ...    85.300    45.841    98.030   146.564   141.280   286.330    60.016   \n",
       "\n",
       "              V       WMT       WBA  \n",
       "count  2741.000  4804.000  4804.000  \n",
       "mean     53.323    50.767    41.697  \n",
       "std      37.647    17.040    19.937  \n",
       "min       9.846    30.748    17.317  \n",
       "25%      18.959    38.062    27.704  \n",
       "50%      45.207    42.782    32.706  \n",
       "75%      76.966    65.076    58.165  \n",
       "max     150.525   107.010    90.188  \n",
       "\n",
       "[8 rows x 30 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# describe data\n",
    "set_option('precision', 3)\n",
    "dataset.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='2.2'></a>\n",
    "## 3.2. Data Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Taking a look at the correlation. More detailed look at the data will be performed after implementing the Dimensionality Reduction Models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10fbb6bab70>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# correlation\n",
    "correlation = dataset.corr()\n",
    "plt.figure(figsize=(15,15))\n",
    "plt.title('Correlation Matrix')\n",
    "sns.heatmap(correlation, vmax=1, square=True,annot=True,cmap='cubehelix')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3'></a>\n",
    "## 4. Data Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3.1'></a>\n",
    "## 4.1. Data Cleaning\n",
    "Checking for the NAs in the rows, either drop them or fill them with the mean of the column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Null Values = True\n"
     ]
    }
   ],
   "source": [
    "#Checking for any null values and removing the null values'''\n",
    "print('Null Values =',dataset.isnull().values.any())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this step we getting rid of the columns with more than 30% missing values. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4804, 28)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_fractions = dataset.isnull().mean().sort_values(ascending=False)\n",
    "\n",
    "missing_fractions.head(10)\n",
    "\n",
    "drop_list = sorted(list(missing_fractions[missing_fractions > 0.3].index))\n",
    "\n",
    "dataset.drop(labels=drop_list, axis=1, inplace=True)\n",
    "dataset.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given that there are null values drop the rown contianing the null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MMM</th>\n",
       "      <th>AXP</th>\n",
       "      <th>AAPL</th>\n",
       "      <th>BA</th>\n",
       "      <th>CAT</th>\n",
       "      <th>CVX</th>\n",
       "      <th>CSCO</th>\n",
       "      <th>KO</th>\n",
       "      <th>DIS</th>\n",
       "      <th>XOM</th>\n",
       "      <th>...</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>NKE</th>\n",
       "      <th>PFE</th>\n",
       "      <th>PG</th>\n",
       "      <th>TRV</th>\n",
       "      <th>UTX</th>\n",
       "      <th>UNH</th>\n",
       "      <th>VZ</th>\n",
       "      <th>WMT</th>\n",
       "      <th>WBA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</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",
       "      <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>2000-01-03</th>\n",
       "      <td>29.847</td>\n",
       "      <td>35.477</td>\n",
       "      <td>3.531</td>\n",
       "      <td>26.65</td>\n",
       "      <td>14.561</td>\n",
       "      <td>21.582</td>\n",
       "      <td>43.004</td>\n",
       "      <td>16.984</td>\n",
       "      <td>23.522</td>\n",
       "      <td>23.862</td>\n",
       "      <td>...</td>\n",
       "      <td>38.135</td>\n",
       "      <td>4.701</td>\n",
       "      <td>16.747</td>\n",
       "      <td>32.228</td>\n",
       "      <td>20.159</td>\n",
       "      <td>21.319</td>\n",
       "      <td>5.841</td>\n",
       "      <td>22.564</td>\n",
       "      <td>47.338</td>\n",
       "      <td>21.713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-04</th>\n",
       "      <td>28.661</td>\n",
       "      <td>34.134</td>\n",
       "      <td>3.233</td>\n",
       "      <td>26.61</td>\n",
       "      <td>14.372</td>\n",
       "      <td>21.582</td>\n",
       "      <td>40.577</td>\n",
       "      <td>17.041</td>\n",
       "      <td>24.900</td>\n",
       "      <td>23.405</td>\n",
       "      <td>...</td>\n",
       "      <td>36.846</td>\n",
       "      <td>4.445</td>\n",
       "      <td>16.122</td>\n",
       "      <td>31.596</td>\n",
       "      <td>19.890</td>\n",
       "      <td>20.446</td>\n",
       "      <td>5.766</td>\n",
       "      <td>21.834</td>\n",
       "      <td>45.566</td>\n",
       "      <td>20.907</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               MMM     AXP   AAPL     BA     CAT     CVX    CSCO      KO     DIS     XOM  ...  \\\n",
       "Date                                                                                      ...   \n",
       "2000-01-03  29.847  35.477  3.531  26.65  14.561  21.582  43.004  16.984  23.522  23.862  ...   \n",
       "2000-01-04  28.661  34.134  3.233  26.61  14.372  21.582  40.577  17.041  24.900  23.405  ...   \n",
       "\n",
       "              MSFT    NKE     PFE      PG     TRV     UTX    UNH      VZ     WMT     WBA  \n",
       "Date                                                                                      \n",
       "2000-01-03  38.135  4.701  16.747  32.228  20.159  21.319  5.841  22.564  47.338  21.713  \n",
       "2000-01-04  36.846  4.445  16.122  31.596  19.890  20.446  5.766  21.834  45.566  20.907  \n",
       "\n",
       "[2 rows x 28 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fill the missing values with the last value available in the dataset. \n",
    "dataset=dataset.fillna(method='ffill')\n",
    "\n",
    "# Drop the rows containing NA\n",
    "#dataset= dataset.dropna(axis=0)\n",
    "# Fill na with 0\n",
    "#dataset.fillna('0')\n",
    "\n",
    "#Filling the NAs with the mean of the column.\n",
    "#dataset['col'] = dataset['col'].fillna(dataset['col'].mean())\n",
    "\n",
    "dataset.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3.2'></a>\n",
    "## 4.2. Data Transformation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this step we preparing the data for the clustering."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Calculate average annual percentage return and volatilities over a theoretical one year period\n",
    "returns = dataset.pct_change().mean() * 252\n",
    "returns = pd.DataFrame(returns)\n",
    "returns.columns = ['Returns']\n",
    "returns['Volatility'] = dataset.pct_change().std() * np.sqrt(252)\n",
    "data=returns\n",
    "#format the data as a numpy array to feed into the K-Means algorithm\n",
    "#data = np.asarray([np.asarray(returns['Returns']),np.asarray(returns['Volatility'])]).T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All the variables should be on the same scale before applying PCA, otherwise a feature with large values will dominate the result. Below I use StandardScaler in scikit-learn to standardize the dataset’s features onto unit scale (mean = 0 and variance = 1)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>Returns</th>\n",
       "      <th>Volatility</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MMM</th>\n",
       "      <td>0.059</td>\n",
       "      <td>-1.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AXP</th>\n",
       "      <td>-0.075</td>\n",
       "      <td>1.115</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Returns  Volatility\n",
       "MMM    0.059      -1.010\n",
       "AXP   -0.075       1.115"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler().fit(data)\n",
    "rescaledDataset = pd.DataFrame(scaler.fit_transform(data),columns = data.columns, index = data.index)\n",
    "# summarize transformed data\n",
    "rescaledDataset.head(2)\n",
    "X=rescaledDataset\n",
    "X.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The parameters to clusters are the indices and the variables used in the clustering are the columns. Hence the data is in the right format to be fed to the clustering algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4'></a>\n",
    "# 5. Evaluate Algorithms and Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will look at the implementation and visualization of the following clustering techniques. \n",
    "\n",
    "1. KMeans\n",
    "2. Hierarchial clustering\n",
    "3. Affinity Propagation clustering\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.1'></a>\n",
    "## 5.1. K-Means Clustering\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "k-Means is the most well-known clustering algorithm and was first proposed by Stuart Lloyd at Bell Labs in 1957. \n",
    "\n",
    "The algorithm finds K centroids and assigns each data point to exactly one cluster with the goal of minimizing the within-cluster variance (called inertia). It typically uses Euclidean distance but other metrics can also be used. k-Means assumes that clusters are spherical and of equal size and ignores the covariance among features.\n",
    "\n",
    "The problem is computationally difficult (np-hard) because there are 𝐾N ways to partition the N observations into K clusters. The standard iterative algorithm delivers a local optimum for a given K and proceeds as follows:\n",
    "1. Randomly define K cluster centers and assign points to nearest centroid\n",
    "2. Repeat: \n",
    "    1. For each cluster, compute the centroid as the average of the features\n",
    "    2. Assign each observation to the closest centroid\n",
    "3. Convergence: assignments (or within-cluster variation) don’t change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "nclust=6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
       "       n_clusters=6, n_init=10, n_jobs=None, precompute_distances='auto',\n",
       "       random_state=None, tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Fit with k-means\n",
    "k_means = cluster.KMeans(n_clusters=nclust)\n",
    "k_means.fit(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the preceding code, first, we import the KMeans package from scikit-learn and initialize a k-means model. We then fit this model to the data by using the .fit() function. This results in a set of labels as the output. We can extract the labels by using the following code:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the next step we extract the important parameters from the k-means clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "centroids, assignments, inertia = k_means.cluster_centers_, k_means.labels_, k_means.inertia_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 3, 1, 2, 2, 4, 3, 5, 4, 0, 3, 4, 0, 3, 5, 3, 5, 0, 4, 2, 0, 5,\n",
       "       4, 4, 2, 0, 0, 4])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Extracting labels \n",
    "target_labels = k_means.predict(X)\n",
    "#Printing the labels\n",
    "target_labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.1.1'></a>\n",
    "### 5.1.1. Finding optimal number of clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Typically, two metrics are used to evaluate a K-means model.\n",
    "\n",
    "1. Sum of square errors (SSE) within clusters\n",
    "2. Silhouette score.\n",
    "\n",
    "SSE within clusters is derived by summing up the squared distance between each data point and its closest centroid. The goal is to reduce the error value. The intuition behind this is that we would want the distance of each data point to be as close as possible to the centroid. If the error is small, it would mean that the data points in the same cluster are relatively similar. As the number of centroids (clusters) increase, the error value will decrease. As such we would need to rely on the next metric to ensure that we are not introducing too many centroids (clusters) in the model.\n",
    "\n",
    "Silhouette score is a measure of how similar the data point is to its own cluster compared to other clusters. The value ranges from -1 (worst score) to 1 (best score). A negative value would mean that data points are wrongly clustered while values near 0 would mean that there are overlapping clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2oAAAE3CAYAAADbpLILAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzt3Xl8lPW9/v/rPTPZEwiQEMKWKIsbgjTsKoVWq7VabbVuFbF1Oe1pe1rbc0572vM9p6fLac85be3mr5taFRfaWq2KWrWKopZFUEEEBWXfQdZAtpn5/P6474QACQmQzH3fyev5ePCYmXvuzFzeTiZz3Z/PfY855wQAAAAACI9Y0AEAAAAAAIeiqAEAAABAyFDUAAAAACBkKGoAAAAAEDIUNQAAAAAIGYoaAAAAAIQMRQ0AAAAAQoaiBgAAAAAhQ1EDAAAAgJBJZPLJSkpKXGVlZSafsl3279+vgoKCoGMcEzJ3vqjllcicKVHLHLW8EpkzJWqZo5ZXInOmRC1z1PJKZO5IixYt2uGcK21zRedcxv5VVVW5MJo9e3bQEY4ZmTtf1PI6R+ZMiVrmqOV1jsyZErXMUcvrHJkzJWqZo5bXOTJ3JEkLXTu6E1MfAQAAACBkKGoAAAAAEDIUNQAAAAAIGYoaAAAAAIQMRQ0AAAAAQoaiBgAAAAAhQ1EDAAAAgJChqAEAAABAyFDUAAAAACBkun1Re3fbPr2zMxV0DAAAAABo0u2L2q1/WKx7ltXJORd0FAAAAACQRFHTtAkV2lTtNG/VzqCjAAAAAIAkipo+flZ/FWRJ985dE3QUAAAAAJBEUVNuVlznDsjSM8u2avOemqDjAAAAAABFTZI+NDihtHN6YP66oKMAAAAAAEVNkvrmxzT1lL56cME61SU5AyQAAACAYFHUfNdPrNCO6nr9demWoKMAAAAA6OYoar7Jw0pV2Sdf985dG3QUAAAAAN0cRc0Xi5mum1ChRWt3aenGPUHHAQAAANCNUdSa+VTVIOVmxTSDUTUAAAAAAaKoNdMzP0ufGD1Af3ljo3YfqA86DgAAAIBuiqJ2mGkTKlWXTOtPCzcEHQUAAABAN0VRO8zp/XtobGUvzZi3Vum0CzoOAAAAgG6IotaCaRMrtW7nAb24YnvQUQAAAAB0QxS1Flx4Rj+VFuXonrlrgo4CAAAAoBuiqLUgOxHTteMG68UV27Vmx/6g4wAAAADoZihqrbh2/GDFzXTfPE7VDwAAACCzKGqtKOuRqwtG9NMfF65XTX0q6DgAAAAAuhGK2lFcP6FCe2uTevSNjUFHAQAAANCNUNSOYtxJvXVqvyLdM3etnONU/QAAAAAyg6J2FGamaRMrtHzzXi1auyvoOAAAAAC6CYpaGy47a4CKchO6Zy4nFQEAAACQGRS1NhTkJHRF1UA99eZmbdtbG3QcAAAAAN0ARa0dpk2oUDLt9OCC9UFHAQAAANANtFnUzGyQmc02s+Vm9paZfdlf/m0z22hmb/j/Lur8uME4ubRQ5w4r0QML1qohlQ46DgAAAIAurj0jaklJX3POnSZpgqQvmNnp/n23OefO8v892WkpQ2D6xEpt3VunZ97aGnQUAAAAAF1cm0XNObfZOfeaf32fpOWSBnR2sLCZempfDSjO071z1wQdBQAAAEAXZ8fy/WBmVilpjqQRkr4q6QZJeyUtlDfqdsQ57M3sFkm3SFJZWVnVzJkzTzRzh6uurlZhYWGb6z25ql5/XNGg756dp0FFwR7e197MYRK1zFHLK5E5U6KWOWp5JTJnStQyRy2vROZMiVrmqOWVyNyRpk6dusg5N6bNFZ1z7fonqVDSIkmf9G+XSYrLG5X7vqS72nqMqqoqF0azZ89u13rvV9e5Yd960n3z4SWdG6gd2ps5TKKWOWp5nSNzpkQtc9TyOkfmTIla5qjldY7MmRK1zFHL6xyZO5Kkha4d/atdw0JmliXpz5Lud8497Be8rc65lHMuLel3ksYda5uMmt4F2fr4qP565PWN2lvbEHQcAAAAAF1Ue876aJLulLTcOfeTZsvLm632CUlLOz5e+Fw/sUIH6lP686INQUcBAAAA0EW1Z0TtbEnTJH3osFPx/6+ZvWlmSyRNlXRrZwYNi5EDi3XWoGLNmLtW6XT7j+8DAAAAgPZKtLWCc+5lSdbCXV36dPxHM31ShW79w2K98t4OnTusNOg4AAAAALqYYE9dGFEXnVmuPgXZuufva4OOAgAAAKALoqgdh5xEXFePG6Tn396q9TsPBB0HAAAAQBdDUTtO146vkCTdP39dwEkAAAAAdDUUteM0oDhP559epj+8uk61Damg4wAAAADoQihqJ+D6iZXadaBBs5ZsDjoKAAAAgC6EonYCJg3poyGlBZoxd03QUQAAAAB0IRS1E2Bmun5ipRZv2KM31u8OOg4AAACALoKidoI++YEBKsiO6965a4KOAgAAAKCLoKidoKLcLH3yAwM1a/FmvV9dF3QcAAAAAF0ARa0DXD+xQvWptP6wcH3QUQAAAAB0ARS1DjCsrEgTT+6j++etUzKVDjoOAAAAgIijqHWQ6ZMqtHF3jZ57e1vQUQAAAABEHEWtg5x3WpnKe+Zqxty1QUcBAAAAEHEUtQ6SiMf06fGD9fK7O/Tutuqg4wAAAACIMIpaB7pq7GBlxU33zWNUDQAAAMDxo6h1oNKiHH3szHI9tGiDquuSQccBAAAAEFEUtQ52/aRKVdcl9cjrG4OOAgAAACCiKGodbPSgYo0Y0EP3/n2NnHNBxwEAAAAQQRS1DmZmun5ipVZuq9a8VTuDjgMAAAAggihqneDjo/qrOD9L985dE3QUAAAAABFEUesEuVlxXTVmkJ5ZtlWb99QEHQcAAABAxFDUOsl1EyqUdk4PzF8XdBQAAAAAEUNR6ySDeufrQ6f01YML1qkumQo6DgAAAIAIoah1omkTK7Sjul5/Xbol6CgAAAAAIoSi1okmDytVZZ983Tt3bdBRAAAAAEQIRa0TxWKm6yZUaNHaXVq6cU/QcQAAAABEBEWtk32qapDysuKawagaAAAAgHaiqHWynvlZumx0f/3ljY3afaA+6DgAAAAAIoCilgHTJlSqLpnWnxZuCDoKAAAAgAigqGXA6f17aGxlL82Yt1bptAs6DgAAAICQo6hlyPUTK7Vu5wG9uGJ70FEAAAAAhBxFLUMuOKOfSotydM/cNUFHAQAAABByFLUMyU7EdO24wXpxxXat2bE/6DgAAAAAQoyilkHXjh+suJnum8ep+gEAAAC0jqKWQWU9cnXBiH7648L1qqlPBR0HAAAAQEi1WdTMbJCZzTaz5Wb2lpl92V/e28yeNbOV/mWvzo8bfdMnVmpvbVKPvrEx6CgAAAAAQqo9I2pJSV9zzp0maYKkL5jZ6ZK+Iek559wwSc/5t9GGsZW9dGq/It0zd62c41T9AAAAAI7UZlFzzm12zr3mX98nabmkAZIulXSPv9o9ki7rrJBdiZnp+omVWr55rxat3RV0HAAAAAAhdEzHqJlZpaTRkuZLKnPObZa8Miepb0eH66ouG91fRbkJ3TOXk4oAAAAAOJK1d/qdmRVKelHS951zD5vZbudccbP7dznnjjhOzcxukXSLJJWVlVXNnDmzY5J3oOrqahUWFmb0OR9YXqfn1iX14w/mqTj32M/pEkTmExW1zFHLK5E5U6KWOWp5JTJnStQyRy2vROZMiVrmqOWVyNyRpk6dusg5N6bNFZ1zbf6TlCXpaUlfbbbsHUnl/vVySe+09ThVVVUujGbPnp3x51y1vdpVfH2W++mzK47r54PIfKKiljlqeZ0jc6ZELXPU8jpH5kyJWuao5XWOzJkStcxRy+scmTuSpIWuHR2sPWd9NEl3SlrunPtJs7sekzTdvz5d0qPtbZGQTiop0OThpXpgwVo1pNJBxwEAAAAQIu2Zc3e2pGmSPmRmb/j/LpL0Q0nnm9lKSef7t3EMrp9Qoa176/TMW1uDjgIAAAAgRBJtreCce1mStXL3hzs2Tvcy9dS+GtgrT/fOXaOPjSwPOg4AAACAkDj2s1igw8RjpusmVGj+6p16e8veoOMAAAAACAmKWsCuGjNIOYmYZnCqfgAAAAA+ilrAehVk65JR/fXI6xu1t7Yh6DgAAAAAQoCiFgLTJ1bqQH1Kf160IegoAAAAAEKAohYCZw7sqbMGFWvG3LVKp9v3BeQAAAAAui6KWkhMn1ShVTv265X3dgQdBQAAAEDAKGohcdGZ5epTkK17/s5JRQAAAIDujqIWEjmJuK4eN0jPv71V63ceCDoOAAAAgABR1ELk0+MrJEn3z18XcBIAAAAAQaKohUj/4jydf3qZ/vDqOtU2pIKOAwAAACAgFLWQmT6xUrsONGjWks1BRwEAAAAQEIpayEwc0kdD+xZqxtw1QUcBAAAAEBCKWsiYma6fWKHFG/bojfW7g44DAAAAIAAUtRD6xOgBKsiO6965a4KOAgAAACAAFLUQKsrN0uVVAzVr8Wa9X10XdBwAAAAAGUZRC6lpEypUn0pr5qvrg44CAAAAIMMoaiE1rKxIk4b00QPz1ymZSgcdBwAAAEAGUdRC7PqJFdq4u0bPvb0t6CgAAAAAMoiiFmLnnVam8p65mjF3bdBRAAAAAGQQRS3EEvGYPj1+sF5+d4fe3VYddBwAAAAAGUJRC7mrxw1Wdjym++YxqgYAAAB0FxS1kCspzNFFZ/bTQ4s2qLouGXQcAAAAABlAUYuA6ydVqrouqUde3xh0FAAAAAAZQFGLgNGDinXmgJ669+9r5JwLOg4AAACATkZRiwAz07SJFVq5rVrzVu0MOg4AAACATkZRi4iPj+qv4vws3Tt3TdBRAAAAAHQyilpE5GbFddWYQXpm2VZt3lMTdBwAAAAAnYiiFiHXTahQ2jk9MH9d0FEAAAAAdCKKWoQM6p2vD53SVw8uWKeGNCcVAQAAALoqilrEXD+pUjuq6/XKRr5TDQAAAOiqKGoRc+7QEo2p6KX7ltXr7+/uCDoOAAAAgE5AUYuYWMx0x/Qx6ldguvnehVq8fnfQkQAAAAB0MIpaBBXnZ+trY3LVuzBbN/x+gd7dti/oSAAAAAA6EEUtonrlxjTjs+MVj8U07c4F2ribU/YDAAAAXQVFLcIqSwo048Zxqq5Latod87Wjui7oSAAAAAA6AEUt4k4r76Hf3zBWm/bUaPpdC7S3tiHoSAAAAABOUJtFzczuMrNtZra02bJvm9lGM3vD/3dR58bE0Yyp7K1fXVeld7bs0033LFRtQyroSAAAAABOQHtG1O6WdGELy29zzp3l/3uyY2PhWE09pa9+fOUovbpmp774wGtqSKWDjgQAAADgOLVZ1JxzcyTtzEAWnKBLzxqg71w6Qn9bvk1ff2iJ0mkXdCQAAAAAx8Gca/vDvJlVSprlnBvh3/62pBsk7ZW0UNLXnHO7WvnZWyTdIkllZWVVM2fO7IDYHau6ulqFhYVBxzgmR8v82Hv1enhlg86vSOjaU7NlZhlO17Kobeeo5ZXInClRyxy1vBKZMyVqmaOWVyJzpkQtc9TySmTuSFOnTl3knBvT5orOuTb/SaqUtLTZ7TJJcXkjct+XdFd7HqeqqsqF0ezZs4OOcMyOljmdTrv/euwtV/H1We5nf1uRuVBtiNp2jlpe58icKVHLHLW8zpE5U6KWOWp5nSNzpkQtc9TyOkfmjiRpoWtHd0ocTwt0zm1tvG5mv5M063geB53DzPTvHztNe2oa9JNnV6hXfpamTawMOhYAAACAdjquomZm5c65zf7NT0haerT1kXmxmOl/Lj9Te2oa9B+PvaUeeVm69KwBQccCAAAA0A7tOT3/g5LmSjrFzDaY2Y2S/tfM3jSzJZKmSrq1k3PiOCTiMf3y2tEaV9lbX/vjYs1+e1vQkQAAAAC0Q3vO+niNc67cOZflnBvonLvTOTfNOXemc26kc+7jzUbXEDK5WXHdMX2MTi0v0ufvX6RX13ACTwAAACDs2vM9aoi4otws3f2ZcerfM0+fvftVLdu0N+hIAAAAAI6CotZNlBTmaMZN41WYk9D1dy3Qmh37g44EAAAAoBUUtW5kQHGeZtw4XmnndN2d87VlT23QkQAAAAC0gKLWzQztW6i7PzNWu/bX6/q75mv3gfqgIwEAAAA4DEWtGxo5sFi/mz5Ga94/oBt+/6r21yWDjgQAAACgGYpaNzVpSIl+cc1oLdmwW5+7b5HqkqmgIwEAAADwUdS6sQvO6Kf/uXykXlq5Q1/9w2Kl0i7oSAAAAAAkJYIOgGB9aswg7alp0PeeWK4eeQn99yfOlJkFHQsAAADo1ihq0E3nnqxdB+p1++z3VJyfra9feGrQkQAAAIBujaIGSdI/f+QU7T7QoF+98J6K87L0Dx8cEnQkAAAAoNuiqEGSZGb6zqUjtKemQT946m0V52fpqrGDg44FAAAAdEsUNTSJx0w/ufIs7atN6t8eflM987J04YjyoGMBAAAA3Q5nfcQhshMx/eq6D2j04F76pwff0MsrdwQdCQAAAOh2KGo4Qn52QndNH6uTSwt0y4yFemP97qAjAQAAAN0KRQ0t6pmfpXs/O04lhTm64fcLtHLrvqAjAQAAAN0GRQ2t6tsjV/fdOF5Z8Zim3blAG3YdCDoSAAAA0C1Q1HBUg/vka8aN43SgPqlpdy7Q9n11QUcCAAAAujyKGtp0ar8e+v1nxmrLnlpNv2uB9tY2BB0JAAAA6NIoamiXqore+vW0Kq3ctk833b1QtQ2poCMBAAAAXRZFDe32weGl+smVZ+nVtTv1j/e/poZUOuhIAAAAQJdEUcMxuWRUf33vshF6/u1t+pc/LVY67YKOBAAAAHQ5iaADIHo+Pb5Cuw806P+efkfF+dn6z0tOl5kFHQsAAADoMihqOC7/OGWIdu2v1x0vr1Zxfpa+ct7woCMBAAAAXQZFDcfFzPStj52m3TUN+unfVqo4L0s3nH1S0LEAAACALoGihuNmZvrhJ8/U3poGffvxZSrOz9ZlowcEHQsAAACIPE4mghOSiMf082tGa+LJffS1Py3W829vDToSAAAAEHkUNZyw3Ky4fjd9jM7o30Ofv+81LVi9M+hIAAAAQKRR1NAhCnMSuvsz4zSwV55uvPtVLd24J+hIAAAAQGRR1NBhehdka8aN41WUm9ANv1+g1Tv2Bx0JAAAAiCSKGjpU/+I8zbhpvJyTrrtjvjbvqQk6EgAAABA5FDV0uCGlhbrns+O0p6ZB19+5QLv21wcdCQAAAIgUiho6xYgBPXXH9DFau/OAbrj7VVXXJYOOBAAAAEQGRQ2dZsLJfXT7tR/Q0o179A8zFqou6YKOBAAAAEQCRQ2d6vzTy/S/l4/U3997X//+Sg2n7gcAAADagaKGTnd51UA9ePMESdJVv52r785aptqGVMCpAAAAgPBqs6iZ2V1mts3MljZb1tvMnjWzlf5lr86NiaibcHIffffsPF03vkJ3vrxaF/3sJb22blfQsQAAAIBQas+I2t2SLjxs2TckPeecGybpOf82cFS5CdN3Lxuh+28ar7pkWlf86u/6wVPLGV0DAAAADtNmUXPOzZF0+IFFl0q6x79+j6TLOjgXurCzh5bor185V1eNHaTfvLhKF//iZS1evzvoWAAAAEBoHO8xamXOuc2S5F/27bhI6A6KcrP0g0+O1D2fHafq2qQ++au/60dPv6O6JKNrAAAAgDnX9inTzaxS0izn3Aj/9m7nXHGz+3c551o8Ts3MbpF0iySVlZVVzZw5swNid6zq6moVFhYGHeOYdKXM+xucHny7Xi9vTGpgoenmkTmq6BEPIOGhutI2DjMyd76o5ZXInClRyxy1vBKZMyVqmaOWVyJzR5o6deoi59yYNld0zrX5T1KlpKXNbr8jqdy/Xi7pnfY8TlVVlQuj2bNnBx3hmHXFzH9btsWN+d6zbsi/PeFue/YdV59MZSZYK7riNg4jMne+qOV1jsyZErXMUcvrHJkzJWqZo5bXOTJ3JEkLXTu60/FOfXxM0nT/+nRJjx7n4wBNPnxamZ69dbIuHlmun/5tpS67/RW9vWVv0LEAAACAjGvP6fkflDRX0ilmtsHMbpT0Q0nnm9lKSef7t4ETVpyfrZ9ePVq/vq5KW/bU6pJfvKzbZ7+rZCoddDQAAAAgYxJtreCcu6aVuz7cwVmAJheO6Kexlb30H4+9pf97+h0989YW/fjKURratyjoaAAAAECnO96pj0Cn61OYo9uv/YB+ee1ordt5QBf9/GX95sX3lEq3fQIcAAAAIMooagi9i0f21zO3flBThpfqB0+9rU/9+u9atb066FgAAABAp6GoIRJKi3L0m2lV+ulVZ+m97fv10Z+9pDtfXq00o2sAAADogihqiAwz02WjB+iZWyfrnKEl+u6sZbr6t/O09v39QUcDAAAAOhRFDZFT1iNXd0wfox99apSWb9mrC3/6kmbMXcPoGgAAALoMihoiycx0RdVAPXPrZI09qbf+36Nv6bo752v9zgNBRwMAAABOGEUNkVbeM0/3fGasfvDJM7V4/W5d+NM5emD+Onlf+g4AAABEE0UNkWdmumbcYD1962SNGlSsbz7ypq6/a4E27a4JOhoAAABwXChq6DIG9srXfTeO13cvPUML1+zSBbfN0Z8Wrmd0DQAAAJFDUUOXEouZpk2s1NNfmazT+vfQvzy0RDfes1Bb99YGHQ0AAABoN4oauqTBffI18+YJ+o+LT9ff39uh83/yoh55fQOjawAAAIgEihq6rFjM9NlzTtKT/3SuhvYt1K1/WKx/mLFI2/fVBR0NAAAAOCqKGrq8k0sL9afPTdI3LzpVL6zYro/c9qJmLdkUdCwAAACgVRQ1dAvxmOmWyUP05D+do8G98/XFB17XF+5/Te9XM7oGAACA8KGooVsZ2rdIf/78JP3LBafomWVb9JHb5uivSzcHHQsAAAA4BEUN3U4iHtMXpg7V4186R/165upz972mL898XbsP1AcdDQAAAJBEUUM3dmq/HvrLF87WrecN1xNLNuv82+boueVbg44FAAAAUNTQvWXFY/ryecP06BfPVp+CbN14z0J97Y+LtaemIehoAAAA6MYoaoCkM/r31GNfPEdf+tBQ/eWNjbrgtjl6fVtS6TTfuwYAAIDMo6gBvuxETF/7yCl6+POTVJSb0M9eq9OkHz6v7zy+TK+v28WXZQMAACBjEkEHAMJm1KBizfqnc3Tbn2ZrVUNP3Tdvre56ZbUG9srTxSP76+KR5Tqjfw+ZWdBRAQAA0EVR1IAW5CTimlCe0DemjNHe2gY989ZWzVqySXe8tEq/fvE9nVxSoItH9dclI8s1rKwo6LgAAADoYihqQBt65GbpiqqBuqJqoHbtr9df39qixxdv0i+fX6mfP7dSp/Yr0sUjy3XxyP6qLCkIOi4AAAC6AIoacAx6FWTrmnGDdc24wdq2r1ZPvemVth89s0I/emaFzhzQU5eMKtfHRvbXgOK8oOMCAAAgoihqwHHqW5Sr6ZMqNX1SpTbtrtETSzZr1pJN+u8n39Z/P/m2qip66ZKR5bpoZLn6FuUGHRcAAAARQlEDOkD/4jzdPPlk3Tz5ZK19f79mLdmsxxdv0rcfX6b/mrVME07qo4tHleujI8rVuyA76LgAAAAIOYoa0MEq+hToC1OH6gtTh+rdbfv0+OLNenzJJn3rkaX6j0ff0jlDS3TxyHJ95Ix+6pmXFXRcAAAAhBBFDehEQ/sW6dbzi/SV84Zp2ea9TSNt//LQEn3rkaWaPLxUl4wq13mnlakgh19HAAAAePhkCGSAmemM/j11Rv+e+tcLTtHiDXv0+OJNemLJZv1t+VblZsX04VPLdMmock05pa9ys+JBRwYAAECAKGpAhpmZzhpUrLMGFetbF52mhWt36fHFm/TU0s164s3NKsiO6yNn9NPFI8t17rBSZSdiQUcGAABAhlHUgADFYqZxJ/XWuJN66z8vOV3zVu3UrCWb9NTSLXrk9Y3qmZelC8/op4tHlWviyX2UiFPaAAAAugOKGhASiXhM5wwr0TnDSvSdS0fo5Xe3a9Zib5TtDwvXq09Btj56Zj9dMrK/xlb2VixmQUcGAABAJ6GoASGUnYjpQ6eW6UOnlqm2IaUX3tmux5ds0kOLNui+eevUr0euLjqzXJeMKtdZg4plRmkDAADoSihqQMjlZsV14Yh+unBEP+2vS+q5t7fp8cWbdN+8tbrrldUa2CtPF4/sr4tHlss5F3RcAAAAdACKGhAhBTkJfXxUf318VH/trW3QM29t1awlm3THS6v06xffU2me6YI9b2rysFJNGlqiQk75DwAAEEl8igMiqkdulq6oGqgrqgZq5/56/XXpFv3x5WV6+LWNum/eOiVipqqKXpo8vFQfHF6q08t7cFwbAABARJxQUTOzNZL2SUpJSjrnxnREKADHpndBtq4dP1j9a1Zp0jmTtXDtTs1ZsUNzVmzX/z39jv7v6XdUUpitc4d5pe2cYSUqKcwJOjYAAABa0REjalOdczs64HEAdIDsREyThpRo0pASfeOjp2rbvlq9tGKH5qzcrhdXbNcjr2+UJI0Y0EMfHF6qycNK9YGKXsri1P8AAAChwdRHoIvrW5Sry6sG6vKqgUqnnZZu2qM5K7Zrzood+vWLq3T77PdUmJPQxCF99EF/muSg3vlBxwYAAOjW7ETOEmdmqyXtkuQk/cY599sW1rlF0i2SVFZWVjVz5szjfr7OUl1drcLCwqBjHBMyd76o5ZWOPfOBBqflO1N6c0dKb25P6f1a7/2gLN90ZklcI0riOq13XDmJzju2rTts56BFLa9E5kyJWuao5ZXInClRyxy1vBKZO9LUqVMXteeQsRMtav2dc5vMrK+kZyV9yTk3p7X1x4wZ4xYuXHjcz9dZXnjhBU2ZMiXoGMeEzJ0vanmlE8vsnNOqHfv90bbtmrvqfdU2pJUdj2nsSb00eVipJg8v1an9ijr0e9u623YOQtTySmTOlKhljlpeicyZErXMUcsrkbkjmVm7itoJTX10zm3yL7eZ2SOSxklqtagBCC8z05DSQg0pLdRnzj5JtQ0pLVyzyzu27Z3t+sFTb+sHT72tsh45OtcvbecOLVGvguy4LliVAAAcE0lEQVSgowMAAHQ5x13UzKxAUsw5t8+//hFJ3+mwZAAClZsV1znDSnTOsBJ986LTtGVPbdMJSZ5dtlUPLdogM2nkwGJ9cFiJJg8v1VmDipXgpCQAAAAn7ERG1MokPeJPgUpIesA599cOSQUgdPr1zNWVYwbpyjGDlEo7LdmwWy/60yR/Oftd/fz5d1WUm9A5Q73SNnl4qQYU5wUdGwAAIJKOu6g551ZJGtWBWQBERDxmGj24l0YP7qWvnDdcew406OV3ve9tm7Nyu55aukWSNLRvoX9sW4kmnNxHuVnxgJMDAABEA6fnB3DCeuZn6WMjy/WxkeVyzundbdV6cYU3TfK++Wt11yurlZOIadxJvZu+AmBo38IOPSkJAABAV0JRA9ChzEzDyoo0rKxIN517smrqU5q/+n3N8b90+3tPLNf3nliu8p65mjysVMX1SQ3bXcM0SQAAgGYoagA6VV52XFNO6aspp/SVJG3cXdP0FQBPLt2sfbVJ/WbJ8+rfM1djKntrbGUvjansreFlRYrHGHEDAADdE0UNQEYNKM7TNeMG65pxg5VKO90363mpZIheXbNT81e/r8cWb5IkFeUk9IGKXk3F7axBxRzjBgAAug2KGoDAxGOmih5xTZlUqemTKuWc04ZdNVq4dqdeXbNLC9fs1I+e2S5JyoqbRgzoqbGVvTWmwitvvfkONwAA0EVR1ACEhplpUO98Deqdr0+MHihJ2n2gXovW7tKra3Zp0dqduvuVNfrtnFWSpCGlBV5x86dMDu6dzwlKAABAl0BRAxBqxfnZ+vBpZfrwaWWSpNqGlJZu3NM04vbU0i2a+ep6SVJJYU7TVMmxlb10enkPvoAbAABEEkUNQKTkZsU1xh9Fk4YonXZ6d3u1Xl2zUwvX7NKrfnmTpPzsuEYPLtaYit4aW9lbowcXqyCHtz0AABB+fGIBEGmxmGl4WZGGlxXp0+MrJEmb99RooT/itnDtLv3i+ZVKO++YuNPLe2hMZa+mY9369sgN+L8AAADgSBQ1AF1Oec88XTIqT5eM6i9J2lfboNfX7dbCNd5JSh5csE6/f2WNJGlw7/ym4ja2speGlPJF3AAAIHgUNQBdXlFuliYPL9Xk4aWSpIZUWm9t2usXt5168Z3tevi1jZKkXvlZqqo4+H1uZw7oqewEx7kBAIDMoqgB6Hay4jGdNahYZw0q1k3nniznnFbv2N90jNuitbv0t+VbJUk5iZhGDSpuKm4fGNwr4PQAAKA7oKgB6PbMTCeXFurk0kJdOXaQJGn7vjotWusd5/bq2l36zYurdPvs9yRJPbJNJ7/1igb2ytPAXvn+5cHrfDE3AAA4URQ1AGhBaVGOLhzRTxeO6CdJOlCf1Bvrd+v1dbs1/633lM5JaOnGPXr6rS1qSLkjfra1EjegmCIHAADaRlEDgHbIz05o0pASTRpSojNsg6ZMGS9JSqWdtu2r1YZdNdqw64A27Kzxru8+oCUbduupNzcrmT60yPU9osgdLHQDeuUpJ0GRAwCgu6OoAcAJiMdM5T3zVN4zT2Mrex9xfyrttHVvsyLX7PKN9bv1ZAtFrqxHToujcQN75at/cS5FDgCAboCiBgCdKB4z9S/OU//iPI07qfUit35nY4k7WOReW7dLs5ZsVqpZkTOTyopyWyxxA3t5z8NZKgEAiD6KGgAEqHmRG9/C/clUWlv31TUrcgcvF67dpcdbKHL9euQeUt72bW1Qw7Kt6lOYrZKCHPUpzFZ+dpzviwMAIMQoagAQYol4TAOKvZOQtCSZSmuLP7Xy8FG5Bat36tE3apR20t1vLTzk53ISMZUUeqWtT0G2+vjXG4tcn8Ic9SnIVklhjnoXZDNKBwBAhlHUACDCEvGYP3KWrwkn9zni/oZUWo8984KGn1mlHfvr9H51vd6vrtP7++u1o9q7vb26Tm9v2af3q+tVn0q3+DxFuQmv2BVkNxW5kmYFr0/BwdJXnJ+teIzROgAATgRFDQC6sKx4TH3yYjpzYM8213XOqbou6ZW5/XXaUV3fYrFbvWO/Fq3dpZ3763XYeVAkSTGTehc0K29No3MHrzcvd4U5CaZhAgBwGIoaAECS98XfRblZKsrNUmVJQZvrp9JOuw/UH1LiDpa6g9eXbtyjHdV12lebbPFxshOxI0bnqnfW6c3USvXIy1KPvIR65GapZ16WdzvXW5aXxXF2AICui6IGADgu8Zj55SpHw8uK2ly/LpnSzv3eKF1TsfOnY+6ortfO/V6xW7m1Wtv3JfX0mhVHfbysuPmlLUs9chPNStzBctd43+Elr0duFl88DgAINYoaACAjchLxpu+ca8sLL7ygSedM1r7aBu2tTWpvTYP21DRob22D9tYk/cvGZd79e2sbtHF3jXd/TUOrx9sdzBM7ouT1PKLktbTMWz8rzglWAACdh6IGAAil7ESsacTueNQ2pJoVuoPlrqnYNSt+e2oatOtAvda+v197a73bqZYOwGsmPzt+yAhd/f5a/WnTayrMTqggJ6HC3IQKc+Le9ZyEChqX5yRUkBP3LxN8VQIAoEUUNQBAl5SbFVduVlx9i3KP+WedczpQn2p5BK/myFG+PTUN2lHvtHzTXlXXJbW/Lqn99al2PZeZ/BLnlboiv8A1L3UFOYmDBbDp/oNlr7DZcr5KAQC6BooaAACHMbOmslTe9gkzJXnTNadMmdJ0O5122l+f1P661MHyVpf0rtcnVV2XOnRZ3aHr7tx/4JCfr08efSpno+x47GC5O6T0xQ8b1Uto87oG7Xp9gwpzslSQE1eRf1nojwhywhYACA5FDQCAThCLHTyLZkeoT6Z1oD6pfbVJv8AdLHuHFsHUEaVwT02DNu2uOWTdxpmd9y5b3Pp/g+mQYld42OhdYU5chbmJI0YCG6970z+9f0zxBIBjQ1EDACACshMxZSe8LxQ/Uc451TSk9MzsORpVNV776/wC6Be56maFrrouqWq/HDaus21fbdNIX3Vdss3j+aSDUzybjtHLzWoa5Wte6A6fylmUe7AU7qxNa+f+emUnYspJxJSIGeUPQJdFUQMAoJsxM+VnJ1ScE9NJ7fjOvKNxzqkumT6i6B1S+moPjvZV1zVof11K+/x1duw7cHA6aG1SybZK3wvPNvvv8M7emZOIN5W37MNu5xy2/OD1I9c92jpHe5wEZwAF0AkoagAA4LiZWdOJW0qLju8MnY0aS19j0Wssf42jea+/uUyVJw9VfSqtuoa0d5lMqz6ZVl0ypbqGtOqa39fgjfq9X924bspf11unLplSOwYD2xQztVD4YspOxFV/oEa/e3ee8vxtlJ8d965nx5WflVBedkx52d7xgHn+/U3r+es2XWbFFYsxggh0FxQ1AAAQCs1LX0kLX8vQc/dKTTn7pA59zmQqfWjxa0irPpVSbcOhJbCx4B28TB1yu6V16pJpba6vVl1DWrv2N6i2IaUD9SnVNHj/2nuCmOZyEjHlZceV75e9I8pdU7HzSmB+dkK57SyBedneSCGAcKCoAQCAbisR96YudsChfy3yzgY6qcX7kqm0av2TxNTWp1XTkNKB+qRX5BoLXSuXjYWvtt67vq82qW1765pKYE2991jHOmIYMykRkwrmPKOcRFy5WTHlZvlTP/3L3HZc5mbFmn4+JxFXzmG3D7/MinO8IXA4ihoAAEAAEvGYCuMxFeZ0zscx55zqU+kjSmDTyF5L5a8+pXdXr1Fpv/6qS3oji7UN3uhhbYNXCLfvq1N98tDldcl028cXHkXj9NHmxfBYCuL6tfV6N75KWfGYsuIxJeKmbP/SW+ZdJmIxZSdMiVjs0OVN6x9clhWPKc5UUwSIogYAANAFmZl/4pO4eqr9XxPxwgubNWXKiGN+vqR/zGDzAlfrHwt4+GVdK8ubXx5zQVyx/Jgzt8VMXmmLmbISftGLN14/WOiy4qZEPNbucrhpQ71eb1ihRMz7Oe/SlIiZ4rFYs+vWVBibr+st99dt9rOJmL9u3LueiJnicVNW7OBjcJxjdJxQUTOzCyX9TFJc0h3OuR92SCoAAABESuM00oJOGiFsTTKV1nMvvKiJZ5+jBr+41fuXDam0/881HY+YTLmmZQ2ptJLptBqSTg3ptBqS/nJ/WTLdys80u+49hvecNQ0pNdQeZb2UN8pZn0zLrVqZ0e3UyJve6pXBlgtg82J4sAxW763Rb1bMU9wve4mYKWameEzeMvN+Pm7N7vdvx5ut27is+f2x2KE/GzcpHo/5P6uDj93seWJ2sMwefBwdfL6YaduBYz8ONEyO+zfJzOKSbpd0vqQNkl41s8ecc8s6KhwAAABwNIl4TDlxU48O+nL5THjhhRc0efIHlXJOKb9QptJOybRTMuUVRG95S/c3u572yl8q7dSQdkr5t5MtresXyoOPm272fIf+bPPnbHzcaknJdFp1SaeUk1LptFJpKZ12SjnXdJlKe9eTaae0fzuVdko7edfdwfs727h+cV15Uac/Tac5kV0e4yS965xbJUlmNlPSpZIoagAAAMBRxGKmmExZcSk3Kx50nDYd7cQ4x+uQctdU8tS0rHmxS7VQCA+WQKdUWoc8Tso5rXvnzQ7Nm2nm3PG1WTO7QtKFzrmb/NvTJI13zn3xsPVukXSLJJWVlVXNnDnzxBJ3gurqahUWFgYd45iQufNFLa9E5kyJWuao5ZXInClRyxy1vBKZMyVqmaOWVyJzR5o6deoi59yYttY7kRG1lo5EPKL1Oed+K+m3kjRmzBg3ZcqUE3jKzuHtIZgSdIxjQubOF7W8EpkzJWqZo5ZXInOmRC1z1PJKZM6UqGWOWl6JzEE4kW813CBpULPbAyVtOrE4AAAAAIATKWqvShpmZieZWbakqyU91jGxAAAAAKD7Ou6pj865pJl9UdLT8k7Pf5dz7q0OSwYAAAAA3dQJfdGFc+5JSU92UBYAAAAAgE5s6iMAAAAAoBNQ1AAAAAAgZChqAAAAABAyFDUAAAAACBmKGgAAAACEjDnnMvdkZtslrc3YE7ZfiaQdQYc4RmTufFHLK5E5U6KWOWp5JTJnStQyRy2vROZMiVrmqOWVyNyRKpxzpW2tlNGiFlZmttA5NyboHMeCzJ0vanklMmdK1DJHLa9E5kyJWuao5ZXInClRyxy1vBKZg8DURwAAAAAIGYoaAAAAAIQMRc3z26ADHAcyd76o5ZXInClRyxy1vBKZMyVqmaOWVyJzpkQtc9TySmTOOI5RAwAAAICQYUQNAAAAAEKGogYAAAAAIUNRQ6cxX9A5AAAAgKjplkXN7w8FZpYIOkt7mVm2mfUKOkd7mFm2JDnfYfeFsriZWb5/Gcp8LTGzgWZ2ppnlBp2lvcxshJldFXSO9vLfK8rM7JzG13VUmFlfMzvLzHoGneVYROl3MKqiuI2jmBloSRRfy+x4D05kikpHMbPzJH1B3n/7fDP7/5xzO/377PBiEQZmdrmkqyQNMLP/lfSypKGSdjvn3gk0XMu+amZnS1ogaYlz7lH/drZzbnbA2VrzYzN7wzn3GzOLS6qUNFjSBufcymCjterbklY45970S/wESR+TtEHS3c65LUGGa8Utkr5oZh+X9EtJ8xrvCOPvnqR/kvQheTu17jaz5ZLOk7RL0l+cc/uCDNcSM7tA0qcl7ZdUKumAmS2TdL9zbn2g4dqh8XVgZjH/djrYRF1PSH/XjqqFnX6xML82wvp5or38D+UW5m18OP89w0nhfo2HOVtrmmeO2msj6n9LuuOI2v9IulPSzyWNkvT//A/mkvQpMzs1sGSt+4a804t+T94H3Xsk3SDpu2b2kQBzteZ0SX0k1Ui61Mz+LOl+SdP9PfxZgaZr2Wk6WBq+IOluSdPkbePzggrVhhGSZvnXfyTpWklvShoo6bKgQrVhlKQPS3pL0s2SJrU08hoi10n6saTvSPqSvPePEklTJV0SYK6j+aG81++vJS2UlCcpX9J/m9nQAHMdlZn1MrNPm9kFZpbtnEtH9Q9rmJlZbzP7lJmN8G+H/nOAmQ0ys8+YWWXjsrC+NprPKAk6S3uZWamZjWy+zH9bDuU2liQzG2Zmn2s+08F/zwjt3xMzG21ms8zsA0FnaS8zy/JnlPynmQ2XIvHa6GFm15rZ+WaWFfW/Jd1qRM3MyiVlOecaP9w+a2YvS5ou6S5J35T0qaDytcTPHHfO/c2//YS8EmSSLpJ0i5nNc87tDTDmIZxz15vZ9yX1lfRdScWSnpZULen7km6StDm4hIfyt3Gpc26xv+iz8kZNnKSL5W3jBWHaxmaWJ+k9SeWSlskbATxP3u/0SZJmmNljzrlNgYU8jJn1l1TknJttZq/J284PmdmLkv7HOfd6sAkPZWZ9JMWcc3P82+Ml9ZCUI2msvBL/N+fctgBjHsLPnHTOPe8vWmxmL0n6Z3k7Hj5tZt9zzqUCC9kCM7tZXoHfJekDkoab2Xvydkrd65zbE2S+lpjZQElpSTudc7WH3ZfjnKsLJlnrzGyavL8b+yVd4M8oec2/L9s5Vx9owBaY2efkzRZISCoxs0fk7eTZKW/mwNYg87XgP8zsenk7S5Y45x4ys3MlDXXO/T7YaK36R0l1kpb4hwGMkbeTaoW837/QvMc1c528WTr1ZtZP3vvb1ZJelPSbkM42+qi8v883mtkA59zjUuhHX2+Vt4P1gKTLzWy+pG9Jek3S7c65NQFmO4KZ3ShpnKQdki6X1N/MXpd0h6SZzrmGIPMdj9DvSetgJ0l6w8zy7eDxabdIutLMLpW0N4TT3IbL2ysuf2/ifzvndvnTNR+TNCxkBaJxDvMv5L3xl8srPJucc1+U9CXnXGhKmq9CUrmZvWxmz0va4Zzb4Zx7X9JfJJ0apm0sSc65Gkm3SfqWmf1K0j55HwQaJO2WlBemkuY7U9IiSXLO7XHO3SZvCu9bkr5iZlODDNeCpKQFZrbczO6XtNg51+Ccq/an8BaH8ANMg6TXzOxhM7vRzP5V0n7n3Fp5O6OuDFtJ802TNMM593nn3Hh5Uza/I+8D48elUB7XMUvSnyR9xx8JHOl/YJS838vPB5itNdMkPSxvp+QSSbc3m0XyOTML1Y5K32Xy3oe/JO+D+PclrZZUJW8WQdheG6/J+2x1iqR/NLOVkh6X9Bn/NRLGY4onSnrBv/4NSZ+T9I68bXy1FLptLEmTJT3qX/+JpFx57xk9JX3TzAqCCnYUkyX9u6TFkr5vZr8ws74hLmmSN/X/LufczZKulDet/k55M3e+ZOE7dvtqSY86574l773jLkkPSfqgvNd5GF/LR9WtRtQkzZW0Vt7IbdLfg7jMzB6SN7XwkWDjHck596KZzfGvr5H3S97oBkmhGoVofMNxzm3xpzx+Tt4e8sZj01YHla01zrl5knqb2Th5e5vXNbv7Bnl/eEPF3wO30My+Ke+D7GhJi/y9Xe9I+kOgAVs2W97voBqnGzvn9pvZryV9Vd6bamiOYXTO7TGzf5GXa5+kSjP7i7zXcLkOfrAJDefcXjP7hrxZAhPkjZx8xb/7WvlFOUz8qdApNdtx6JxLSnrMzN6Q9Bczm++cWxFUxsP5H7Zz5ZWGk+S9Rm6WtNPM5kr6jPwPuGHhj8IPcs79yV/0c3/b/5e8Y6AvkbenPDT8zOXOub/4t7MlfdU5t9HMZkl6wMwed869G2jQZpxzD5vZLnk7AB/wR3zWyDt2+HF579eLj/IQGeW/lkfKG3k4Rd6sovP8bVwh6T4zezJM29j3hKQbzDv+tlDSL5xzuyU96v8ODpP0RpABm/Nfy32dc4/4t5+SN9PhYTP7naQ/O+eqg8x4OP/3rbektX7+PpL+zd9B+YCZLZC3Q+LNAGM28fP20MEdwm+b2Wh5BX6FpC+b2XLn3PYAYx6zblXU/BKxsdntxmkef5b3h/a5IHK1pbH8NB8e91+Q+fL2FISSc+4NM/u2pK9LutdfbPIP9g0b59wCeSdAaS6uEG7jZoV4nv9m2UveKMTJktY750Lxxtmc//tW719PNVu+XdK/BZXraPw/nPc13van442RV4YfCyrX0TjndpnZL/zrzUfPtihkO3YkyTnX4I/8fc3MTpP3geU9/+5CSYVhKmm+fHl//Gf5o9sy74Q+VfIKTy/n3CsB5mtJP3nT/SskrfPfQ+6UdIaZfUFSH/89MEz6y9/p5E/r/blzbqMkOec2mFnPEBYIydsh9RFJXzez2yXtc85dG3Cm1vSRt5N6nKRLJW1tto3XmlmPkG7j38kb/ftnSZsk3WRmD8rbcZLnnAtNSfOdooM7KrOdc+v9Ha1Xy9vuveXNkgkNfyfDz+Ud77xK3s6GMknbzKy3pJwwfdbw894u75CKpyRlSTrgz0B72sx+FbWSJnlnbQk6QyiYWY68YzvCOC3oCOYdAJ4lqT7kw+aR1Tg8zvbtfCGfo3+IKGWNCn8q+vnyRqXOllQrab6kvZI2Ouf+M8B4h2j8/++PRuXIy+oa/3aYWZWk/3LOXRxkzuaaZc6Xd5z2HjOLO+dS5p2R91FJTzvnPh1w1CbNMmdLSh3+t9nMPi3pk865y4NJ2DJrdjZK/4P4v8nbtleYWcIfLQ6Fw14XQ+QdanHAOfeUf/+nJF3lnLsiyJyt8aft3iRpvLxj4V+WdyzVaufcL4PM1lyz7ZzjnKvz3+9SzXa8f1jSaOfcj4JNeiR/JO1iSdsk7ZH0M3nveRvkff4M1RRv/7V8jbzML8k7jnWnmX1C0jTn3CcDDXgcKGoAgMD4oyJ7Dlt2urwPjqudc0uDSdY6Myv2p1k1X5bljw6OlFQbtlHAVjLHnHNpM/uJpHecc78JKF6LWsnceJbmL0ta45x7OPPJWtbKa/njkt5zzr0VtqImtbqNE/7hIZ+Td3x5qGYPtLKdT5I3aryucUQwTMysl3Nu12HLslyIT27RynY+Vd703a2S/tg4oyAMWslr8mZynS/v/AOhm/7flu52MhEAQEiYd/KNFWb2kpn9zMwuNrN859wy550R7Up/SmFo+JnfMbM5ZvZj875OILfZB65LJYVqes1RMjeesnq1pD8GGPEIR8ncfHQtNMe0NnstN+b9qJnlOece80vadyQVBZ2zuWbb+CUzu83MLvK3cWOZLJA3KhEah23nn5rZx/z3jNXOubmSPh/S94y3W3vPMLPvhzRz43vzT83sQv/1/LZz7n/lfc9saE6M08Lfko/5eZ3/PvcBedM3I4cRNQBAIMw7jfnNkv5V3nHCY+R9rcc6eX9UP+Wc69f6I2TeUTKvkZf5Gudc38ACtqCNzGvkZS4JKl9L2si8Wl7m0sACHqYdr4urIvZaDt02lrrse0aUXhvr5b02rnDOlQWX8FDteC1fHbb35fbqVicTAQCEygp5p7hf4Jyb609rO0netMcfKpwneGor87NBhmtFW5mfDjJcK9rK/EyQ4VrQFV/LYdvGUtfczlHM/Lcgw7Ugiu/L7cKIGgAgNJodeP8HSU845+5t84cCRubMiFrmqOWVyJwpZO58UcvbGooaACB0zGyCpDedc/uDztJeZM6MqGWOWl6JzJlC5s4XtbyHo6gBAAAAQMhw1kcAAAAACBmKGgAAAACEDEUNAAAAAEKGogYAAAAAIUNRAwAAAICQ+f8BsJdqzYmXcpQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "distorsions = []\n",
    "max_loop=20\n",
    "for k in range(2, max_loop):\n",
    "    kmeans_test = KMeans(n_clusters=k)\n",
    "    kmeans_test.fit(X)\n",
    "    distorsions.append(kmeans_test.inertia_)\n",
    "fig = plt.figure(figsize=(15, 5))\n",
    "plt.plot(range(2, max_loop), distorsions)\n",
    "plt.xticks([i for i in range(2, max_loop)], rotation=75)\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Silhouette score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "\n",
    "silhouette_score = []\n",
    "for k in range(2, max_loop):\n",
    "        kmeans_test = KMeans(n_clusters=k,  random_state=10, n_init=10, n_jobs=-1)\n",
    "        kmeans_test.fit(X)        \n",
    "        silhouette_score.append(metrics.silhouette_score(X, kmeans_test.labels_, random_state=10))\n",
    "fig = plt.figure(figsize=(15, 5))\n",
    "plt.plot(range(2, max_loop), silhouette_score)\n",
    "plt.xticks([i for i in range(2, max_loop)], rotation=75)\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the first graph, Within Cluster SSE After K-Means Clustering, we can see that as the number of clusters increase pass 3, the sum of square of errors within clusters plateaus off. From the second graph, Silhouette Score After K-Means Clustering, we can see that there are various parts of the graph where a kink can be seen. Since there is not much a difference in SSE after 7 clusters and that the drop in sihouette score is quite significant between 14 clusters and 15 clusters, I would use 14 clusters in my K-Means model below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 3, 1, 2, 2, 4, 3, 5, 4, 0, 3, 4, 0, 3, 5, 3, 5, 0, 4, 2, 0, 5,\n",
       "       4, 4, 2, 0, 0, 4])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k_means.labels_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.1.2'></a>\n",
    "### 5.1.2. Cluster Visualisation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing how your clusters are formed is no easy task when the number of variables/dimensions in your dataset is very large. One of the methods of visualising a cluster in two-dimensional space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10fc2c216a0>]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "centroids = k_means.cluster_centers_\n",
    "fig = plt.figure(figsize=(16,10))\n",
    "ax = fig.add_subplot(111)\n",
    "scatter = ax.scatter(X.iloc[:,0],X.iloc[:,1], c = k_means.labels_, cmap =\"rainbow\", label = X.index)\n",
    "ax.set_title('k-Means')\n",
    "ax.set_xlabel('Mean Return')\n",
    "ax.set_ylabel('Volatility')\n",
    "plt.colorbar(scatter)\n",
    "\n",
    "# zip joins x and y coordinates in pairs\n",
    "for x,y,name in zip(X.iloc[:,0],X.iloc[:,1],X.index):\n",
    "\n",
    "    label = name\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,10), # distance from text to points (x,y)\n",
    "                 ha='center') # horizontal alignment can be left, right or center\n",
    "    \n",
    "plt.plot(centroids[:,0],centroids[:,1],'sg',markersize=11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking Elements in each cluster "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "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>Company</th>\n",
       "      <th>Cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>MRK</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>VZ</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>PFE</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>XOM</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>WMT</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>IBM</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BA</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CAT</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>UNH</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NKE</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>JPM</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>INTC</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>GS</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CSCO</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AXP</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>TRV</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>UTX</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>WBA</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>HD</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DIS</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CVX</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>MSFT</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>MCD</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>PG</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>KO</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MMM</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Company  Cluster\n",
       "17     MRK        0\n",
       "25      VZ        0\n",
       "20     PFE        0\n",
       "9      XOM        0\n",
       "26     WMT        0\n",
       "12     IBM        0\n",
       "2     AAPL        1\n",
       "3       BA        2\n",
       "4      CAT        2\n",
       "24     UNH        2\n",
       "19     NKE        2\n",
       "15     JPM        3\n",
       "13    INTC        3\n",
       "10      GS        3\n",
       "6     CSCO        3\n",
       "1      AXP        3\n",
       "22     TRV        4\n",
       "23     UTX        4\n",
       "27     WBA        4\n",
       "11      HD        4\n",
       "8      DIS        4\n",
       "5      CVX        4\n",
       "18    MSFT        4\n",
       "16     MCD        5\n",
       "14     JNJ        5\n",
       "21      PG        5\n",
       "7       KO        5\n",
       "0      MMM        5"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_label = pd.concat([pd.DataFrame(X.index), pd.DataFrame(k_means.labels_)],axis = 1)\n",
    "cluster_label.columns =['Company','Cluster']\n",
    "cluster_label.sort_values(by=['Cluster'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.2'></a>\n",
    "## 5.2. Hierarchical Clustering (Agglomerative Clustering)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Initially, each point is considered as a separate cluster, then it recursively clusters the points together depending upon the distance between them. The points are clustered in such a way that the distance between points within a cluster is minimum and distance between the cluster is maximum. Commonly used distance measures are Euclidean distance, Manhattan distance or Mahalanobis distance. Unlike k-means clustering, it is \"bottom-up\" approach.\n",
    "\n",
    "Its primary advantage over other clustering methods is that you don't need to guess in advance how many clusters there might be. Agglomerate Clustering first assigns each data point into its own cluster, and gradually merges clusters until only one remains. It's then up to the user to choose a cutoff threshold and decide how many clusters are present.\n",
    "\n",
    "Python Tip: Though providing the number of clusters is not necessary but Python provides an option of providing the same for easy and simple use.\n",
    "\n",
    "While hierarchical clustering does not have hyperparameters like k-Means, the measure of dissimilarity between clusters (as opposed to individual data points) has an important impact on the clustering result. The options differ as follows:\n",
    "\n",
    "- Single-link: distance between nearest neighbors of two clusters\n",
    "- Complete link: maximum distance between respective cluster members\n",
    "- Group average\n",
    "- Ward’s method: minimize within-cluster variance\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The use of a distance metric makes hierarchical clustering sensitive to scale:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "nclust = 4\n",
    "model = AgglomerativeClustering(n_clusters=nclust, affinity = 'euclidean', linkage = 'ward')\n",
    "clust_labels1 = model.fit_predict(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,10))\n",
    "ax = fig.add_subplot(111)\n",
    "scatter = ax.scatter(X.iloc[:,0],X.iloc[:,1], c =clust_labels1, cmap =\"rainbow\")\n",
    "ax.set_title('Hierarchial')\n",
    "ax.set_xlabel('Mean Return')\n",
    "ax.set_ylabel('Volatility')\n",
    "plt.colorbar(scatter)\n",
    "\n",
    "# zip joins x and y coordinates in pairs\n",
    "for x,y,name in zip(X.iloc[:,0],X.iloc[:,1],X.index):\n",
    "\n",
    "    label = name\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,10), # distance from text to points (x,y)\n",
    "                 ha='center') # horizontal alignment can be left, right or center"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this instance, the results between k-means and hierarchical clustering were pretty similar. This is not always the case, however. In general, the advantage of agglomerative hierarchical clustering is that it tends to produce more accurate results. The downside is that hierarchical clustering is more difficult to implement and more time/resource consuming than k-means."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.2.1'></a>\n",
    "### 5.2.1. Visualisation : Building Hierarchy Graph/ Dendogram\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next step is to look for clusters of correlations using the agglomerate hierarchical clustering technique. \n",
    "The hierarchy class has a dendrogram method which takes the value returned by the linkage method of the same class. The linkage method takes the dataset and the method to minimize distances as parameters. We use 'ward' as the method since it minimizes then variants of distances between the clusters.\n",
    "\n",
    "Linkage does the actual clustering in one line of code, and returns a list of the clusters joined in the format: Z=[stock_1, stock_2, distance, sample_count]\n",
    "\n",
    "There are also different options for the measurement of the distance. The option we will choose is the average distance measurement, but others are possible (ward, single, centroid, etc.).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([20.        , 25.        ,  0.06407423,  2.        ])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.cluster.hierarchy import dendrogram, linkage, ward\n",
    "\n",
    "#Calulate linkage\n",
    "Z= linkage(X, method='ward')\n",
    "Z[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best way to visualize an agglomerate clustering algorithm is through a dendogram, which displays a cluster tree, the leaves being the individual stocks and the root being the final single cluster. The \"distance\" between each cluster is shown on the y-axis, and thus the longer the branches are, the less correlated two clusters are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot Dendogram\n",
    "plt.figure(figsize=(10, 7))\n",
    "plt.title(\"Stocks Dendograms\")\n",
    "dendrogram(Z,labels = X.index)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once one big cluster is formed, the longest vertical distance without any horizontal line passing through it is selected and a horizontal line is drawn through it. The number of vertical lines this newly created horizontal line passes is equal to number of clusters.\n",
    "Then we select the distance threshold to cut the dendrogram to obtain the selected clustering level. The output is the cluster labelled for each row of data. As expected from the dendrogram, a cut at 2.5 gives us 5 clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 3, 5, 4, 1], dtype=int64)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distance_threshold = 2.5\n",
    "clusters = fcluster(Z, distance_threshold, criterion='distance')\n",
    "chosen_clusters = pd.DataFrame(data=clusters, columns=['cluster'])\n",
    "\n",
    "chosen_clusters['cluster'].unique()\n",
    "# array([4, 5, 2, 3, 1], dtype=int64)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cophenetic Correlation coefficient"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's important to get a sense of how well the clustering performs. One measure is the Cophenetic Correlation Coefficient,  c . This compares (correlates) the actual pairwise distances of all your samples to those implied by the hierarchical clustering. The closer  c  is to 1, the better the clustering preserves the original distances. Generally  c  > 0.7 is consistered a good cluster fit. Of course, other accuracy checks are possible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.693558090937627"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.cluster.hierarchy import cophenet\n",
    "from scipy.spatial.distance import pdist\n",
    "import pylab\n",
    "c, coph_dists = cophenet(Z, pdist(X))\n",
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "According to the dendogram above, the two most correlated stocks PAYX and ADP. First, does this intuitively make sense? Doing a quick look at PAYX and ADP, it seems like they are both in the business of taxes, payroll, HR, retirement and insurance. So it makes sense that they would be strongly correlated. Let's plot them below to visually see how well they correlate. In addition, let's pick two stocks that are not well correlated at all to compare to, say, NVDA and WDC."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.2.2'></a>\n",
    "### 5.2.2. Compare linkage types"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hierarchical clustering provides insight into degrees of similarity among observations as it continues to merge data. A significant change in the similarity metric from one merge to the next suggests a natural clustering existed prior to this point. The dendrogram visualizes the successive merges as a binary tree, displaying the individual data points as leaves and the final merge as the root of the tree. It also shows how the similarity monotonically decreases from bottom to top. Hence, it is natural to select a clustering by cutting the dendrogram.\n",
    "\n",
    "The following figure illustrates the dendrogram for the classic Iris dataset with four classes and three features using the four different distance metrics introduced above. It evaluates the fit of the hierarchical clustering using the cophenetic correlation coefficient that compares the pairwise distances among points and the cluster similarity metric at which a pairwise merge occurred. A coefficient of 1 implies that closer points always merge earlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "methods = ['single', 'complete', 'average', 'ward']\n",
    "pairwise_distance = pdist(rescaledDataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(15, 8), nrows=2, ncols=2, sharex=True)\n",
    "axes = axes.flatten()\n",
    "for i, method in enumerate(methods):\n",
    "    Z = linkage(X, method)\n",
    "    c, coph_dists = cophenet(Z, pairwise_distance)\n",
    "    dendrogram(Z, labels=X.index,\n",
    "        orientation='top', leaf_rotation=0., \n",
    "        leaf_font_size=8., ax = axes[i])\n",
    "    axes[i].set_title('Method: {} | Correlation: {:.2f}'.format(\n",
    "                                                method.capitalize(), c))\n",
    "    \n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Different linkage methods produce different dendrogram ‘looks’ so that we can not use this visualization to compare results across methods. In addition, the Ward method that minimizes the within-cluster variance may not properly reflect the change in variance but the total variance that may be misleading. Instead, other quality metrics like the cophenetic correlation or measures like inertia if aligned with the overall goal are more appropriate."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "The strengths of hierarchical clustering include that:\n",
    "\n",
    "* You do not need to specify the number of clusters but instead offers insight about potential clustering by means of an intuitive visualization.\n",
    "\n",
    "* It produces a hierarchy of clusters that can serve as a taxonomy.\n",
    "\n",
    "* It can be combined with k-means to reduce the number of items at the start of the agglomerative process.\n",
    "\n",
    "The weaknesses include:\n",
    "\n",
    "* The high cost in terms of computation and memory because of the numerous similarity matrix updates.\n",
    "\n",
    "* Another downside is that all merges are final so that it does not achieve the global optimum. \n",
    "\n",
    "* Furthermore, the curse of dimensionality leads to difficulties with noisy, high-dimensional data.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.3'></a>\n",
    "## 5.3. Affinity Propagation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It does not require the number of cluster to be estimated and provided before starting the algorithm. It makes no assumption regarding the internal structure of the data points\n",
    "\n",
    "The algorithm exchanges messages between pairs of data points until a set of exemplars emerges, with each exemplar corresponding to a cluster. The Affinity Propagation algorithm takes as input a real number s(k,k) for each data point k — referred to as a “preference”. Data points with large values for s(k,k) are more likely to be exemplars. The number of clusters is influenced by the preference values and the message-passing procedure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "ap = AffinityPropagation(damping = 0.5, max_iter = 250, affinity = 'euclidean')\n",
    "ap.fit(X)\n",
    "clust_labels2 = ap.predict(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,10))\n",
    "ax = fig.add_subplot(111)\n",
    "scatter = ax.scatter(X.iloc[:,0],X.iloc[:,1], c =clust_labels2, cmap =\"rainbow\")\n",
    "ax.set_title('Affinity')\n",
    "ax.set_xlabel('Mean Return')\n",
    "ax.set_ylabel('Volatility')\n",
    "plt.colorbar(scatter)\n",
    "\n",
    "# zip joins x and y coordinates in pairs\n",
    "for x,y,name in zip(X.iloc[:,0],X.iloc[:,1],X.index):\n",
    "\n",
    "    label = name\n",
    "\n",
    "    plt.annotate(label, # this is the text\n",
    "                 (x,y), # this is the point to label\n",
    "                 textcoords=\"offset points\", # how to position the text\n",
    "                 xytext=(0,10), # distance from text to points (x,y)\n",
    "                 ha='center') # horizontal alignment can be left, right or center"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.3.1'></a>\n",
    "### 5.3.1 Cluster Visualisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster_centers_indices = ap.cluster_centers_indices_\n",
    "labels = ap.labels_\n",
    "n_clusters_ = len(cluster_centers_indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated number of clusters: 6\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cluster_centers_indices = ap.cluster_centers_indices_\n",
    "labels = ap.labels_\n",
    "no_clusters = len(cluster_centers_indices)\n",
    "\n",
    "print('Estimated number of clusters: %d' % no_clusters)\n",
    "# Plot exemplars\n",
    "\n",
    "X_temp=np.asarray(X)\n",
    "plt.close('all')\n",
    "plt.figure(1)\n",
    "plt.clf()\n",
    "\n",
    "fig = plt.figure(figsize=(8,6))\n",
    "colors = cycle('bgrcmykbgrcmykbgrcmykbgrcmyk')\n",
    "for k, col in zip(range(n_clusters_), colors):\n",
    "    class_members = labels == k\n",
    "    cluster_center = X_temp[cluster_centers_indices[k]]\n",
    "    plt.plot(X_temp[class_members, 0], X_temp[class_members, 1], col + '.')\n",
    "    plt.plot(cluster_center[0], cluster_center[1], 'o', markerfacecolor=col, markeredgecolor='k', markersize=14)\n",
    "    for x in X_temp[class_members]:\n",
    "        plt.plot([cluster_center[0], x[0]], [cluster_center[1], x[1]], col)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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>Company</th>\n",
       "      <th>Cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MMM</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CVX</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>MCD</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>UTX</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>TRV</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>MSFT</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DIS</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>HD</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>JPM</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>INTC</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CSCO</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AXP</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>GS</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CAT</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NKE</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BA</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>UNH</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>IBM</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>WMT</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>XOM</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>KO</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>MRK</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>PFE</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>PG</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>VZ</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>WBA</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Company  Cluster\n",
       "0      MMM        0\n",
       "5      CVX        0\n",
       "16     MCD        0\n",
       "14     JNJ        0\n",
       "2     AAPL        1\n",
       "23     UTX        2\n",
       "22     TRV        2\n",
       "18    MSFT        2\n",
       "8      DIS        2\n",
       "11      HD        2\n",
       "15     JPM        3\n",
       "13    INTC        3\n",
       "6     CSCO        3\n",
       "1      AXP        3\n",
       "10      GS        3\n",
       "4      CAT        4\n",
       "19     NKE        4\n",
       "3       BA        4\n",
       "24     UNH        4\n",
       "12     IBM        5\n",
       "26     WMT        5\n",
       "9      XOM        5\n",
       "7       KO        5\n",
       "17     MRK        5\n",
       "20     PFE        5\n",
       "21      PG        5\n",
       "25      VZ        5\n",
       "27     WBA        5"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_label = pd.concat([pd.DataFrame(X.index), pd.DataFrame(ap.labels_)],axis = 1)\n",
    "cluster_label.columns =['Company','Cluster']\n",
    "cluster_label.sort_values(by=['Cluster'])"
   ]
  }
 ],
 "metadata": {
  "_change_revision": 206,
  "_is_fork": false,
  "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}