2.absenteeism-at-work-clustering.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "# Absenteeism at Work - Clustering\n",
    "CSE4063 - Data Mining Project-2 part-2\n",
    "\n",
    "**Absenteeism at work Data Set**  \n",
    "https://archive.ics.uci.edu/ml/datasets/Absenteeism+at+work"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [],
   "source": [
    "# import packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import ShuffleSplit, GridSearchCV\n",
    "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n",
    "from sklearn.preprocessing import StandardScaler, OneHotEncoder, MinMaxScaler\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.manifold import TSNE\n",
    "import plotly.express as px\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.inspection import permutation_importance\n",
    "from sklearn.cluster import AgglomerativeClustering \n",
    "from sklearn.metrics import silhouette_samples, silhouette_score, homogeneity_score, completeness_score, v_measure_score, adjusted_rand_score, adjusted_mutual_info_score, fowlkes_mallows_score\n",
    "from scipy.cluster import hierarchy \n",
    "from scipy.spatial import distance_matrix \n",
    "from sklearn.cluster import DBSCAN \n",
    "import matplotlib.cm as cm"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "# ANALYSING DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Reason for absence</th>\n",
       "      <th>Month of absence</th>\n",
       "      <th>Day of the week</th>\n",
       "      <th>Seasons</th>\n",
       "      <th>Transportation expense</th>\n",
       "      <th>Distance from Residence to Work</th>\n",
       "      <th>Service time</th>\n",
       "      <th>Age</th>\n",
       "      <th>Work load Average/day</th>\n",
       "      <th>Hit target</th>\n",
       "      <th>Disciplinary failure</th>\n",
       "      <th>Education</th>\n",
       "      <th>Son</th>\n",
       "      <th>Social drinker</th>\n",
       "      <th>Social smoker</th>\n",
       "      <th>Pet</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Height</th>\n",
       "      <th>Body mass index</th>\n",
       "      <th>Absenteeism time in hours</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>11</th>\n",
       "      <td>26</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>289</td>\n",
       "      <td>36</td>\n",
       "      <td>13</td>\n",
       "      <td>33</td>\n",
       "      <td>239.554</td>\n",
       "      <td>97</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>90</td>\n",
       "      <td>172</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>118</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>50</td>\n",
       "      <td>239.554</td>\n",
       "      <td>97</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>98</td>\n",
       "      <td>178</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>179</td>\n",
       "      <td>51</td>\n",
       "      <td>18</td>\n",
       "      <td>38</td>\n",
       "      <td>239.554</td>\n",
       "      <td>97</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>89</td>\n",
       "      <td>170</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>279</td>\n",
       "      <td>5</td>\n",
       "      <td>14</td>\n",
       "      <td>39</td>\n",
       "      <td>239.554</td>\n",
       "      <td>97</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>168</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>23</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>289</td>\n",
       "      <td>36</td>\n",
       "      <td>13</td>\n",
       "      <td>33</td>\n",
       "      <td>239.554</td>\n",
       "      <td>97</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>90</td>\n",
       "      <td>172</td>\n",
       "      <td>30</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Reason for absence  Month of absence  Day of the week  Seasons  \\\n",
       "ID                                                                   \n",
       "11                  26                 7                3        1   \n",
       "36                   0                 7                3        1   \n",
       "3                   23                 7                4        1   \n",
       "7                    7                 7                5        1   \n",
       "11                  23                 7                5        1   \n",
       "\n",
       "    Transportation expense  Distance from Residence to Work  Service time  \\\n",
       "ID                                                                          \n",
       "11                     289                               36            13   \n",
       "36                     118                               13            18   \n",
       "3                      179                               51            18   \n",
       "7                      279                                5            14   \n",
       "11                     289                               36            13   \n",
       "\n",
       "    Age  Work load Average/day   Hit target  Disciplinary failure  Education  \\\n",
       "ID                                                                             \n",
       "11   33                 239.554          97                     0          1   \n",
       "36   50                 239.554          97                     1          1   \n",
       "3    38                 239.554          97                     0          1   \n",
       "7    39                 239.554          97                     0          1   \n",
       "11   33                 239.554          97                     0          1   \n",
       "\n",
       "    Son  Social drinker  Social smoker  Pet  Weight  Height  Body mass index  \\\n",
       "ID                                                                             \n",
       "11    2               1              0    1      90     172               30   \n",
       "36    1               1              0    0      98     178               31   \n",
       "3     0               1              0    0      89     170               31   \n",
       "7     2               1              1    0      68     168               24   \n",
       "11    2               1              0    1      90     172               30   \n",
       "\n",
       "    Absenteeism time in hours  \n",
       "ID                             \n",
       "11                          4  \n",
       "36                          0  \n",
       "3                           2  \n",
       "7                           4  \n",
       "11                          2  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data\n",
    "data = pd.read_csv(\"../input/absenteeism-at-work-uci-ml-repositiory/Absenteeism_at_work.csv\",\n",
    "                        sep=';', index_col=\"ID\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 740 entries, 11 to 35\n",
      "Data columns (total 20 columns):\n",
      " #   Column                           Non-Null Count  Dtype  \n",
      "---  ------                           --------------  -----  \n",
      " 0   Reason for absence               740 non-null    int64  \n",
      " 1   Month of absence                 740 non-null    int64  \n",
      " 2   Day of the week                  740 non-null    int64  \n",
      " 3   Seasons                          740 non-null    int64  \n",
      " 4   Transportation expense           740 non-null    int64  \n",
      " 5   Distance from Residence to Work  740 non-null    int64  \n",
      " 6   Service time                     740 non-null    int64  \n",
      " 7   Age                              740 non-null    int64  \n",
      " 8   Work load Average/day            740 non-null    float64\n",
      " 9   Hit target                       740 non-null    int64  \n",
      " 10  Disciplinary failure             740 non-null    int64  \n",
      " 11  Education                        740 non-null    int64  \n",
      " 12  Son                              740 non-null    int64  \n",
      " 13  Social drinker                   740 non-null    int64  \n",
      " 14  Social smoker                    740 non-null    int64  \n",
      " 15  Pet                              740 non-null    int64  \n",
      " 16  Weight                           740 non-null    int64  \n",
      " 17  Height                           740 non-null    int64  \n",
      " 18  Body mass index                  740 non-null    int64  \n",
      " 19  Absenteeism time in hours        740 non-null    int64  \n",
      "dtypes: float64(1), int64(19)\n",
      "memory usage: 121.4 KB\n"
     ]
    }
   ],
   "source": [
    "# data types\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Reason for absence</th>\n",
       "      <th>Month of absence</th>\n",
       "      <th>Day of the week</th>\n",
       "      <th>Seasons</th>\n",
       "      <th>Transportation expense</th>\n",
       "      <th>Distance from Residence to Work</th>\n",
       "      <th>Service time</th>\n",
       "      <th>Age</th>\n",
       "      <th>Work load Average/day</th>\n",
       "      <th>Hit target</th>\n",
       "      <th>Disciplinary failure</th>\n",
       "      <th>Education</th>\n",
       "      <th>Son</th>\n",
       "      <th>Social drinker</th>\n",
       "      <th>Social smoker</th>\n",
       "      <th>Pet</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Height</th>\n",
       "      <th>Body mass index</th>\n",
       "      <th>Absenteeism time in hours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>19.216216</td>\n",
       "      <td>6.324324</td>\n",
       "      <td>3.914865</td>\n",
       "      <td>2.544595</td>\n",
       "      <td>221.329730</td>\n",
       "      <td>29.631081</td>\n",
       "      <td>12.554054</td>\n",
       "      <td>36.450000</td>\n",
       "      <td>271.490235</td>\n",
       "      <td>94.587838</td>\n",
       "      <td>0.054054</td>\n",
       "      <td>1.291892</td>\n",
       "      <td>1.018919</td>\n",
       "      <td>0.567568</td>\n",
       "      <td>0.072973</td>\n",
       "      <td>0.745946</td>\n",
       "      <td>79.035135</td>\n",
       "      <td>172.114865</td>\n",
       "      <td>26.677027</td>\n",
       "      <td>6.924324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.433406</td>\n",
       "      <td>3.436287</td>\n",
       "      <td>1.421675</td>\n",
       "      <td>1.111831</td>\n",
       "      <td>66.952223</td>\n",
       "      <td>14.836788</td>\n",
       "      <td>4.384873</td>\n",
       "      <td>6.478772</td>\n",
       "      <td>39.058116</td>\n",
       "      <td>3.779313</td>\n",
       "      <td>0.226277</td>\n",
       "      <td>0.673238</td>\n",
       "      <td>1.098489</td>\n",
       "      <td>0.495749</td>\n",
       "      <td>0.260268</td>\n",
       "      <td>1.318258</td>\n",
       "      <td>12.883211</td>\n",
       "      <td>6.034995</td>\n",
       "      <td>4.285452</td>\n",
       "      <td>13.330998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>118.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>205.917000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>163.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>244.387000</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>169.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>23.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>264.249000</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>170.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>26.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>260.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>294.217000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>172.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>28.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>388.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>378.884000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>196.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>120.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Reason for absence  Month of absence  Day of the week     Seasons  \\\n",
       "count          740.000000        740.000000       740.000000  740.000000   \n",
       "mean            19.216216          6.324324         3.914865    2.544595   \n",
       "std              8.433406          3.436287         1.421675    1.111831   \n",
       "min              0.000000          0.000000         2.000000    1.000000   \n",
       "25%             13.000000          3.000000         3.000000    2.000000   \n",
       "50%             23.000000          6.000000         4.000000    3.000000   \n",
       "75%             26.000000          9.000000         5.000000    4.000000   \n",
       "max             28.000000         12.000000         6.000000    4.000000   \n",
       "\n",
       "       Transportation expense  Distance from Residence to Work  Service time  \\\n",
       "count              740.000000                       740.000000    740.000000   \n",
       "mean               221.329730                        29.631081     12.554054   \n",
       "std                 66.952223                        14.836788      4.384873   \n",
       "min                118.000000                         5.000000      1.000000   \n",
       "25%                179.000000                        16.000000      9.000000   \n",
       "50%                225.000000                        26.000000     13.000000   \n",
       "75%                260.000000                        50.000000     16.000000   \n",
       "max                388.000000                        52.000000     29.000000   \n",
       "\n",
       "              Age  Work load Average/day   Hit target  Disciplinary failure  \\\n",
       "count  740.000000              740.000000  740.000000            740.000000   \n",
       "mean    36.450000              271.490235   94.587838              0.054054   \n",
       "std      6.478772               39.058116    3.779313              0.226277   \n",
       "min     27.000000              205.917000   81.000000              0.000000   \n",
       "25%     31.000000              244.387000   93.000000              0.000000   \n",
       "50%     37.000000              264.249000   95.000000              0.000000   \n",
       "75%     40.000000              294.217000   97.000000              0.000000   \n",
       "max     58.000000              378.884000  100.000000              1.000000   \n",
       "\n",
       "        Education         Son  Social drinker  Social smoker         Pet  \\\n",
       "count  740.000000  740.000000      740.000000     740.000000  740.000000   \n",
       "mean     1.291892    1.018919        0.567568       0.072973    0.745946   \n",
       "std      0.673238    1.098489        0.495749       0.260268    1.318258   \n",
       "min      1.000000    0.000000        0.000000       0.000000    0.000000   \n",
       "25%      1.000000    0.000000        0.000000       0.000000    0.000000   \n",
       "50%      1.000000    1.000000        1.000000       0.000000    0.000000   \n",
       "75%      1.000000    2.000000        1.000000       0.000000    1.000000   \n",
       "max      4.000000    4.000000        1.000000       1.000000    8.000000   \n",
       "\n",
       "           Weight      Height  Body mass index  Absenteeism time in hours  \n",
       "count  740.000000  740.000000       740.000000                 740.000000  \n",
       "mean    79.035135  172.114865        26.677027                   6.924324  \n",
       "std     12.883211    6.034995         4.285452                  13.330998  \n",
       "min     56.000000  163.000000        19.000000                   0.000000  \n",
       "25%     69.000000  169.000000        24.000000                   2.000000  \n",
       "50%     83.000000  170.000000        25.000000                   3.000000  \n",
       "75%     89.000000  172.000000        31.000000                   8.000000  \n",
       "max    108.000000  196.000000        38.000000                 120.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# min and max values\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# divide columns to numerical and categorical ones\n",
    "categorical_atts = ['Reason for absence','Month of absence','Day of the week',\n",
    "                     'Seasons','Disciplinary failure', 'Education', 'Social drinker',\n",
    "                     'Social smoker', 'Pet', 'Son']\n",
    "numerical_atts = data.drop(columns=categorical_atts).columns.to_list()\n",
    "\n",
    "# update types of categorical columns \n",
    "#for cat in categorical_atts:\n",
    "#    data[cat] = data[cat].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Reason for absence      28\n",
       "Month of absence        13\n",
       "Day of the week          5\n",
       "Seasons                  4\n",
       "Disciplinary failure     2\n",
       "Education                4\n",
       "Social drinker           2\n",
       "Social smoker            2\n",
       "Pet                      6\n",
       "Son                      5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of unique values in categorical atts\n",
    "data[categorical_atts].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/categorical.py:3695: UserWarning: The `size` parameter has been renamed to `height`; please update your code.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f9abaa94ed0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot distribution of \"reason for absence\" column\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.catplot(data=data, x='Reason for absence', kind= 'count',size=4, aspect=4, palette='muted')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot distribution of numerical attributes\n",
    "num_df = data[numerical_atts]\n",
    "plt.figure(figsize=(20,20))\n",
    "for i in range(1, 11):\n",
    "    plt.subplot(4, 3, i)\n",
    "    sns.distplot(num_df[num_df.columns[i-1]],bins=14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# correlation matrix\n",
    "num_corr = num_df.corr()\n",
    "plt.figure(figsize=(10,6))\n",
    "sns.heatmap(num_corr, annot=True, fmt=\".3f\",vmin=-1, vmax=1, linewidths=.5, cmap = sns.color_palette(\"RdBu\", 100))\n",
    "plt.yticks(rotation=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# display boxlots\n",
    "plt.figure(figsize=(8,8))\n",
    "sns.boxplot(x=\"variable\", y=\"value\", data=pd.melt(num_df))\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "# OUTLIER DETECTION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check for outliers using boxplots and drop them\n",
    "for num_att in numerical_atts:\n",
    "    # Getting 75 and 25 percentile of variable \"i\"\n",
    "    Q3, Q1 = np.percentile(data[num_att], [75,25])\n",
    "    MEAN = data[num_att].mean()\n",
    "    \n",
    "    # Calculating Interquartile range\n",
    "    IQR = Q3 - Q1\n",
    "    \n",
    "    # Calculating upper extream and lower extream\n",
    "    minimum = Q1 - (IQR*1.5)\n",
    "    maximum = Q3 + (IQR*1.5)\n",
    "    \n",
    "    # Replacing all the outliers value to Mean\n",
    "    data_clean=data.drop(data.loc[data[num_att]< minimum,num_att].index) \n",
    "    data_clean=data.drop(data.loc[data[num_att]> maximum,num_att].index) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "150"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# size reduced to 150 from 740\n",
    "len(data_clean)"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "# NORMALIZATION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform data\n",
    "numeric_transformer = MinMaxScaler()\n",
    "#categorical_transformer = OneHotEncoder(sparse=False, handle_unknown='ignore')\n",
    "\n",
    "# exclude target attr,bute\n",
    "numerical_atts = [x for x in numerical_atts if x not in ['Absenteeism time in hours']]\n",
    "preprocessor = ColumnTransformer(\n",
    "    transformers=[\n",
    "        ('num', numeric_transformer, numerical_atts),\n",
    "        ('cat', 'passthrough', categorical_atts)\n",
    "    ], remainder='passthrough')\n",
    "data_pp = preprocessor.fit_transform(data_clean)"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "# FEATURE SELECTION"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "**1. w Random Forest importances:**\n",
    "\n",
    "Train a RF model to see feature importances. It's ok, we are already have target attribute in the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The best parameters are {'n_estimators': 1000} with a score of 0.7133\n"
     ]
    }
   ],
   "source": [
    "# X, y splitting (we dont need train test splitting since this model is just for feature importances)\n",
    "y_original = data_pp[:,-1].reshape(-1, 1)\n",
    "y = np.round(MinMaxScaler((0,2)).fit_transform(y_original)).ravel()\n",
    "X = np.delete(data_pp,-1,1) \n",
    "\n",
    "# cross-validation with 10 splits\n",
    "cross_val = ShuffleSplit(n_splits=10, random_state = 42)\n",
    "\n",
    "# define model\n",
    "rf = RandomForestClassifier(random_state = 0,max_features=None,n_jobs=-1)\n",
    "\n",
    "# parameters \n",
    "parameters = {  \n",
    "                \"n_estimators\":[1000],\n",
    "                #'max_depth': list(range(1,11)),\n",
    "                #\"criterion\": [\"gini\",\"entropy\"],\n",
    "                #\"criterion\": [\"mse\",\"mae\"],\n",
    "                #\"class_weight\": [None, \"balanced\"],\n",
    "                #\"max_features\":[\"auto\", None, \"log2\"],\n",
    "                }\n",
    "\n",
    "# grid search for parameters\n",
    "grid = GridSearchCV(estimator=rf, param_grid=parameters, cv=cross_val, n_jobs=-1)#multithreading; all cores are used\n",
    "grid.fit(X,y)\n",
    "\n",
    "# print best scores\n",
    "print(\"The best parameters are %s with a score of %0.4f\"\n",
    "      % (grid.best_params_, grid.best_score_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.patches.Wedge at 0x7f9aab19ee10>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab1ad1d0>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab1adb50>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab139450>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab145350>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab145c10>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab145fd0>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab14f8d0>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab139d50>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab1456d0>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab1c7c90>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab252390>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab165550>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab165e10>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab0f8710>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab0f8fd0>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab1038d0>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab10b1d0>,\n",
       "  <matplotlib.patches.Wedge at 0x7f9aab10ba90>],\n",
       " [Text(-0.1313317475276619, 1.0921318473935877, 'Transportation expense'),\n",
       "  Text(-0.3581127587593462, 1.0400746377129721, 'Distance from Residence to Work'),\n",
       "  Text(-0.5948118466784025, 0.9253101464109366, 'Service time'),\n",
       "  Text(-0.8413521534152558, 0.7086088864412525, 'Age'),\n",
       "  Text(-1.0786359628887607, 0.21574165004244406, 'Work load Average/day '),\n",
       "  Text(-1.027764258844849, -0.3920467169115161, 'Hit target'),\n",
       "  Text(-0.8823204639788816, -0.6568946634309728, 'Weight'),\n",
       "  Text(-0.7636117546052942, -0.7917683298974669, 'Height'),\n",
       "  Text(-0.5050658629874362, -0.977194184410016, 'Body mass index'),\n",
       "  Text(0.7140355146727428, -0.83675162610301, 'Reason for absence'),\n",
       "  Text(1.049786167740627, 0.3285559343862898, 'Month of absence'),\n",
       "  Text(0.8285714358130334, 0.7235118352554631, 'Day of the week'),\n",
       "  Text(0.5455920522182793, 0.9551593126574469, 'Seasons'),\n",
       "  Text(0.43057792989017457, 1.0122265785344169, 'Disciplinary failure'),\n",
       "  Text(0.37644601812945033, 1.0335803768621392, 'Education'),\n",
       "  Text(0.3085749188808197, 1.0558321454841655, 'Social drinker'),\n",
       "  Text(0.2572888536051454, 1.0694870012349613, 'Social smoker'),\n",
       "  Text(0.17364837349563292, 1.0862072741343254, 'Pet'),\n",
       "  Text(0.05227956503916368, 1.0987569554179468, 'Son')])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# pie-chart \n",
    "atts = numerical_atts+categorical_atts\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.pie(grid.best_estimator_.feature_importances_, labels=atts, shadow=True, startangle=90) "
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "Half of the attributes seem close so it's hard to decide how to do elimination. Thus we tried another method called Permutaion importance."
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "**2. w Permutation importance:**\n",
    "\n",
    "see https://scikit-learn.org/stable/modules/permutation_importance.html#permutation-importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reason for absence 0.305 +/- 0.021\n",
      "Day of the week 0.049 +/- 0.013\n",
      "Work load Average/day  0.035 +/- 0.009\n",
      "Body mass index 0.033 +/- 0.007\n",
      "Hit target 0.021 +/- 0.006\n",
      "Seasons  0.009 +/- 0.004\n",
      "Month of absence 0.007 +/- 0.002\n",
      "Transportation expense 0.007 +/- 0.000\n",
      "Age      0.003 +/- 0.003\n",
      "Disciplinary failure 0.000 +/- 0.000\n",
      "Pet      0.000 +/- 0.000\n",
      "Education 0.000 +/- 0.000\n",
      "Height   0.000 +/- 0.000\n",
      "Weight   0.000 +/- 0.000\n",
      "Social drinker 0.000 +/- 0.000\n",
      "Social smoker 0.000 +/- 0.000\n",
      "Service time 0.000 +/- 0.000\n",
      "Distance from Residence to Work 0.000 +/- 0.000\n",
      "Son      0.000 +/- 0.000\n"
     ]
    }
   ],
   "source": [
    "# permutation importance with RF classifier\n",
    "atts_arr = np.array(atts)\n",
    "result = permutation_importance(grid, X, y, n_repeats=10,\n",
    "                                random_state=42, n_jobs=-1)\n",
    "sorted_idx = result.importances_mean.argsort()\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.boxplot(result.importances[sorted_idx].T,\n",
    "           vert=False, labels=atts_arr[sorted_idx])\n",
    "ax.set_title(\"Permutation Importances (train set)\")\n",
    "fig.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "for i in result.importances_mean.argsort()[::-1]:\n",
    "     print(f\"{atts_arr[i]:<8} \"\n",
    "           f\"{result.importances_mean[i]:.3f}\"\n",
    "           f\" +/- {result.importances_std[i]:.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "We choosed 9 attributes based on Permutaion importances w RF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# select important attributes\n",
    "selected_atts = ['Reason for absence', 'Day of the week', 'Work load Average/day','Body mass index','Hit target', \n",
    "                     'Seasons', 'Month of absence', 'Transportation expense', 'Age']\n",
    "\n",
    "selected_atts_idx=np.where(np.isin(atts,selected_atts))[0]\n",
    "X_selected = X[:,selected_atts_idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "# CLUSTERING"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "**1. K-means:**\n",
    "\n",
    "\"inertia_\" attribute provides sum of squared distances of samples to their closest cluster center. Wen can plot it and decide on the parameter \"n_clusters\" by using elbow method.\n",
    "\n",
    "see https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# run k-means for range of 10 clusters then analyse with elbow method\n",
    "clusters = []\n",
    "\n",
    "for i in range(1, 11):\n",
    "    km = KMeans(n_clusters=i).fit(X_selected)\n",
    "    clusters.append(km.inertia_)\n",
    "    \n",
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "sns.lineplot(x=list(range(1, 11)), y=clusters, ax=ax)\n",
    "ax.set_title('Searching for Elbow')\n",
    "ax.set_xlabel('Clusters')\n",
    "ax.set_ylabel('Inertia')\n",
    "\n",
    "# Annotate arrow\n",
    "ax.annotate('Possible Elbow Point', xy=(4, clusters[3]), xytext=(4, clusters[3]+1000), xycoords='data',          \n",
    "             arrowprops=dict(arrowstyle='->', connectionstyle='arc3', color='blue', lw=2))\n",
    "\n",
    "ax.annotate('Possible Elbow Point', xy=(3,clusters[2] ), xytext=(3, clusters[2]+1000), xycoords='data',          \n",
    "             arrowprops=dict(arrowstyle='->', connectionstyle='arc3', color='blue', lw=2))\n",
    "\n",
    "ax.annotate('Possible Elbow Point', xy=(2,clusters[1] ), xytext=(2, clusters[1]+1000), xycoords='data',          \n",
    "             arrowprops=dict(arrowstyle='->', connectionstyle='arc3', color='blue', lw=2))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "Let's try possible elbow points by creating plots. We can use t-SNE for visualizing 9D data on 3D space.\n",
    "\n",
    "see https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"911cb6b3-28d6-4776-b802-ec0ee948a16c\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"911cb6b3-28d6-4776-b802-ec0ee948a16c\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        '911cb6b3-28d6-4776-b802-ec0ee948a16c',\n",
       "                        [{\"hovertemplate\": \"color=g<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"g\", \"marker\": {\"color\": \"#636efa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"g\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [-16.051851272583008, -28.01970863342285, -23.7200984954834, 23.643281936645508, -72.91089630126953, 11.968172073364258, -79.24576568603516, -68.05513763427734, -75.87440490722656, -49.211429595947266, -31.466691970825195, 3.5444746017456055, -27.346542358398438, 5.89685583114624, 7.682126998901367, 13.478333473205566, -49.55375289916992, -14.697940826416016, -0.4247758388519287, -4.524716854095459, 1.9300822019577026, -1.8310210704803467, 11.063920021057129, 15.0502290725708, 24.261194229125977, 26.23409652709961, 23.72462272644043, 32.061439514160156, 41.97663879394531, 39.56591033935547, 0.07558732479810715, -34.93399429321289, -84.41986083984375, -76.68899536132812, -2.0306243896484375, -51.12693405151367, -8.458586692810059, -45.20844650268555, -7.688177585601807, 24.50506019592285, -3.439753532409668, 6.584710597991943, 14.679350852966309, 9.8240385055542, 32.163780212402344, -14.846447944641113, 27.504737854003906, -92.09933471679688, 12.23808479309082, -81.64250183105469, -65.40040588378906, -65.02498626708984, -58.738670349121094, -5.192770004272461, -43.6920166015625, -14.682917594909668, 9.473039627075195, -2.76469349861145, -30.976539611816406, 8.936984062194824, -4.896734714508057, -4.690402030944824], \"y\": [4.4482598304748535, 11.40792465209961, -0.14262452721595764, 73.46062469482422, -26.464393615722656, 88.60043334960938, 15.517782211303711, -25.052114486694336, -2.1702678203582764, 30.691390991210938, -0.4104595184326172, 86.7532730102539, -12.368196487426758, 119.78094482421875, 114.0484848022461, 104.24891662597656, 16.39856719970703, 1.8766013383865356, 0.8861563205718994, 53.82294464111328, 52.78414535522461, 66.535888671875, 58.82744216918945, 41.10039520263672, 63.610595703125, 51.92506790161133, -23.19164276123047, 56.24617385864258, 47.919158935546875, 62.28577423095703, 4.999932289123535, -43.58101272583008, -27.04196548461914, -8.303616523742676, 107.51199340820312, -19.46199607849121, 88.88972473144531, -2.7562646865844727, -12.61686897277832, 17.430078506469727, -15.25459098815918, -12.55990982055664, 1.6315102577209473, -7.39304256439209, 33.13533401489258, -28.882776260375977, 45.677276611328125, -15.132575988769531, 103.4489974975586, -10.048362731933594, -29.55080223083496, 7.568136692047119, 5.82424259185791, 107.51396942138672, -19.462696075439453, -8.347434997558594, 90.91043090820312, 99.93169403076172, -5.69174861907959, 89.82836151123047, 90.24043273925781, 106.4412612915039], \"z\": [80.63272857666016, 48.72231674194336, 37.440189361572266, 90.18350982666016, 64.01304626464844, -6.696622848510742, 26.933799743652344, 32.943450927734375, 26.67510223388672, 14.684473991394043, 96.62628936767578, 13.40608024597168, 85.99493408203125, 11.619553565979004, 28.012550354003906, 14.81717586517334, 30.000110626220703, 50.12711715698242, 82.91858673095703, 76.5682373046875, 92.12594604492188, 88.85021209716797, 59.339168548583984, 59.114662170410156, 69.98632049560547, 51.5333137512207, -113.98896026611328, 95.4275131225586, 60.36748504638672, 81.23568725585938, 26.296035766601562, 29.253244400024414, 47.042179107666016, 64.59676361083984, -2.4596099853515625, 44.96508026123047, 25.963834762573242, 46.35492706298828, 75.65142059326172, 67.55467224121094, 38.683902740478516, 22.485858917236328, 66.26422119140625, 45.806514739990234, 58.27777099609375, 31.6491756439209, 72.30074310302734, 66.96732330322266, -13.049555778503418, 49.83415603637695, 47.38495635986328, 37.11040115356445, 20.859668731689453, 17.68865966796875, 64.80724334716797, 94.19955444335938, 32.08248519897461, 38.850467681884766, 54.964847564697266, -26.91890525817871, -16.869943618774414, -24.56075096130371]}, {\"hovertemplate\": \"color=b<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"b\", \"marker\": {\"color\": \"#EF553B\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"b\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [13.443845748901367, -4.07905387878418, 50.6001091003418, -62.843772888183594, -11.988554000854492, -84.30481719970703, 58.23987579345703, 18.504188537597656, -76.65352630615234, 33.257606506347656, 51.008384704589844, 63.0673942565918, -57.37456130981445, 51.170955657958984, 54.72771453857422, 6.39027214050293, 19.252605438232422, 4.6363654136657715, 11.566444396972656, 11.537176132202148, -35.133445739746094, 63.63831329345703, -43.02503967285156, -71.42203521728516, -54.053077697753906, -16.829618453979492, 57.269012451171875, 62.589778900146484, -53.62313461303711, 1.9179813861846924, 47.98454666137695, 13.759295463562012, -70.34564971923828, 71.36397552490234, 81.74644470214844, 55.41337585449219, 69.63069152832031, 66.75590515136719, 72.9482650756836, -68.32137298583984, 49.18230438232422, 73.8700942993164, 40.35387420654297, 73.46485900878906, 60.809532165527344, 0.3341088891029358, 8.943510055541992, -0.2680262625217438, -20.011632919311523, 58.171241760253906, -4.249980449676514, 66.67961883544922, 25.12101936340332, 11.021951675415039, -20.4036808013916, 59.899105072021484, 14.341323852539062, -19.821107864379883, 47.05691146850586, 75.78777313232422, 39.60555648803711, -72.91056823730469, 47.46449279785156, -29.413843154907227, 43.94081115722656, 19.486083984375, 22.519386291503906, 18.821937561035156, 43.2929801940918, 46.828914642333984, -1.209606647491455, 7.879936695098877, -42.13523864746094, -19.574186325073242, -63.1363639831543, 3.384650945663452, -56.23793029785156, 68.13286590576172, 75.10267639160156, -25.764202117919922, -7.042070388793945, -17.6519718170166, -55.56201934814453, -23.5776424407959, -13.757485389709473, 69.43165588378906, 50.53891372680664, 4.087852954864502], \"y\": [-21.551349639892578, 1.333781123161316, -36.386009216308594, -7.800886154174805, 17.03435516357422, -7.24591064453125, -43.56979751586914, 9.709979057312012, -19.533185958862305, 30.371814727783203, 39.402198791503906, 69.68557739257812, 62.69525146484375, 62.146671295166016, 56.58028793334961, -76.02986145019531, -69.00030517578125, -57.11161422729492, -62.198760986328125, -80.57331085205078, -64.92558288574219, -49.2873420715332, -70.46537017822266, -38.732460021972656, -74.4123764038086, -7.312612056732178, -26.361766815185547, -1.1771035194396973, -18.149242401123047, 16.212392807006836, -4.967414855957031, -5.828280448913574, -16.923498153686523, 37.624237060546875, 49.665958404541016, 51.3908805847168, 50.30913162231445, 26.4985294342041, 61.46052169799805, 12.132923126220703, 41.02153015136719, 27.628366470336914, 54.54361343383789, 73.7714614868164, -76.60296630859375, -74.93193054199219, -83.8011703491211, -70.55852508544922, -56.92851638793945, -61.95793533325195, -31.496051788330078, -47.97669982910156, -9.56602954864502, 34.74769592285156, 2.823852777481079, -18.505016326904297, 5.930328369140625, 18.384159088134766, 27.231422424316406, 43.15444564819336, 46.917930603027344, 24.944669723510742, -41.409542083740234, -73.56331634521484, -76.66158294677734, -68.7757339477539, -48.30293273925781, -70.41215515136719, -61.579647064208984, -75.92961883544922, -51.710044860839844, -52.67837905883789, -84.8721923828125, -36.7751350402832, -19.39414405822754, -47.81476593017578, -88.3822021484375, -39.15634536743164, -52.989139556884766, -24.783592224121094, -23.415834426879883, -11.023223876953125, 0.8730364441871643, -3.754545211791992, -13.902688026428223, -29.431659698486328, -3.5274276733398438, -8.99573802947998], \"z\": [-59.0936393737793, -72.04867553710938, -65.91287231445312, -59.398292541503906, -60.9799919128418, -54.86521911621094, -77.2613525390625, -80.64534759521484, -52.57797622680664, -55.51892852783203, -58.01566696166992, -69.162353515625, -9.876018524169922, -54.33824157714844, -24.841604232788086, 16.85468101501465, 23.27411651611328, 22.409513473510742, 7.3952107429504395, -10.822163581848145, -13.919873237609863, -9.845146179199219, -30.110912322998047, -17.31197738647461, -14.923943519592285, -8.502848625183105, -43.611473083496094, -60.84794235229492, -71.0333251953125, -71.6630859375, -68.2049789428711, -73.60839080810547, -70.98750305175781, -41.58895492553711, -36.67809295654297, -75.69207000732422, -66.61734771728516, -20.02412986755371, -35.55797576904297, -37.368927001953125, -33.096343994140625, -2.7142655849456787, -33.704986572265625, -17.970510482788086, -5.775143623352051, -41.724693298339844, -30.992216110229492, -23.622726440429688, -3.876955032348633, -27.990949630737305, -25.43830108642578, -44.71148681640625, -56.40513229370117, -42.580039978027344, -58.98588562011719, -70.87205505371094, -62.264190673828125, -76.3041000366211, -50.06577682495117, -15.414530754089355, -18.65686798095703, -39.24653244018555, 5.559897422790527, -36.48843765258789, -5.498666763305664, -17.44999122619629, 18.127727508544922, -35.22344970703125, -15.403614044189453, -21.51132583618164, 3.378756284713745, -10.854170799255371, -16.361608505249023, -3.1334903240203857, 16.173492431640625, -38.93711471557617, -23.205244064331055, -24.066307067871094, -33.7904052734375, -11.845132827758789, -12.34650707244873, -22.80036163330078, -84.61084747314453, -42.105079650878906, -47.946449279785156, -63.932437896728516, -18.218263626098633, -52.98310089111328]}],\n",
       "                        {\"legend\": {\"title\": {\"text\": \"color\"}, \"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"scene\": {\"domain\": {\"x\": [0.0, 1.0], \"y\": [0.0, 1.0]}, \"xaxis\": {\"title\": {\"text\": \"x\"}}, \"yaxis\": {\"title\": {\"text\": \"y\"}}, \"zaxis\": {\"title\": {\"text\": \"z\"}}}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('911cb6b3-28d6-4776-b802-ec0ee948a16c');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2 clusters\n",
    "km2 = KMeans(n_clusters=2).fit(X_selected)\n",
    "\n",
    "# plot using tsne \n",
    "X_embedded  = TSNE(n_components=3, perplexity=10, random_state=24).fit_transform( X_selected )\n",
    "colors = np.array([x for x in 'bgrcmykbgrcmykbgrcmykbgrcmyk'])\n",
    "\n",
    "fig = px.scatter_3d(x=X_embedded [:,0],y=X_embedded [:,1],z=X_embedded [:,2],color=colors[km2.labels_])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"e09ecf2f-2b8c-4606-86e5-3acba420d92d\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"e09ecf2f-2b8c-4606-86e5-3acba420d92d\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        'e09ecf2f-2b8c-4606-86e5-3acba420d92d',\n",
       "                        [{\"hovertemplate\": \"color=r<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"r\", \"marker\": {\"color\": \"#636efa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"r\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [-16.051851272583008, -28.01970863342285, -23.7200984954834, -72.91089630126953, -79.24576568603516, -68.05513763427734, -75.87440490722656, -49.211429595947266, -31.466691970825195, -27.346542358398438, -49.55375289916992, -14.697940826416016, 0.07558732479810715, -34.93399429321289, -84.41986083984375, -76.68899536132812, -51.12693405151367, -45.20844650268555, -7.688177585601807, -3.439753532409668, 6.584710597991943, 9.8240385055542, -14.846447944641113, -92.09933471679688, -81.64250183105469, -65.40040588378906, -65.02498626708984, -63.1363639831543, -58.738670349121094, -43.6920166015625, -14.682917594909668, -30.976539611816406], \"y\": [4.4482598304748535, 11.40792465209961, -0.14262452721595764, -26.464393615722656, 15.517782211303711, -25.052114486694336, -2.1702678203582764, 30.691390991210938, -0.4104595184326172, -12.368196487426758, 16.39856719970703, 1.8766013383865356, 4.999932289123535, -43.58101272583008, -27.04196548461914, -8.303616523742676, -19.46199607849121, -2.7562646865844727, -12.61686897277832, -15.25459098815918, -12.55990982055664, -7.39304256439209, -28.882776260375977, -15.132575988769531, -10.048362731933594, -29.55080223083496, 7.568136692047119, -19.39414405822754, 5.82424259185791, -19.462696075439453, -8.347434997558594, -5.69174861907959], \"z\": [80.63272857666016, 48.72231674194336, 37.440189361572266, 64.01304626464844, 26.933799743652344, 32.943450927734375, 26.67510223388672, 14.684473991394043, 96.62628936767578, 85.99493408203125, 30.000110626220703, 50.12711715698242, 26.296035766601562, 29.253244400024414, 47.042179107666016, 64.59676361083984, 44.96508026123047, 46.35492706298828, 75.65142059326172, 38.683902740478516, 22.485858917236328, 45.806514739990234, 31.6491756439209, 66.96732330322266, 49.83415603637695, 47.38495635986328, 37.11040115356445, 16.173492431640625, 20.859668731689453, 64.80724334716797, 94.19955444335938, 54.964847564697266]}, {\"hovertemplate\": \"color=g<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"g\", \"marker\": {\"color\": \"#EF553B\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"g\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [13.443845748901367, -4.07905387878418, 50.6001091003418, -62.843772888183594, -11.988554000854492, -84.30481719970703, 58.23987579345703, 18.504188537597656, -76.65352630615234, 33.257606506347656, 51.008384704589844, 63.0673942565918, -57.37456130981445, 51.170955657958984, 54.72771453857422, 6.39027214050293, 19.252605438232422, 4.6363654136657715, 11.566444396972656, 11.537176132202148, -35.133445739746094, 63.63831329345703, -43.02503967285156, -71.42203521728516, -54.053077697753906, -16.829618453979492, 57.269012451171875, 62.589778900146484, -53.62313461303711, 1.9179813861846924, 47.98454666137695, 13.759295463562012, -70.34564971923828, 71.36397552490234, 81.74644470214844, 55.41337585449219, 69.63069152832031, 66.75590515136719, 72.9482650756836, -68.32137298583984, 49.18230438232422, 73.8700942993164, 40.35387420654297, 73.46485900878906, 60.809532165527344, 0.3341088891029358, 8.943510055541992, -0.2680262625217438, -20.011632919311523, 58.171241760253906, -4.249980449676514, 66.67961883544922, 25.12101936340332, 11.021951675415039, -20.4036808013916, 59.899105072021484, 14.341323852539062, -19.821107864379883, 47.05691146850586, 75.78777313232422, 39.60555648803711, -72.91056823730469, 47.46449279785156, -29.413843154907227, 43.94081115722656, 19.486083984375, 22.519386291503906, 18.821937561035156, 43.2929801940918, 46.828914642333984, -1.209606647491455, 7.879936695098877, -42.13523864746094, -19.574186325073242, 3.384650945663452, -56.23793029785156, 68.13286590576172, 75.10267639160156, -25.764202117919922, -7.042070388793945, -17.6519718170166, -55.56201934814453, -23.5776424407959, -13.757485389709473, 69.43165588378906, 50.53891372680664, 4.087852954864502], \"y\": [-21.551349639892578, 1.333781123161316, -36.386009216308594, -7.800886154174805, 17.03435516357422, -7.24591064453125, -43.56979751586914, 9.709979057312012, -19.533185958862305, 30.371814727783203, 39.402198791503906, 69.68557739257812, 62.69525146484375, 62.146671295166016, 56.58028793334961, -76.02986145019531, -69.00030517578125, -57.11161422729492, -62.198760986328125, -80.57331085205078, -64.92558288574219, -49.2873420715332, -70.46537017822266, -38.732460021972656, -74.4123764038086, -7.312612056732178, -26.361766815185547, -1.1771035194396973, -18.149242401123047, 16.212392807006836, -4.967414855957031, -5.828280448913574, -16.923498153686523, 37.624237060546875, 49.665958404541016, 51.3908805847168, 50.30913162231445, 26.4985294342041, 61.46052169799805, 12.132923126220703, 41.02153015136719, 27.628366470336914, 54.54361343383789, 73.7714614868164, -76.60296630859375, -74.93193054199219, -83.8011703491211, -70.55852508544922, -56.92851638793945, -61.95793533325195, -31.496051788330078, -47.97669982910156, -9.56602954864502, 34.74769592285156, 2.823852777481079, -18.505016326904297, 5.930328369140625, 18.384159088134766, 27.231422424316406, 43.15444564819336, 46.917930603027344, 24.944669723510742, -41.409542083740234, -73.56331634521484, -76.66158294677734, -68.7757339477539, -48.30293273925781, -70.41215515136719, -61.579647064208984, -75.92961883544922, -51.710044860839844, -52.67837905883789, -84.8721923828125, -36.7751350402832, -47.81476593017578, -88.3822021484375, -39.15634536743164, -52.989139556884766, -24.783592224121094, -23.415834426879883, -11.023223876953125, 0.8730364441871643, -3.754545211791992, -13.902688026428223, -29.431659698486328, -3.5274276733398438, -8.99573802947998], \"z\": [-59.0936393737793, -72.04867553710938, -65.91287231445312, -59.398292541503906, -60.9799919128418, -54.86521911621094, -77.2613525390625, -80.64534759521484, -52.57797622680664, -55.51892852783203, -58.01566696166992, -69.162353515625, -9.876018524169922, -54.33824157714844, -24.841604232788086, 16.85468101501465, 23.27411651611328, 22.409513473510742, 7.3952107429504395, -10.822163581848145, -13.919873237609863, -9.845146179199219, -30.110912322998047, -17.31197738647461, -14.923943519592285, -8.502848625183105, -43.611473083496094, -60.84794235229492, -71.0333251953125, -71.6630859375, -68.2049789428711, -73.60839080810547, -70.98750305175781, -41.58895492553711, -36.67809295654297, -75.69207000732422, -66.61734771728516, -20.02412986755371, -35.55797576904297, -37.368927001953125, -33.096343994140625, -2.7142655849456787, -33.704986572265625, -17.970510482788086, -5.775143623352051, -41.724693298339844, -30.992216110229492, -23.622726440429688, -3.876955032348633, -27.990949630737305, -25.43830108642578, -44.71148681640625, -56.40513229370117, -42.580039978027344, -58.98588562011719, -70.87205505371094, -62.264190673828125, -76.3041000366211, -50.06577682495117, -15.414530754089355, -18.65686798095703, -39.24653244018555, 5.559897422790527, -36.48843765258789, -5.498666763305664, -17.44999122619629, 18.127727508544922, -35.22344970703125, -15.403614044189453, -21.51132583618164, 3.378756284713745, -10.854170799255371, -16.361608505249023, -3.1334903240203857, -38.93711471557617, -23.205244064331055, -24.066307067871094, -33.7904052734375, -11.845132827758789, -12.34650707244873, -22.80036163330078, -84.61084747314453, -42.105079650878906, -47.946449279785156, -63.932437896728516, -18.218263626098633, -52.98310089111328]}, {\"hovertemplate\": \"color=b<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"b\", \"marker\": {\"color\": \"#00cc96\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"b\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [23.643281936645508, 11.968172073364258, 3.5444746017456055, 5.89685583114624, 7.682126998901367, 13.478333473205566, -0.4247758388519287, -4.524716854095459, 1.9300822019577026, -1.8310210704803467, 11.063920021057129, 15.0502290725708, 24.261194229125977, 26.23409652709961, 23.72462272644043, 32.061439514160156, 41.97663879394531, 39.56591033935547, -2.0306243896484375, -8.458586692810059, 24.50506019592285, 14.679350852966309, 32.163780212402344, 27.504737854003906, 12.23808479309082, -5.192770004272461, 9.473039627075195, -2.76469349861145, 8.936984062194824, -4.896734714508057, -4.690402030944824], \"y\": [73.46062469482422, 88.60043334960938, 86.7532730102539, 119.78094482421875, 114.0484848022461, 104.24891662597656, 0.8861563205718994, 53.82294464111328, 52.78414535522461, 66.535888671875, 58.82744216918945, 41.10039520263672, 63.610595703125, 51.92506790161133, -23.19164276123047, 56.24617385864258, 47.919158935546875, 62.28577423095703, 107.51199340820312, 88.88972473144531, 17.430078506469727, 1.6315102577209473, 33.13533401489258, 45.677276611328125, 103.4489974975586, 107.51396942138672, 90.91043090820312, 99.93169403076172, 89.82836151123047, 90.24043273925781, 106.4412612915039], \"z\": [90.18350982666016, -6.696622848510742, 13.40608024597168, 11.619553565979004, 28.012550354003906, 14.81717586517334, 82.91858673095703, 76.5682373046875, 92.12594604492188, 88.85021209716797, 59.339168548583984, 59.114662170410156, 69.98632049560547, 51.5333137512207, -113.98896026611328, 95.4275131225586, 60.36748504638672, 81.23568725585938, -2.4596099853515625, 25.963834762573242, 67.55467224121094, 66.26422119140625, 58.27777099609375, 72.30074310302734, -13.049555778503418, 17.68865966796875, 32.08248519897461, 38.850467681884766, -26.91890525817871, -16.869943618774414, -24.56075096130371]}],\n",
       "                        {\"legend\": {\"title\": {\"text\": \"color\"}, \"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"scene\": {\"domain\": {\"x\": [0.0, 1.0], \"y\": [0.0, 1.0]}, \"xaxis\": {\"title\": {\"text\": \"x\"}}, \"yaxis\": {\"title\": {\"text\": \"y\"}}, \"zaxis\": {\"title\": {\"text\": \"z\"}}}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('e09ecf2f-2b8c-4606-86e5-3acba420d92d');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3 clusters\n",
    "km3 = KMeans(n_clusters=3).fit(X_selected)\n",
    "\n",
    "# plot using tsne \n",
    "X_embedded  = TSNE(n_components=3, perplexity=10,random_state=24).fit_transform( X_selected )\n",
    "\n",
    "fig = px.scatter_3d(x=X_embedded [:,0],y=X_embedded [:,1],z=X_embedded [:,2],color=colors[km3.labels_])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"78d4af0b-115b-4c05-9666-41bdeaca5ed8\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"78d4af0b-115b-4c05-9666-41bdeaca5ed8\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        '78d4af0b-115b-4c05-9666-41bdeaca5ed8',\n",
       "                        [{\"hovertemplate\": \"color=c<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"c\", \"marker\": {\"color\": \"#636efa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"c\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [-16.051851272583008, -28.01970863342285, -23.7200984954834, -72.91089630126953, -79.24576568603516, -68.05513763427734, -75.87440490722656, -49.211429595947266, -31.466691970825195, -27.346542358398438, -49.55375289916992, -14.697940826416016, 0.07558732479810715, -34.93399429321289, -84.41986083984375, -76.68899536132812, -51.12693405151367, -45.20844650268555, -7.688177585601807, -3.439753532409668, 6.584710597991943, 9.8240385055542, -14.846447944641113, -92.09933471679688, -81.64250183105469, -65.40040588378906, -65.02498626708984, -63.1363639831543, -58.738670349121094, -43.6920166015625, -14.682917594909668, -30.976539611816406], \"y\": [4.4482598304748535, 11.40792465209961, -0.14262452721595764, -26.464393615722656, 15.517782211303711, -25.052114486694336, -2.1702678203582764, 30.691390991210938, -0.4104595184326172, -12.368196487426758, 16.39856719970703, 1.8766013383865356, 4.999932289123535, -43.58101272583008, -27.04196548461914, -8.303616523742676, -19.46199607849121, -2.7562646865844727, -12.61686897277832, -15.25459098815918, -12.55990982055664, -7.39304256439209, -28.882776260375977, -15.132575988769531, -10.048362731933594, -29.55080223083496, 7.568136692047119, -19.39414405822754, 5.82424259185791, -19.462696075439453, -8.347434997558594, -5.69174861907959], \"z\": [80.63272857666016, 48.72231674194336, 37.440189361572266, 64.01304626464844, 26.933799743652344, 32.943450927734375, 26.67510223388672, 14.684473991394043, 96.62628936767578, 85.99493408203125, 30.000110626220703, 50.12711715698242, 26.296035766601562, 29.253244400024414, 47.042179107666016, 64.59676361083984, 44.96508026123047, 46.35492706298828, 75.65142059326172, 38.683902740478516, 22.485858917236328, 45.806514739990234, 31.6491756439209, 66.96732330322266, 49.83415603637695, 47.38495635986328, 37.11040115356445, 16.173492431640625, 20.859668731689453, 64.80724334716797, 94.19955444335938, 54.964847564697266]}, {\"hovertemplate\": \"color=r<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"r\", \"marker\": {\"color\": \"#EF553B\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"r\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [13.443845748901367, -4.07905387878418, 50.6001091003418, -62.843772888183594, -11.988554000854492, -84.30481719970703, 58.23987579345703, 18.504188537597656, -76.65352630615234, 33.257606506347656, 51.008384704589844, 63.0673942565918, -57.37456130981445, 51.170955657958984, 54.72771453857422, 57.269012451171875, 62.589778900146484, -53.62313461303711, 1.9179813861846924, 47.98454666137695, 13.759295463562012, -70.34564971923828, 71.36397552490234, 81.74644470214844, 55.41337585449219, 69.63069152832031, 66.75590515136719, 72.9482650756836, -68.32137298583984, 49.18230438232422, 73.8700942993164, 40.35387420654297, 73.46485900878906, 66.67961883544922, 25.12101936340332, 11.021951675415039, -20.4036808013916, 59.899105072021484, 14.341323852539062, -19.821107864379883, 47.05691146850586, 75.78777313232422, 39.60555648803711, -72.91056823730469, 69.43165588378906, 4.087852954864502], \"y\": [-21.551349639892578, 1.333781123161316, -36.386009216308594, -7.800886154174805, 17.03435516357422, -7.24591064453125, -43.56979751586914, 9.709979057312012, -19.533185958862305, 30.371814727783203, 39.402198791503906, 69.68557739257812, 62.69525146484375, 62.146671295166016, 56.58028793334961, -26.361766815185547, -1.1771035194396973, -18.149242401123047, 16.212392807006836, -4.967414855957031, -5.828280448913574, -16.923498153686523, 37.624237060546875, 49.665958404541016, 51.3908805847168, 50.30913162231445, 26.4985294342041, 61.46052169799805, 12.132923126220703, 41.02153015136719, 27.628366470336914, 54.54361343383789, 73.7714614868164, -47.97669982910156, -9.56602954864502, 34.74769592285156, 2.823852777481079, -18.505016326904297, 5.930328369140625, 18.384159088134766, 27.231422424316406, 43.15444564819336, 46.917930603027344, 24.944669723510742, -29.431659698486328, -8.99573802947998], \"z\": [-59.0936393737793, -72.04867553710938, -65.91287231445312, -59.398292541503906, -60.9799919128418, -54.86521911621094, -77.2613525390625, -80.64534759521484, -52.57797622680664, -55.51892852783203, -58.01566696166992, -69.162353515625, -9.876018524169922, -54.33824157714844, -24.841604232788086, -43.611473083496094, -60.84794235229492, -71.0333251953125, -71.6630859375, -68.2049789428711, -73.60839080810547, -70.98750305175781, -41.58895492553711, -36.67809295654297, -75.69207000732422, -66.61734771728516, -20.02412986755371, -35.55797576904297, -37.368927001953125, -33.096343994140625, -2.7142655849456787, -33.704986572265625, -17.970510482788086, -44.71148681640625, -56.40513229370117, -42.580039978027344, -58.98588562011719, -70.87205505371094, -62.264190673828125, -76.3041000366211, -50.06577682495117, -15.414530754089355, -18.65686798095703, -39.24653244018555, -63.932437896728516, -52.98310089111328]}, {\"hovertemplate\": \"color=b<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"b\", \"marker\": {\"color\": \"#00cc96\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"b\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [23.643281936645508, 11.968172073364258, 3.5444746017456055, 5.89685583114624, 7.682126998901367, 13.478333473205566, -0.4247758388519287, -4.524716854095459, 1.9300822019577026, -1.8310210704803467, 11.063920021057129, 15.0502290725708, 24.261194229125977, 26.23409652709961, 23.72462272644043, 32.061439514160156, 41.97663879394531, 39.56591033935547, -2.0306243896484375, -8.458586692810059, 24.50506019592285, 14.679350852966309, 32.163780212402344, 27.504737854003906, 12.23808479309082, -5.192770004272461, 9.473039627075195, -2.76469349861145, 8.936984062194824, -4.896734714508057, -4.690402030944824], \"y\": [73.46062469482422, 88.60043334960938, 86.7532730102539, 119.78094482421875, 114.0484848022461, 104.24891662597656, 0.8861563205718994, 53.82294464111328, 52.78414535522461, 66.535888671875, 58.82744216918945, 41.10039520263672, 63.610595703125, 51.92506790161133, -23.19164276123047, 56.24617385864258, 47.919158935546875, 62.28577423095703, 107.51199340820312, 88.88972473144531, 17.430078506469727, 1.6315102577209473, 33.13533401489258, 45.677276611328125, 103.4489974975586, 107.51396942138672, 90.91043090820312, 99.93169403076172, 89.82836151123047, 90.24043273925781, 106.4412612915039], \"z\": [90.18350982666016, -6.696622848510742, 13.40608024597168, 11.619553565979004, 28.012550354003906, 14.81717586517334, 82.91858673095703, 76.5682373046875, 92.12594604492188, 88.85021209716797, 59.339168548583984, 59.114662170410156, 69.98632049560547, 51.5333137512207, -113.98896026611328, 95.4275131225586, 60.36748504638672, 81.23568725585938, -2.4596099853515625, 25.963834762573242, 67.55467224121094, 66.26422119140625, 58.27777099609375, 72.30074310302734, -13.049555778503418, 17.68865966796875, 32.08248519897461, 38.850467681884766, -26.91890525817871, -16.869943618774414, -24.56075096130371]}, {\"hovertemplate\": \"color=g<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"g\", \"marker\": {\"color\": \"#ab63fa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"g\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [6.39027214050293, 19.252605438232422, 4.6363654136657715, 11.566444396972656, 11.537176132202148, -35.133445739746094, 63.63831329345703, -43.02503967285156, -71.42203521728516, -54.053077697753906, -16.829618453979492, 60.809532165527344, 0.3341088891029358, 8.943510055541992, -0.2680262625217438, -20.011632919311523, 58.171241760253906, -4.249980449676514, 47.46449279785156, -29.413843154907227, 43.94081115722656, 19.486083984375, 22.519386291503906, 18.821937561035156, 43.2929801940918, 46.828914642333984, -1.209606647491455, 7.879936695098877, -42.13523864746094, -19.574186325073242, 3.384650945663452, -56.23793029785156, 68.13286590576172, 75.10267639160156, -25.764202117919922, -7.042070388793945, -17.6519718170166, -55.56201934814453, -23.5776424407959, -13.757485389709473, 50.53891372680664], \"y\": [-76.02986145019531, -69.00030517578125, -57.11161422729492, -62.198760986328125, -80.57331085205078, -64.92558288574219, -49.2873420715332, -70.46537017822266, -38.732460021972656, -74.4123764038086, -7.312612056732178, -76.60296630859375, -74.93193054199219, -83.8011703491211, -70.55852508544922, -56.92851638793945, -61.95793533325195, -31.496051788330078, -41.409542083740234, -73.56331634521484, -76.66158294677734, -68.7757339477539, -48.30293273925781, -70.41215515136719, -61.579647064208984, -75.92961883544922, -51.710044860839844, -52.67837905883789, -84.8721923828125, -36.7751350402832, -47.81476593017578, -88.3822021484375, -39.15634536743164, -52.989139556884766, -24.783592224121094, -23.415834426879883, -11.023223876953125, 0.8730364441871643, -3.754545211791992, -13.902688026428223, -3.5274276733398438], \"z\": [16.85468101501465, 23.27411651611328, 22.409513473510742, 7.3952107429504395, -10.822163581848145, -13.919873237609863, -9.845146179199219, -30.110912322998047, -17.31197738647461, -14.923943519592285, -8.502848625183105, -5.775143623352051, -41.724693298339844, -30.992216110229492, -23.622726440429688, -3.876955032348633, -27.990949630737305, -25.43830108642578, 5.559897422790527, -36.48843765258789, -5.498666763305664, -17.44999122619629, 18.127727508544922, -35.22344970703125, -15.403614044189453, -21.51132583618164, 3.378756284713745, -10.854170799255371, -16.361608505249023, -3.1334903240203857, -38.93711471557617, -23.205244064331055, -24.066307067871094, -33.7904052734375, -11.845132827758789, -12.34650707244873, -22.80036163330078, -84.61084747314453, -42.105079650878906, -47.946449279785156, -18.218263626098633]}],\n",
       "                        {\"legend\": {\"title\": {\"text\": \"color\"}, \"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"scene\": {\"domain\": {\"x\": [0.0, 1.0], \"y\": [0.0, 1.0]}, \"xaxis\": {\"title\": {\"text\": \"x\"}}, \"yaxis\": {\"title\": {\"text\": \"y\"}}, \"zaxis\": {\"title\": {\"text\": \"z\"}}}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('78d4af0b-115b-4c05-9666-41bdeaca5ed8');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 4 clusters\n",
    "km4 = KMeans(n_clusters=4).fit(X_selected)\n",
    "\n",
    "# plot using tsne \n",
    "X_embedded  = TSNE(n_components=3, perplexity=10,random_state=24).fit_transform( X_selected )\n",
    "\n",
    "fig = px.scatter_3d(x=X_embedded [:,0],y=X_embedded [:,1],z=X_embedded [:,2],color=colors[km4.labels_])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "It seems like 4 clusters work best. Let's try the same process again with PCA + K-means.\n",
    "\n",
    "For PCA see https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"1713306c-fbf6-457e-8107-610787e93cd5\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"1713306c-fbf6-457e-8107-610787e93cd5\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        '1713306c-fbf6-457e-8107-610787e93cd5',\n",
       "                        [{\"hovertemplate\": \"color=r<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"r\", \"marker\": {\"color\": \"#636efa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"r\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [9.067049128150698, 5.066717918205411, 5.073425196274106, 5.0413681008919395, 2.0860878679258863, 2.04514488847169, 2.0986405614418095, 2.107769486069083, 9.108907506722613, 9.092611440739423, 3.1186323838048726, 5.0722862509045195, 3.085985200467527, 2.0875378345498086, 3.045387491470311, 5.059767558023505, 3.07004015002364, 3.0431938745809544, 9.036071799104816, 5.144881951610396, 2.134772842843844, 6.112245460812809, 2.14845991261251, 6.066694310631436, 4.06113850097513, 3.0423026429507987, 3.1013825422618173, 0.08178073455884723, 2.1035191518207292, 6.070793010291179, 9.09411959719207, 5.046709467415418], \"y\": [-0.2797022739456225, -0.30367927218506907, -1.2999166315564528, 4.423831422639787, 3.528812295720668, 3.4117669780925506, 3.3802127352640206, 3.400707490042873, 2.460522859088264, 1.41233064682535, 0.4395937898558931, -1.2994818112240654, -5.486487084869094, -5.479700740670247, 5.4329270348265855, 4.492127601306766, 1.296067345176009, 0.6007727743315392, -0.3839900735712383, -3.6689429335933914, -3.73756018454834, -3.7713839889924596, -4.686875726645286, 5.497769818166319, 4.487782313232654, 3.4122955295928086, 2.390311984851404, 2.307298224807006, 1.400090606599902, 1.3335677571098166, 0.41978976474821555, -0.3805238272846054], \"z\": [0.9985626853539182, 1.0467779031810094, 1.0737838165469789, -1.9785752582449831, 2.0653430588982693, -1.917554308036196, 1.1478810583318386, 2.1407268093973757, 2.076365181820051, 0.11172803735206771, 2.196829740547129, 1.0713074074646762, -0.7382393803213543, -0.7212265998610002, -0.98470447318011, 0.015557946236549564, -1.820404242537298, -0.9446867286300725, -1.9892684242888456, 1.3441821896521808, 0.3801094629053768, -1.6606908655950834, 1.3998849661584378, 0.9715565782103109, 0.02810907083718087, -1.9365658316184475, 1.159348664842756, -0.7969470177019685, 1.1876886145132273, -1.851130722146417, 0.13104247849587278, -0.9456770642126567]}, {\"hovertemplate\": \"color=b<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"b\", \"marker\": {\"color\": \"#EF553B\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"b\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [-5.961402349571306, -6.934943040198211, -11.933583477857587, -1.9262635245944781, -6.924324209287761, -1.9580775794214016, -11.912442712017638, -6.941665147713357, -2.9444146694048516, -6.8450524337438345, -6.8628866395988855, -5.8809231407908635, -11.878851563526068, -6.867263432703262, -9.855679763502454, -6.928648871138685, -6.928648871138685, -6.915452676498613, -6.926445457411988, -6.947266731325536, -2.9277319084658004, -11.939600703521247, -2.94436662456041, -11.884352771213008, -2.9051574553729194, -5.8857927316387135, -11.96230798567449, -8.960961376836329, -2.915791059065247, -6.935465476419412, -8.956031620777118, -6.946056015393578, -2.9261330965627756, -9.863640441472171, -9.881810934671998, -6.884006794281184, -6.884006794281184, -6.881504499785737, -9.881756536846066, -1.8618890477502485, -8.849033073463767, -6.876809099235027, -8.844351818881197, -11.918826919148932, -9.962267248865935, -5.9577974706705605, -5.95452747809938, -5.940637738529431, -4.923035036035912, -9.927937172730346, -6.904317477106522, -9.91049294452659, -6.960105897744302, -9.96004082928332, -6.9264989770810335, -9.946060980311445, -6.945794797282977, -6.908791197620423, -6.85172795734277, -6.883715473946373, -9.835962633047268, -1.8786753527513032, -11.913441912891116, -2.957819579565313, -8.956451126599516, -6.946990490391326, -8.914032386830286, -6.954481229414669, -8.943233318945452, -8.953337180680553, -6.922667174587745, -6.912427399344984, -2.907150565415696, -5.88496221127258, -5.925834313786452, -2.905477469304312, -11.902208590082047, -9.904569514166852, -5.883303261129337, -6.893211968957004, -5.8863151678599195, -2.878912474981616, -5.931915557919955, -5.942520242862263, -9.939092677509306, -2.917855674796038, -5.949908838838813], \"y\": [-0.47414091608966946, -1.4199072988800943, -1.4333773549800335, -1.3584148966117637, -1.381859484146134, -1.4549654594610317, -1.3876071136007377, -2.42397195253176, -2.4251320261281206, -2.7303865512792154, -3.7837655344746484, -4.820264816738582, -4.869352322608766, -5.790933066077607, -5.771297972725263, 5.441105109719888, 5.441105109719888, 4.488836497281685, 4.4502642948755415, 4.3922859344324205, 4.474814590051031, 3.3604919606046053, 3.418791676771465, 2.325769515632734, 2.3319264779893576, 0.3615936510883586, 0.46314847444026813, -0.4796801824167492, -1.3107322769970284, -1.416867426941452, -1.493509616428707, -1.4431866541069998, -1.354269317032, -2.8369452344313997, -3.86828068381818, -3.862791880429282, -3.862791880429282, -4.832584709762116, -4.858057055352246, -4.731665505109037, -4.742445000716389, -5.823332037120442, -5.739056621858923, -5.586456775649, 5.308031136563767, 4.355291497912184, 3.3614017232628415, 3.4030067905396693, 3.464089859905978, 2.2123504513601033, 1.3061182733453067, 0.2518507856628871, -0.49512145116514883, -0.5192148091044908, -0.38550313449419304, -1.4760432294506596, -1.4447065900763216, -2.3536718140924413, -3.7606148277434372, -3.838910385205856, -5.718334912849151, -5.773418619468815, 4.44300865997033, 4.380452254776037, 4.338164715736616, 4.370595317930441, 4.4668987995356355, 3.350919791654083, 3.3708281650160923, 3.3506727104100156, 3.4474703545033476, 3.2977440237499587, 2.3090409580314675, 2.3608595723335664, 1.2537530990238768, 1.337219216680784, 1.2874584707196206, 1.280645927755176, 1.383173537198676, 1.3503298606387382, 0.36463352302700225, 0.41743408786695557, 0.6230474568911722, 0.5908639359414174, -0.45332783123565884, -0.3214479859506672, -0.44163936969446277], \"z\": [-1.8089264174456048, 0.22205429597669837, 0.2877891738473192, 1.156332140395032, 1.2193789001246316, -1.8337194754738961, 2.2768559468637095, -0.7480476535835937, -0.8057706579022826, 2.4639562380864035, 0.4922740885634918, -1.4885773371876811, -1.416790741393175, -0.4624332992335248, 0.5720432852681201, 1.1395482102998054, 1.1395482102998054, 2.15582561971564, 1.1574601369759958, -0.8342259961532887, 1.1079241631710481, -0.74767907862453, -0.8589736791000369, 2.335788312104398, 0.23630232176835209, 1.3162987720980295, -1.7576574679165002, -1.769297610979142, 2.168306272078686, 0.22065959135657637, -1.7479401656535691, -0.7753835484081081, 1.1684482216995635, 0.5114232951206716, -1.4598141812534875, -1.5015949486163154, -1.5015949486163154, -1.4815001178896026, -1.4483361923533837, 0.45058839095845776, 1.533960217073425, -1.4556870297579663, 1.559132573013436, -1.5413603850771813, -1.8250252172794585, -1.8428834154139873, -1.823771806055631, -0.8223909716532426, 1.1538958163620607, -1.6771098672434344, 0.3007914907051811, -0.6375560997748989, -1.7941824549174807, -1.7605324690994706, 1.2001933421240116, -0.7421630027534539, -0.7746861960980472, 2.2412917481393886, 1.4882492759228174, -1.4971815858160908, 2.5600848898615616, -1.5170550966821859, 2.216610508808563, -1.8785707189167808, -1.8065087063561536, -0.8370302672294168, 2.1802267814690843, -1.8127258971060798, -0.7912740382472973, -1.785520464276507, 1.177325718762848, 0.25994547668617535, 0.23445138868095217, 2.265611845138907, -1.7043195144670495, 0.2529247098131016, 0.3651489038884642, 0.33395541624139957, 2.283444434079431, 1.2999128085885896, 1.3149040674779078, 2.273777658516696, 1.1634782659158842, 0.16679439395957513, 0.23213792250308757, 2.1474851611484342, -0.8075765035277622]}, {\"hovertemplate\": \"color=g<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"g\", \"marker\": {\"color\": \"#00cc96\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"g\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [16.10553763468977, 15.048756658199714, 16.06390622611976, 16.091589716423293, 16.093413156704035, 16.093459021716473, 10.059313301888874, 16.073557457190763, 16.052648477581428, 16.05518786734828, 16.138602311620353, 16.152231727279307, 16.129805482044006, 16.151014851928622, 16.120169170975743, 15.114719220014072, 16.15681634701985, 16.12317885191218, 16.091892714074767, 15.06741181818103, 12.14216140015162, 10.111459832966203, 15.155384454837135, 16.142740458573474, 15.056538713755005, 16.091584629929834, 16.0711789904001, 16.07250249146447, 16.014801439070723, 16.04855028785702, 16.092588592155433], \"y\": [-2.703802671932342, 4.517390681528268, 2.3675085104113562, 1.4483316849900234, 1.4519287589304009, 1.4453717870131093, -1.2938779278822816, -2.260870377807574, -2.3205336181502023, -2.3040215346511532, -2.645184794840957, -3.5858339751626804, -3.657260641270704, -3.5928935993711946, -3.6651667251425217, -4.68227224618564, -4.547400588592749, -4.647548225382393, 3.4648741038995063, 1.3826421486951999, -3.6440009256598587, -3.7348056274732935, -4.562875680031516, -4.608009317739584, 4.537805462345391, 1.4625683107156549, 0.38644475588086447, 0.39937495277281443, 6.617685299091646, 6.51961109607948, 6.46698283664335], \"z\": [-1.8050384208183488, -1.1057313208010418, -1.998185052637261, 0.024679228387932288, 0.02617880213486425, 0.02598261447286609, 0.014330678381800783, 0.9599720858475063, -1.0320787956761972, -1.0257540332188075, 1.1861233373448248, 2.2042967446479684, 0.20694094591785753, 2.2003086898304764, -0.7819399606065225, -1.7486102791791076, 2.2257412151948937, -0.7658099744209673, 0.9692157043851943, -1.964383376943022, 1.2529534003493186, -1.7077893934729313, 2.238014369175767, 1.2225210030236313, -0.11279425120031687, 0.021297335964438717, -1.9534191592377255, -1.9503612333893017, -1.2426658060390852, -0.17122062585954398, 1.904945597950271]}],\n",
       "                        {\"legend\": {\"title\": {\"text\": \"color\"}, \"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"scene\": {\"domain\": {\"x\": [0.0, 1.0], \"y\": [0.0, 1.0]}, \"xaxis\": {\"title\": {\"text\": \"x\"}}, \"yaxis\": {\"title\": {\"text\": \"y\"}}, \"zaxis\": {\"title\": {\"text\": \"z\"}}}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('1713306c-fbf6-457e-8107-610787e93cd5');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PCA for reducing dimensions to 3\n",
    "pca = PCA(n_components=3)\n",
    "pca_results = pca.fit_transform(X_selected)\n",
    "\n",
    "# running k-means on resuts of pca\n",
    "km_pca = KMeans(n_clusters=3).fit(pca_results)\n",
    "fig = px.scatter_3d(x=pca_results [:,0],y=pca_results [:,1],z=pca_results [:,2],color=colors[km_pca.labels_])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "We lost most of valuable information about data with PCA so, resulting graph seems incomplete. Using k-means on original 7-dimensional data then plotting with t-sne gives better results."
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "**2. AGNES:**\n",
    "\n",
    "There's no inertia (Sum of squared distances of samples to their closest cluster center) attribute of AgglomerativeClustering class so we used silhouette coefficient (best:1, worst:-1) to select cluster number of AGNES.\n",
    "\n",
    "see https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html#sklearn.metrics.silhouette_score \n",
    "\n",
    "for AGNES see https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html#sklearn.cluster.AgglomerativeClustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define a function to plot silhouette values of clusters\n",
    "def silhouette_plot(X, y, n_clusters, ax=None):\n",
    "    if ax is None:\n",
    "        ax = plt.gca()\n",
    "\n",
    "    # Compute the silhouette scores for each sample\n",
    "    silhouette_avg = silhouette_score(X, y)\n",
    "    sample_silhouette_values = silhouette_samples(X, y)\n",
    "\n",
    "    y_lower = padding = 2\n",
    "    for i in range(n_clusters):\n",
    "        # Aggregate the silhouette scores for samples belonging to\n",
    "        ith_cluster_silhouette_values = sample_silhouette_values[y == i]\n",
    "        ith_cluster_silhouette_values.sort()\n",
    "\n",
    "        size_cluster_i = ith_cluster_silhouette_values.shape[0]\n",
    "        y_upper = y_lower + size_cluster_i\n",
    "\n",
    "        color = cm.nipy_spectral(float(i) / n_clusters)\n",
    "        ax.fill_betweenx(np.arange(y_lower, y_upper),\n",
    "                         0,\n",
    "                         ith_cluster_silhouette_values,\n",
    "                         facecolor=color,\n",
    "                         edgecolor=color,\n",
    "                         alpha=0.7)\n",
    "\n",
    "        # Label the silhouette plots with their cluster numbers at the middle\n",
    "        ax.text(-0.05, y_lower + 0.5 * size_cluster_i, str(i + 1))\n",
    "\n",
    "        # Compute the new y_lower for next plot\n",
    "        y_lower = y_upper + padding\n",
    "\n",
    "    ax.set_xlabel(\"The silhouette coefficient values\")\n",
    "    ax.set_ylabel(\"Cluster label\")\n",
    "\n",
    "    # The vertical line for average silhoutte score of all the values\n",
    "    ax.axvline(x=silhouette_avg, c='r', alpha=0.8, lw=0.8, ls='-')\n",
    "    ax.annotate('Average',\n",
    "                xytext=(silhouette_avg, y_lower * 1.025),\n",
    "                xy=(0, 0),\n",
    "                ha='center',\n",
    "                alpha=0.8,\n",
    "                c='r')\n",
    "\n",
    "    ax.set_yticks([])  # Clear the yaxis labels / ticks\n",
    "    ax.set_xticks([0, 0.2, 0.4, 0.6, 0.8, 1])\n",
    "    ax.set_ylim(0, y_upper + 1)\n",
    "    ax.set_xlim(-0.075, 1.0)\n",
    "    return ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x2160 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot silhouette coefficients\n",
    "plt.figure(figsize=(20,30))\n",
    "for i in range(2,11):  \n",
    "    agnes = AgglomerativeClustering(n_clusters=i, linkage='average')\n",
    "    agnes_labels = agnes.fit_predict(X_selected)\n",
    "    plt.subplot(5,2,i-1)\n",
    "    silhouette_plot(X_selected,agnes_labels,i)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "It seems like 3, 6 or 9 are best amongst them (cluster with euqal sizes and significant silhouette value). We choosed to work with n_clusters = 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"d80afd9f-2fa5-43bb-acac-6b981cd7eb4e\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"d80afd9f-2fa5-43bb-acac-6b981cd7eb4e\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        'd80afd9f-2fa5-43bb-acac-6b981cd7eb4e',\n",
       "                        [{\"hovertemplate\": \"color=g<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"g\", \"marker\": {\"color\": \"#636efa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"g\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [-16.051851272583008, -28.01970863342285, -23.7200984954834, -72.91089630126953, -79.24576568603516, -68.05513763427734, -75.87440490722656, -49.211429595947266, -31.466691970825195, -27.346542358398438, -49.55375289916992, -14.697940826416016, -0.4247758388519287, -84.41986083984375, -76.68899536132812, -51.12693405151367, -45.20844650268555, -7.688177585601807, -92.09933471679688, -81.64250183105469, -65.40040588378906, -65.02498626708984, -63.1363639831543, -58.738670349121094, -43.6920166015625, -14.682917594909668, -30.976539611816406], \"y\": [4.4482598304748535, 11.40792465209961, -0.14262452721595764, -26.464393615722656, 15.517782211303711, -25.052114486694336, -2.1702678203582764, 30.691390991210938, -0.4104595184326172, -12.368196487426758, 16.39856719970703, 1.8766013383865356, 0.8861563205718994, -27.04196548461914, -8.303616523742676, -19.46199607849121, -2.7562646865844727, -12.61686897277832, -15.132575988769531, -10.048362731933594, -29.55080223083496, 7.568136692047119, -19.39414405822754, 5.82424259185791, -19.462696075439453, -8.347434997558594, -5.69174861907959], \"z\": [80.63272857666016, 48.72231674194336, 37.440189361572266, 64.01304626464844, 26.933799743652344, 32.943450927734375, 26.67510223388672, 14.684473991394043, 96.62628936767578, 85.99493408203125, 30.000110626220703, 50.12711715698242, 82.91858673095703, 47.042179107666016, 64.59676361083984, 44.96508026123047, 46.35492706298828, 75.65142059326172, 66.96732330322266, 49.83415603637695, 47.38495635986328, 37.11040115356445, 16.173492431640625, 20.859668731689453, 64.80724334716797, 94.19955444335938, 54.964847564697266]}, {\"hovertemplate\": \"color=b<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"b\", \"marker\": {\"color\": \"#EF553B\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"b\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [13.443845748901367, -4.07905387878418, 50.6001091003418, -62.843772888183594, -11.988554000854492, -84.30481719970703, 58.23987579345703, 18.504188537597656, -76.65352630615234, 6.39027214050293, 19.252605438232422, 4.6363654136657715, 11.566444396972656, 11.537176132202148, -35.133445739746094, 63.63831329345703, -43.02503967285156, -71.42203521728516, -54.053077697753906, -16.829618453979492, 57.269012451171875, 62.589778900146484, -53.62313461303711, 1.9179813861846924, 47.98454666137695, 13.759295463562012, -70.34564971923828, 60.809532165527344, 0.3341088891029358, 8.943510055541992, -0.2680262625217438, -20.011632919311523, 58.171241760253906, -4.249980449676514, 66.67961883544922, 25.12101936340332, 11.021951675415039, -20.4036808013916, 59.899105072021484, 14.341323852539062, -19.821107864379883, 47.46449279785156, -29.413843154907227, 43.94081115722656, 19.486083984375, 22.519386291503906, 18.821937561035156, 43.2929801940918, 46.828914642333984, -1.209606647491455, 7.879936695098877, -42.13523864746094, -19.574186325073242, 3.384650945663452, -56.23793029785156, 68.13286590576172, 75.10267639160156, -25.764202117919922, -7.042070388793945, -17.6519718170166, -55.56201934814453, -23.5776424407959, -13.757485389709473, 69.43165588378906, 50.53891372680664, 4.087852954864502], \"y\": [-21.551349639892578, 1.333781123161316, -36.386009216308594, -7.800886154174805, 17.03435516357422, -7.24591064453125, -43.56979751586914, 9.709979057312012, -19.533185958862305, -76.02986145019531, -69.00030517578125, -57.11161422729492, -62.198760986328125, -80.57331085205078, -64.92558288574219, -49.2873420715332, -70.46537017822266, -38.732460021972656, -74.4123764038086, -7.312612056732178, -26.361766815185547, -1.1771035194396973, -18.149242401123047, 16.212392807006836, -4.967414855957031, -5.828280448913574, -16.923498153686523, -76.60296630859375, -74.93193054199219, -83.8011703491211, -70.55852508544922, -56.92851638793945, -61.95793533325195, -31.496051788330078, -47.97669982910156, -9.56602954864502, 34.74769592285156, 2.823852777481079, -18.505016326904297, 5.930328369140625, 18.384159088134766, -41.409542083740234, -73.56331634521484, -76.66158294677734, -68.7757339477539, -48.30293273925781, -70.41215515136719, -61.579647064208984, -75.92961883544922, -51.710044860839844, -52.67837905883789, -84.8721923828125, -36.7751350402832, -47.81476593017578, -88.3822021484375, -39.15634536743164, -52.989139556884766, -24.783592224121094, -23.415834426879883, -11.023223876953125, 0.8730364441871643, -3.754545211791992, -13.902688026428223, -29.431659698486328, -3.5274276733398438, -8.99573802947998], \"z\": [-59.0936393737793, -72.04867553710938, -65.91287231445312, -59.398292541503906, -60.9799919128418, -54.86521911621094, -77.2613525390625, -80.64534759521484, -52.57797622680664, 16.85468101501465, 23.27411651611328, 22.409513473510742, 7.3952107429504395, -10.822163581848145, -13.919873237609863, -9.845146179199219, -30.110912322998047, -17.31197738647461, -14.923943519592285, -8.502848625183105, -43.611473083496094, -60.84794235229492, -71.0333251953125, -71.6630859375, -68.2049789428711, -73.60839080810547, -70.98750305175781, -5.775143623352051, -41.724693298339844, -30.992216110229492, -23.622726440429688, -3.876955032348633, -27.990949630737305, -25.43830108642578, -44.71148681640625, -56.40513229370117, -42.580039978027344, -58.98588562011719, -70.87205505371094, -62.264190673828125, -76.3041000366211, 5.559897422790527, -36.48843765258789, -5.498666763305664, -17.44999122619629, 18.127727508544922, -35.22344970703125, -15.403614044189453, -21.51132583618164, 3.378756284713745, -10.854170799255371, -16.361608505249023, -3.1334903240203857, -38.93711471557617, -23.205244064331055, -24.066307067871094, -33.7904052734375, -11.845132827758789, -12.34650707244873, -22.80036163330078, -84.61084747314453, -42.105079650878906, -47.946449279785156, -63.932437896728516, -18.218263626098633, -52.98310089111328]}, {\"hovertemplate\": \"color=r<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"r\", \"marker\": {\"color\": \"#00cc96\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"r\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [23.643281936645508, -4.524716854095459, 1.9300822019577026, -1.8310210704803467, 11.063920021057129, 15.0502290725708, 24.261194229125977, 26.23409652709961, 23.72462272644043, 32.061439514160156, 41.97663879394531, 39.56591033935547, 24.50506019592285, 14.679350852966309, 32.163780212402344, 27.504737854003906], \"y\": [73.46062469482422, 53.82294464111328, 52.78414535522461, 66.535888671875, 58.82744216918945, 41.10039520263672, 63.610595703125, 51.92506790161133, -23.19164276123047, 56.24617385864258, 47.919158935546875, 62.28577423095703, 17.430078506469727, 1.6315102577209473, 33.13533401489258, 45.677276611328125], \"z\": [90.18350982666016, 76.5682373046875, 92.12594604492188, 88.85021209716797, 59.339168548583984, 59.114662170410156, 69.98632049560547, 51.5333137512207, -113.98896026611328, 95.4275131225586, 60.36748504638672, 81.23568725585938, 67.55467224121094, 66.26422119140625, 58.27777099609375, 72.30074310302734]}, {\"hovertemplate\": \"color=m<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"m\", \"marker\": {\"color\": \"#ab63fa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"m\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [33.257606506347656, 51.008384704589844, 63.0673942565918, -57.37456130981445, 51.170955657958984, 54.72771453857422, 71.36397552490234, 81.74644470214844, 55.41337585449219, 69.63069152832031, 66.75590515136719, 72.9482650756836, 49.18230438232422, 73.8700942993164, 40.35387420654297, 73.46485900878906, 47.05691146850586, 75.78777313232422, 39.60555648803711], \"y\": [30.371814727783203, 39.402198791503906, 69.68557739257812, 62.69525146484375, 62.146671295166016, 56.58028793334961, 37.624237060546875, 49.665958404541016, 51.3908805847168, 50.30913162231445, 26.4985294342041, 61.46052169799805, 41.02153015136719, 27.628366470336914, 54.54361343383789, 73.7714614868164, 27.231422424316406, 43.15444564819336, 46.917930603027344], \"z\": [-55.51892852783203, -58.01566696166992, -69.162353515625, -9.876018524169922, -54.33824157714844, -24.841604232788086, -41.58895492553711, -36.67809295654297, -75.69207000732422, -66.61734771728516, -20.02412986755371, -35.55797576904297, -33.096343994140625, -2.7142655849456787, -33.704986572265625, -17.970510482788086, -50.06577682495117, -15.414530754089355, -18.65686798095703]}, {\"hovertemplate\": \"color=y<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"y\", \"marker\": {\"color\": \"#FFA15A\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"y\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [11.968172073364258, 3.5444746017456055, 5.89685583114624, 7.682126998901367, 13.478333473205566, -2.0306243896484375, -8.458586692810059, 12.23808479309082, -5.192770004272461, 9.473039627075195, -2.76469349861145, 8.936984062194824, -4.896734714508057, -4.690402030944824], \"y\": [88.60043334960938, 86.7532730102539, 119.78094482421875, 114.0484848022461, 104.24891662597656, 107.51199340820312, 88.88972473144531, 103.4489974975586, 107.51396942138672, 90.91043090820312, 99.93169403076172, 89.82836151123047, 90.24043273925781, 106.4412612915039], \"z\": [-6.696622848510742, 13.40608024597168, 11.619553565979004, 28.012550354003906, 14.81717586517334, -2.4596099853515625, 25.963834762573242, -13.049555778503418, 17.68865966796875, 32.08248519897461, 38.850467681884766, -26.91890525817871, -16.869943618774414, -24.56075096130371]}, {\"hovertemplate\": \"color=c<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"c\", \"marker\": {\"color\": \"#19d3f3\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"c\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [-68.32137298583984, 0.07558732479810715, -34.93399429321289, -3.439753532409668, 6.584710597991943, 9.8240385055542, -14.846447944641113, -72.91056823730469], \"y\": [12.132923126220703, 4.999932289123535, -43.58101272583008, -15.25459098815918, -12.55990982055664, -7.39304256439209, -28.882776260375977, 24.944669723510742], \"z\": [-37.368927001953125, 26.296035766601562, 29.253244400024414, 38.683902740478516, 22.485858917236328, 45.806514739990234, 31.6491756439209, -39.24653244018555]}],\n",
       "                        {\"legend\": {\"title\": {\"text\": \"color\"}, \"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"scene\": {\"domain\": {\"x\": [0.0, 1.0], \"y\": [0.0, 1.0]}, \"xaxis\": {\"title\": {\"text\": \"x\"}}, \"yaxis\": {\"title\": {\"text\": \"y\"}}, \"zaxis\": {\"title\": {\"text\": \"z\"}}}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('d80afd9f-2fa5-43bb-acac-6b981cd7eb4e');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 6 clusters\n",
    "agnes6 = AgglomerativeClustering(n_clusters=6, linkage='average').fit(X_selected)\n",
    "\n",
    "# plot using tsne \n",
    "X_embedded  = TSNE(n_components=3, perplexity=10,random_state=24).fit_transform( X_selected )\n",
    "\n",
    "fig = px.scatter_3d(x=X_embedded [:,0],y=X_embedded [:,1],z=X_embedded [:,2],color=colors[agnes6.labels_])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "Let's plot the complete dendrogram to see the possible clusterings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:5: ClusterWarning:\n",
      "\n",
      "scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# there's no inertia in attribute of AgglomerativeClustering class so we use scipy's distance matrix\n",
    "dist = distance_matrix(X_selected, X_selected)\n",
    "\n",
    "# dendrogram\n",
    "Z = hierarchy.linkage(dist, 'average')\n",
    "plt.figure(figsize=(18, 15))\n",
    "dendro = hierarchy.dendrogram(Z, leaf_rotation=0, leaf_font_size=12, orientation='right')"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "**3. DBSCAN:**\n",
    "\n",
    "eps: The maximum distance between two samples for one to be considered as in the neighborhood of the other (default: 0.5).\n",
    "\n",
    "min_samples: The number of samples (or total weight) in a neighborhood for a point to be considered as a core point. This includes the point itself (default: 5).\n",
    "\n",
    "see https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5.0, 11)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# search for best parameters by using silhouette_score\n",
    "score_list=[]\n",
    "for eps in np.arange(0.5,20,0.5):\n",
    "    for min_samples in range(3,20):\n",
    "        db = DBSCAN(eps=eps, min_samples=min_samples).fit(X_selected)\n",
    "        labels = db.labels_\n",
    "        n = len(np.unique(labels))\n",
    "        if n>1:\n",
    "            score=silhouette_score(X_selected, labels)\n",
    "            score_list.append((score,(eps,min_samples)))\n",
    "     \n",
    "biggest_score = sorted(score_list)[-1]  \n",
    "best_eps, best_min_spamles = biggest_score[1]\n",
    "best_eps, best_min_spamles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"d82540d2-ebd4-495f-b0bc-2cb91beb087e\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"d82540d2-ebd4-495f-b0bc-2cb91beb087e\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        'd82540d2-ebd4-495f-b0bc-2cb91beb087e',\n",
       "                        [{\"hovertemplate\": \"color=b<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"b\", \"marker\": {\"color\": \"#636efa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"b\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [-16.051851272583008, 13.443845748901367, -28.01970863342285, -4.07905387878418, 50.6001091003418, -62.843772888183594, -11.988554000854492, -84.30481719970703, -23.7200984954834, 58.23987579345703, 18.504188537597656, -76.65352630615234, 33.257606506347656, 51.008384704589844, 63.0673942565918, -57.37456130981445, 51.170955657958984, 54.72771453857422, 6.39027214050293, 19.252605438232422, 4.6363654136657715, 11.566444396972656, -72.91089630126953, 11.537176132202148, -35.133445739746094, 63.63831329345703, -43.02503967285156, -79.24576568603516, -68.05513763427734, -75.87440490722656, -49.211429595947266, -71.42203521728516, -54.053077697753906, -31.466691970825195, -27.346542358398438, -49.55375289916992, -16.829618453979492, 57.269012451171875, 62.589778900146484, -53.62313461303711, 1.9179813861846924, -14.697940826416016, 47.98454666137695, 13.759295463562012, -70.34564971923828, 71.36397552490234, 81.74644470214844, 55.41337585449219, 69.63069152832031, 66.75590515136719, 72.9482650756836, -68.32137298583984, 49.18230438232422, 73.8700942993164, 40.35387420654297, 0.07558732479810715, -34.93399429321289, 73.46485900878906, -84.41986083984375, 60.809532165527344, 0.3341088891029358, -76.68899536132812, 8.943510055541992, -0.2680262625217438, -20.011632919311523, 58.171241760253906, -51.12693405151367, -4.249980449676514, 66.67961883544922, -45.20844650268555, -7.688177585601807, 25.12101936340332, 11.021951675415039, -20.4036808013916, 59.899105072021484, 14.341323852539062, -19.821107864379883, -3.439753532409668, 6.584710597991943, 47.05691146850586, 75.78777313232422, 9.8240385055542, -14.846447944641113, 39.60555648803711, -72.91056823730469, -92.09933471679688, 47.46449279785156, -29.413843154907227, -81.64250183105469, 43.94081115722656, 19.486083984375, 22.519386291503906, 18.821937561035156, 43.2929801940918, 46.828914642333984, -65.40040588378906, -1.209606647491455, 7.879936695098877, -42.13523864746094, -65.02498626708984, -19.574186325073242, -63.1363639831543, 3.384650945663452, -56.23793029785156, 68.13286590576172, 75.10267639160156, -58.738670349121094, -25.764202117919922, -43.6920166015625, -7.042070388793945, -14.682917594909668, -17.6519718170166, -55.56201934814453, -23.5776424407959, -13.757485389709473, 69.43165588378906, 50.53891372680664, 4.087852954864502, -30.976539611816406], \"y\": [4.4482598304748535, -21.551349639892578, 11.40792465209961, 1.333781123161316, -36.386009216308594, -7.800886154174805, 17.03435516357422, -7.24591064453125, -0.14262452721595764, -43.56979751586914, 9.709979057312012, -19.533185958862305, 30.371814727783203, 39.402198791503906, 69.68557739257812, 62.69525146484375, 62.146671295166016, 56.58028793334961, -76.02986145019531, -69.00030517578125, -57.11161422729492, -62.198760986328125, -26.464393615722656, -80.57331085205078, -64.92558288574219, -49.2873420715332, -70.46537017822266, 15.517782211303711, -25.052114486694336, -2.1702678203582764, 30.691390991210938, -38.732460021972656, -74.4123764038086, -0.4104595184326172, -12.368196487426758, 16.39856719970703, -7.312612056732178, -26.361766815185547, -1.1771035194396973, -18.149242401123047, 16.212392807006836, 1.8766013383865356, -4.967414855957031, -5.828280448913574, -16.923498153686523, 37.624237060546875, 49.665958404541016, 51.3908805847168, 50.30913162231445, 26.4985294342041, 61.46052169799805, 12.132923126220703, 41.02153015136719, 27.628366470336914, 54.54361343383789, 4.999932289123535, -43.58101272583008, 73.7714614868164, -27.04196548461914, -76.60296630859375, -74.93193054199219, -8.303616523742676, -83.8011703491211, -70.55852508544922, -56.92851638793945, -61.95793533325195, -19.46199607849121, -31.496051788330078, -47.97669982910156, -2.7562646865844727, -12.61686897277832, -9.56602954864502, 34.74769592285156, 2.823852777481079, -18.505016326904297, 5.930328369140625, 18.384159088134766, -15.25459098815918, -12.55990982055664, 27.231422424316406, 43.15444564819336, -7.39304256439209, -28.882776260375977, 46.917930603027344, 24.944669723510742, -15.132575988769531, -41.409542083740234, -73.56331634521484, -10.048362731933594, -76.66158294677734, -68.7757339477539, -48.30293273925781, -70.41215515136719, -61.579647064208984, -75.92961883544922, -29.55080223083496, -51.710044860839844, -52.67837905883789, -84.8721923828125, 7.568136692047119, -36.7751350402832, -19.39414405822754, -47.81476593017578, -88.3822021484375, -39.15634536743164, -52.989139556884766, 5.82424259185791, -24.783592224121094, -19.462696075439453, -23.415834426879883, -8.347434997558594, -11.023223876953125, 0.8730364441871643, -3.754545211791992, -13.902688026428223, -29.431659698486328, -3.5274276733398438, -8.99573802947998, -5.69174861907959], \"z\": [80.63272857666016, -59.0936393737793, 48.72231674194336, -72.04867553710938, -65.91287231445312, -59.398292541503906, -60.9799919128418, -54.86521911621094, 37.440189361572266, -77.2613525390625, -80.64534759521484, -52.57797622680664, -55.51892852783203, -58.01566696166992, -69.162353515625, -9.876018524169922, -54.33824157714844, -24.841604232788086, 16.85468101501465, 23.27411651611328, 22.409513473510742, 7.3952107429504395, 64.01304626464844, -10.822163581848145, -13.919873237609863, -9.845146179199219, -30.110912322998047, 26.933799743652344, 32.943450927734375, 26.67510223388672, 14.684473991394043, -17.31197738647461, -14.923943519592285, 96.62628936767578, 85.99493408203125, 30.000110626220703, -8.502848625183105, -43.611473083496094, -60.84794235229492, -71.0333251953125, -71.6630859375, 50.12711715698242, -68.2049789428711, -73.60839080810547, -70.98750305175781, -41.58895492553711, -36.67809295654297, -75.69207000732422, -66.61734771728516, -20.02412986755371, -35.55797576904297, -37.368927001953125, -33.096343994140625, -2.7142655849456787, -33.704986572265625, 26.296035766601562, 29.253244400024414, -17.970510482788086, 47.042179107666016, -5.775143623352051, -41.724693298339844, 64.59676361083984, -30.992216110229492, -23.622726440429688, -3.876955032348633, -27.990949630737305, 44.96508026123047, -25.43830108642578, -44.71148681640625, 46.35492706298828, 75.65142059326172, -56.40513229370117, -42.580039978027344, -58.98588562011719, -70.87205505371094, -62.264190673828125, -76.3041000366211, 38.683902740478516, 22.485858917236328, -50.06577682495117, -15.414530754089355, 45.806514739990234, 31.6491756439209, -18.65686798095703, -39.24653244018555, 66.96732330322266, 5.559897422790527, -36.48843765258789, 49.83415603637695, -5.498666763305664, -17.44999122619629, 18.127727508544922, -35.22344970703125, -15.403614044189453, -21.51132583618164, 47.38495635986328, 3.378756284713745, -10.854170799255371, -16.361608505249023, 37.11040115356445, -3.1334903240203857, 16.173492431640625, -38.93711471557617, -23.205244064331055, -24.066307067871094, -33.7904052734375, 20.859668731689453, -11.845132827758789, 64.80724334716797, -12.34650707244873, 94.19955444335938, -22.80036163330078, -84.61084747314453, -42.105079650878906, -47.946449279785156, -63.932437896728516, -18.218263626098633, -52.98310089111328, 54.964847564697266]}, {\"hovertemplate\": \"color=g<br>x=%{x}<br>y=%{y}<br>z=%{z}<extra></extra>\", \"legendgroup\": \"g\", \"marker\": {\"color\": \"#EF553B\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"g\", \"scene\": \"scene\", \"showlegend\": true, \"type\": \"scatter3d\", \"x\": [23.643281936645508, 11.968172073364258, 3.5444746017456055, 5.89685583114624, 7.682126998901367, 13.478333473205566, -0.4247758388519287, -4.524716854095459, 1.9300822019577026, -1.8310210704803467, 11.063920021057129, 15.0502290725708, 24.261194229125977, 26.23409652709961, 23.72462272644043, 32.061439514160156, 41.97663879394531, 39.56591033935547, -2.0306243896484375, -8.458586692810059, 24.50506019592285, 14.679350852966309, 32.163780212402344, 27.504737854003906, 12.23808479309082, -5.192770004272461, 9.473039627075195, -2.76469349861145, 8.936984062194824, -4.896734714508057, -4.690402030944824], \"y\": [73.46062469482422, 88.60043334960938, 86.7532730102539, 119.78094482421875, 114.0484848022461, 104.24891662597656, 0.8861563205718994, 53.82294464111328, 52.78414535522461, 66.535888671875, 58.82744216918945, 41.10039520263672, 63.610595703125, 51.92506790161133, -23.19164276123047, 56.24617385864258, 47.919158935546875, 62.28577423095703, 107.51199340820312, 88.88972473144531, 17.430078506469727, 1.6315102577209473, 33.13533401489258, 45.677276611328125, 103.4489974975586, 107.51396942138672, 90.91043090820312, 99.93169403076172, 89.82836151123047, 90.24043273925781, 106.4412612915039], \"z\": [90.18350982666016, -6.696622848510742, 13.40608024597168, 11.619553565979004, 28.012550354003906, 14.81717586517334, 82.91858673095703, 76.5682373046875, 92.12594604492188, 88.85021209716797, 59.339168548583984, 59.114662170410156, 69.98632049560547, 51.5333137512207, -113.98896026611328, 95.4275131225586, 60.36748504638672, 81.23568725585938, -2.4596099853515625, 25.963834762573242, 67.55467224121094, 66.26422119140625, 58.27777099609375, 72.30074310302734, -13.049555778503418, 17.68865966796875, 32.08248519897461, 38.850467681884766, -26.91890525817871, -16.869943618774414, -24.56075096130371]}],\n",
       "                        {\"legend\": {\"title\": {\"text\": \"color\"}, \"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"scene\": {\"domain\": {\"x\": [0.0, 1.0], \"y\": [0.0, 1.0]}, \"xaxis\": {\"title\": {\"text\": \"x\"}}, \"yaxis\": {\"title\": {\"text\": \"y\"}}, \"zaxis\": {\"title\": {\"text\": \"z\"}}}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('d82540d2-ebd4-495f-b0bc-2cb91beb087e');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# best model for DBSCAN\n",
    "db_best = DBSCAN(eps=best_eps, min_samples=best_min_spamles).fit(X_selected)\n",
    "\n",
    "# plot using tsne \n",
    "X_embedded  = TSNE(n_components=3, perplexity=10,random_state=24).fit_transform( X_selected )\n",
    "\n",
    "fig = px.scatter_3d(x=X_embedded [:,0],y=X_embedded [:,1],z=X_embedded [:,2],color=colors[db_best.labels_])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "# EVALUATION\n",
    "We will compare best of 3 models by using 8 metrics:\n",
    "* Estimated number of clusters\n",
    "* Estimated number of noise points\n",
    "* Homogeneity: For perfect clustering, each cluster contains only members of a single class.\n",
    "* Completeness: For perfect clustering, all members of a given class are assigned to the same cluster.\n",
    "* V-measure: Harmonic mean of Homogeneity and Completeness.\n",
    "* Adjusted Rand Index: Given the knowledge of the ground truth class, the adjusted Rand index is a function that measures the similarity of the two assignments, ignoring permutations and with chance normalization:\n",
    "* Adjusted Mutual Information: Given the knowledge of the ground truth class, the Mutual Information is a function that measures the agreement of the two assignments, ignoring permutations.\n",
    "* Fowlkes-Mallows score: Geometric mean of precision and recall.\n",
    "* Silhouette Coefficient: If the ground truth labels are not known, the Silhouette Coefficient is calculated using the mean intra-cluster distance (a) and the mean nearest-cluster distance (b) for each sample by (b - a) / max(a, b)\n",
    "\n",
    "see https://scikit-learn.org/stable/modules/clustering.html#clustering-performance-evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "K-MEANS:\n",
      "Estimated number of clusters: 4\n",
      "Estimated number of noise points: 0\n",
      "Homogeneity: 0.157\n",
      "Completeness: 0.133\n",
      "V-measure: 0.144\n",
      "Adjusted Rand Index: 0.075\n",
      "Adjusted Mutual Information: 0.121\n",
      "Fowlkes-Mallows score: 0.344\n",
      "Silhouette Coefficient: 0.330\n",
      "\n",
      "\n",
      "PCA + K-MEANS:\n",
      "Estimated number of clusters: 3\n",
      "Estimated number of noise points: 0\n",
      "Homogeneity: 0.147\n",
      "Completeness: 0.176\n",
      "V-measure: 0.160\n",
      "Adjusted Rand Index: 0.077\n",
      "Adjusted Mutual Information: 0.143\n",
      "Fowlkes-Mallows score: 0.423\n",
      "Silhouette Coefficient: 0.437\n",
      "\n",
      "\n",
      "AGNES:\n",
      "Estimated number of clusters: 6\n",
      "Estimated number of noise points: 0\n",
      "Homogeneity: 0.211\n",
      "Completeness: 0.188\n",
      "V-measure: 0.199\n",
      "Adjusted Rand Index: 0.110\n",
      "Adjusted Mutual Information: 0.156\n",
      "Fowlkes-Mallows score: 0.348\n",
      "Silhouette Coefficient: 0.276\n",
      "\n",
      "\n",
      "DBSCAN:\n",
      "Estimated number of clusters: 2\n",
      "Estimated number of noise points: 0\n",
      "Homogeneity: 0.029\n",
      "Completeness: 0.045\n",
      "V-measure: 0.035\n",
      "Adjusted Rand Index: -0.035\n",
      "Adjusted Mutual Information: 0.024\n",
      "Fowlkes-Mallows score: 0.557\n",
      "Silhouette Coefficient: 0.518\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# print metric for chosen models\n",
    "models = [km4, km_pca, agnes6, db_best] \n",
    "names = [\"K-MEANS:\",\"PCA + K-MEANS:\",\"AGNES:\", \"DBSCAN:\"]\n",
    "\n",
    "for i, model in enumerate(models):\n",
    "    labels = model.labels_\n",
    "    n = len(np.unique(labels))\n",
    "    y = np.round(MinMaxScaler((0,n)).fit_transform(y_original)).ravel()\n",
    "    # Number of clusters in labels, ignoring noise if present.\n",
    "    n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n",
    "    n_noise_ = list(labels).count(-1)\n",
    "    print(names[i])\n",
    "    print('Estimated number of clusters: %d' % n_clusters_)\n",
    "    print('Estimated number of noise points: %d' % n_noise_)\n",
    "    print(\"Homogeneity: %0.3f\" % homogeneity_score(y, labels))\n",
    "    print(\"Completeness: %0.3f\" % completeness_score(y, labels))\n",
    "    print(\"V-measure: %0.3f\" % v_measure_score(y, labels))\n",
    "    print(\"Adjusted Rand Index: %0.3f\"\n",
    "          % adjusted_rand_score(y, labels))\n",
    "    print(\"Adjusted Mutual Information: %0.3f\"\n",
    "          % adjusted_mutual_info_score(y, labels))\n",
    "    print(\"Fowlkes-Mallows score: %0.3f\"\n",
    "          % fowlkes_mallows_score(y, labels))\n",
    "    print(\"Silhouette Coefficient: %0.3f\"\n",
    "          % silhouette_score(X, labels))\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "Only metric doesn't reqire ground-truth labels is Silhouette Coefficient. For it, DBSCAN takes ahead, then comes PCA+KMEANS and followed by K-MEANS and AGNES. Its results are correlated with Fowlkes-Mallows score altough they require different inputs with only difference of swapping AGNES and K-MEANS.\n",
    "\n",
    "But from the perspective of Homogeneity and Completeness principles, AGNES performs best. Followings are PCA+KMEANS, K-MEANS and DBSCAN. The results are similar for Mutual Information.\n",
    "\n",
    "And finally for Rand Index AGNES performs best again. Followings are K-MEANS, PCA+KMEANS and DBSCAN. "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}