KMedoids on socio-economic dataset.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b52e9c4c",
   "metadata": {},
   "source": [
    "# K-Medoids clustering on socio-economic dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2d344c85",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Normalised Age (Yrs)</th>\n",
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       "     Normalised Age (Yrs)  Gender (Male)  Education (<Class 10)  \\\n",
       "0               -0.927352              1                      1   \n",
       "1                0.387063              1                      0   \n",
       "2               -0.739578              1                      0   \n",
       "3                0.762611              0                      1   \n",
       "4               -1.678446              1                      0   \n",
       "..                    ...            ...                    ...   \n",
       "476             -0.739578              1                      0   \n",
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       "478              2.077026              1                      0   \n",
       "479             -0.551804              1                      0   \n",
       "480             -0.551804              1                      0   \n",
       "\n",
       "     Education (Class 10-12)  Graduate  Higher Edu  Income <20k  \\\n",
       "0                          0         0           0            1   \n",
       "1                          0         1           0            0   \n",
       "2                          0         1           0            0   \n",
       "3                          0         0           0            1   \n",
       "4                          1         0           0            0   \n",
       "..                       ...       ...         ...          ...   \n",
       "476                        0         1           0            0   \n",
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       "478                        0         1           0            0   \n",
       "479                        0         1           0            0   \n",
       "480                        0         0           1            0   \n",
       "\n",
       "     Income 20-40k  Income 40-60k  Income 60-80k  Income >80k  \\\n",
       "0                0              0              0            0   \n",
       "1                0              1              0            0   \n",
       "2                0              1              0            0   \n",
       "3                0              0              0            0   \n",
       "4                1              0              0            0   \n",
       "..             ...            ...            ...          ...   \n",
       "476              0              1              0            0   \n",
       "477              0              0              1            0   \n",
       "478              0              0              1            0   \n",
       "479              0              1              0            0   \n",
       "480              0              1              0            0   \n",
       "\n",
       "     Experience (<1yr)  Experience (1-2yr)  Experience (2-5yr)  \\\n",
       "0                    0                   0                   0   \n",
       "1                    0                   0                   0   \n",
       "2                    0                   0                   0   \n",
       "3                    0                   0                   1   \n",
       "4                    1                   0                   0   \n",
       "..                 ...                 ...                 ...   \n",
       "476                  0                   0                   0   \n",
       "477                  0                   0                   1   \n",
       "478                  0                   0                   0   \n",
       "479                  0                   0                   0   \n",
       "480                  0                   0                   0   \n",
       "\n",
       "     Experience (5-10yr)  Experience (10-20yr)  Experience (20-30yr)  \\\n",
       "0                      1                     0                     0   \n",
       "1                      0                     1                     0   \n",
       "2                      1                     0                     0   \n",
       "3                      0                     0                     0   \n",
       "4                      0                     0                     0   \n",
       "..                   ...                   ...                   ...   \n",
       "476                    1                     0                     0   \n",
       "477                    0                     0                     0   \n",
       "478                    0                     0                     1   \n",
       "479                    0                     1                     0   \n",
       "480                    0                     1                     0   \n",
       "\n",
       "     Experience (>30yr)  Helmet (Full-mask)  \n",
       "0                     0                   1  \n",
       "1                     0                   0  \n",
       "2                     0                   1  \n",
       "3                     0                   0  \n",
       "4                     0                   1  \n",
       "..                  ...                 ...  \n",
       "476                   0                   1  \n",
       "477                   0                   1  \n",
       "478                   0                   1  \n",
       "479                   0                   1  \n",
       "480                   0                   1  \n",
       "\n",
       "[481 rows x 19 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn_extra.cluster import KMedoids\n",
    "from sklearn.metrics import silhouette_score\n",
    "\n",
    "df = pd.read_excel('Preprocessed_data_standardscaler.xlsx')\n",
    "\n",
    "# Dropping the ID Column, as it is not required in clustering.\n",
    "\n",
    "new_df = df.drop(columns=['ID'])\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "16789107",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>no. of clusters</th>\n",
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      "text/plain": [
       "   no. of clusters  silhouette score\n",
       "0                2          0.137599\n",
       "1                3          0.152380\n",
       "2                4          0.170523\n",
       "3                5          0.172540\n",
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      ]
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     "execution_count": 7,
     "metadata": {},
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   ],
   "source": [
    "# Now the Silhouette Score method is used to determine the number of clusters to achieve the best possible clustering\n",
    "# Here the scores are calculated for k = {2,3,4,5,6}\n",
    "\n",
    "scores = {}\n",
    "\n",
    "for i in range(2,7):\n",
    "    kmedoids = KMedoids(n_clusters=i,method='pam',init='build',random_state=42)\n",
    "    kmedoids.fit(new_df)\n",
    "    score = silhouette_score(new_df,kmedoids.labels_)\n",
    "    scores[i]=score\n",
    "\n",
    "df_scores = pd.DataFrame(list(scores.items()), columns=['no. of clusters', 'silhouette score'])\n",
    "df_scores\n",
    "\n",
    "# since setting k = 5 yields the highest score, the number of clusters are chosen to be 5.\n",
    "# As can be seen in the table below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8cc4081b",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Normalised Age (Yrs)</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.762611</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-1.678446</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>-0.739578</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>-1.302899</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>2.077026</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>-0.551804</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>-0.551804</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>481 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Normalised Age (Yrs)  Gender (Male)  Education (<Class 10)  \\\n",
       "0               -0.927352              1                      1   \n",
       "1                0.387063              1                      0   \n",
       "2               -0.739578              1                      0   \n",
       "3                0.762611              0                      1   \n",
       "4               -1.678446              1                      0   \n",
       "..                    ...            ...                    ...   \n",
       "476             -0.739578              1                      0   \n",
       "477             -1.302899              1                      0   \n",
       "478              2.077026              1                      0   \n",
       "479             -0.551804              1                      0   \n",
       "480             -0.551804              1                      0   \n",
       "\n",
       "     Education (Class 10-12)  Graduate  Higher Edu  Income <20k  \\\n",
       "0                          0         0           0            1   \n",
       "1                          0         1           0            0   \n",
       "2                          0         1           0            0   \n",
       "3                          0         0           0            1   \n",
       "4                          1         0           0            0   \n",
       "..                       ...       ...         ...          ...   \n",
       "476                        0         1           0            0   \n",
       "477                        0         1           0            0   \n",
       "478                        0         1           0            0   \n",
       "479                        0         1           0            0   \n",
       "480                        0         0           1            0   \n",
       "\n",
       "     Income 20-40k  Income 40-60k  Income 60-80k  Income >80k  \\\n",
       "0                0              0              0            0   \n",
       "1                0              1              0            0   \n",
       "2                0              1              0            0   \n",
       "3                0              0              0            0   \n",
       "4                1              0              0            0   \n",
       "..             ...            ...            ...          ...   \n",
       "476              0              1              0            0   \n",
       "477              0              0              1            0   \n",
       "478              0              0              1            0   \n",
       "479              0              1              0            0   \n",
       "480              0              1              0            0   \n",
       "\n",
       "     Experience (<1yr)  Experience (1-2yr)  Experience (2-5yr)  \\\n",
       "0                    0                   0                   0   \n",
       "1                    0                   0                   0   \n",
       "2                    0                   0                   0   \n",
       "3                    0                   0                   1   \n",
       "4                    1                   0                   0   \n",
       "..                 ...                 ...                 ...   \n",
       "476                  0                   0                   0   \n",
       "477                  0                   0                   1   \n",
       "478                  0                   0                   0   \n",
       "479                  0                   0                   0   \n",
       "480                  0                   0                   0   \n",
       "\n",
       "     Experience (5-10yr)  Experience (10-20yr)  Experience (20-30yr)  \\\n",
       "0                      1                     0                     0   \n",
       "1                      0                     1                     0   \n",
       "2                      1                     0                     0   \n",
       "3                      0                     0                     0   \n",
       "4                      0                     0                     0   \n",
       "..                   ...                   ...                   ...   \n",
       "476                    1                     0                     0   \n",
       "477                    0                     0                     0   \n",
       "478                    0                     0                     1   \n",
       "479                    0                     1                     0   \n",
       "480                    0                     1                     0   \n",
       "\n",
       "     Experience (>30yr)  Helmet (Full-mask)  Cluster  \n",
       "0                     0                   1        2  \n",
       "1                     0                   0        1  \n",
       "2                     0                   1        4  \n",
       "3                     0                   0        2  \n",
       "4                     0                   1        3  \n",
       "..                  ...                 ...      ...  \n",
       "476                   0                   1        4  \n",
       "477                   0                   1        4  \n",
       "478                   0                   1        0  \n",
       "479                   0                   1        1  \n",
       "480                   0                   1        1  \n",
       "\n",
       "[481 rows x 20 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now applying the K-Medoids algorithm.\n",
    "\n",
    "optimal_clusters = 5\n",
    "\n",
    "kmedoids_1 = KMedoids(n_clusters=optimal_clusters,method='pam',init='build',random_state=42)\n",
    "kmedoids_1.fit(new_df)\n",
    "\n",
    "list1 = list(kmedoids_1.labels_)\n",
    "\n",
    "df_clustered = new_df.copy()\n",
    "\n",
    "df_clustered['Cluster'] = list1\n",
    "df_clustered\n",
    "\n",
    "# As can be seen in the below dataset, a new 'Cluster' column has been added at the very end:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "33bab839",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Age (Yrs)</th>\n",
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       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>44</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <th>478</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>481 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age (Yrs)  Gender (Male)  Education (<Class 10)  Education (Class 10-12)  \\\n",
       "0           26              1                      1                        0   \n",
       "1           40              1                      0                        0   \n",
       "2           28              1                      0                        0   \n",
       "3           44              0                      1                        0   \n",
       "4           18              1                      0                        1   \n",
       "..         ...            ...                    ...                      ...   \n",
       "476         28              1                      0                        0   \n",
       "477         22              1                      0                        0   \n",
       "478         58              1                      0                        0   \n",
       "479         30              1                      0                        0   \n",
       "480         30              1                      0                        0   \n",
       "\n",
       "     Graduate  Higher Edu  Income <20k  Income 20-40k  Income 40-60k  \\\n",
       "0           0           0            1              0              0   \n",
       "1           1           0            0              0              1   \n",
       "2           1           0            0              0              1   \n",
       "3           0           0            1              0              0   \n",
       "4           0           0            0              1              0   \n",
       "..        ...         ...          ...            ...            ...   \n",
       "476         1           0            0              0              1   \n",
       "477         1           0            0              0              0   \n",
       "478         1           0            0              0              0   \n",
       "479         1           0            0              0              1   \n",
       "480         0           1            0              0              1   \n",
       "\n",
       "     Income 60-80k  Income >80k  Experience (<1yr)  Experience (1-2yr)  \\\n",
       "0                0            0                  0                   0   \n",
       "1                0            0                  0                   0   \n",
       "2                0            0                  0                   0   \n",
       "3                0            0                  0                   0   \n",
       "4                0            0                  1                   0   \n",
       "..             ...          ...                ...                 ...   \n",
       "476              0            0                  0                   0   \n",
       "477              1            0                  0                   0   \n",
       "478              1            0                  0                   0   \n",
       "479              0            0                  0                   0   \n",
       "480              0            0                  0                   0   \n",
       "\n",
       "     Experience (2-5yr)  Experience (5-10yr)  Experience (10-20yr)  \\\n",
       "0                     0                    1                     0   \n",
       "1                     0                    0                     1   \n",
       "2                     0                    1                     0   \n",
       "3                     1                    0                     0   \n",
       "4                     0                    0                     0   \n",
       "..                  ...                  ...                   ...   \n",
       "476                   0                    1                     0   \n",
       "477                   1                    0                     0   \n",
       "478                   0                    0                     0   \n",
       "479                   0                    0                     1   \n",
       "480                   0                    0                     1   \n",
       "\n",
       "     Experience (20-30yr)  Experience (>30yr)  Helmet (Full-mask)  Cluster  \n",
       "0                       0                   0                   1        2  \n",
       "1                       0                   0                   0        1  \n",
       "2                       0                   0                   1        4  \n",
       "3                       0                   0                   0        2  \n",
       "4                       0                   0                   1        3  \n",
       "..                    ...                 ...                 ...      ...  \n",
       "476                     0                   0                   1        4  \n",
       "477                     0                   0                   1        4  \n",
       "478                     1                   0                   1        0  \n",
       "479                     0                   0                   1        1  \n",
       "480                     0                   0                   1        1  \n",
       "\n",
       "[481 rows x 20 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df = df_clustered.copy()\n",
    "\n",
    "old_df = pd.read_excel('Asansol socio-economic data 1.xlsx')\n",
    "age = list(old_df['Age (Yrs)'])\n",
    "\n",
    "final_df['Age (Yrs)'] = age\n",
    "\n",
    "final_df = final_df.drop(columns = ['Normalised Age (Yrs)'])\n",
    "\n",
    "list2 = list(final_df.columns)\n",
    "new_order = [list2[-1]] + list2[0:-1]\n",
    "\n",
    "final_df = final_df[new_order]\n",
    "final_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0753e83e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age (Yrs)</th>\n",
       "      <th>Gender (Male)</th>\n",
       "      <th>Education (&lt;Class 10)</th>\n",
       "      <th>Education (Class 10-12)</th>\n",
       "      <th>Graduate</th>\n",
       "      <th>Higher Edu</th>\n",
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       "      <th>Income 20-40k</th>\n",
       "      <th>Income 40-60k</th>\n",
       "      <th>Income 60-80k</th>\n",
       "      <th>Income &gt;80k</th>\n",
       "      <th>Experience (&lt;1yr)</th>\n",
       "      <th>Experience (1-2yr)</th>\n",
       "      <th>Experience (2-5yr)</th>\n",
       "      <th>Experience (5-10yr)</th>\n",
       "      <th>Experience (10-20yr)</th>\n",
       "      <th>Experience (20-30yr)</th>\n",
       "      <th>Experience (&gt;30yr)</th>\n",
       "      <th>Helmet (Full-mask)</th>\n",
       "      <th>Cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.0</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>51.873239</td>\n",
       "      <td>0.943662</td>\n",
       "      <td>0.140845</td>\n",
       "      <td>0.183099</td>\n",
       "      <td>0.577465</td>\n",
       "      <td>0.098592</td>\n",
       "      <td>0.070423</td>\n",
       "      <td>0.239437</td>\n",
       "      <td>0.267606</td>\n",
       "      <td>0.380282</td>\n",
       "      <td>0.042254</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.014085</td>\n",
       "      <td>0.028169</td>\n",
       "      <td>0.056338</td>\n",
       "      <td>0.169014</td>\n",
       "      <td>0.591549</td>\n",
       "      <td>0.140845</td>\n",
       "      <td>0.760563</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.349388</td>\n",
       "      <td>0.232214</td>\n",
       "      <td>0.350338</td>\n",
       "      <td>0.389500</td>\n",
       "      <td>0.497479</td>\n",
       "      <td>0.300235</td>\n",
       "      <td>0.257679</td>\n",
       "      <td>0.429777</td>\n",
       "      <td>0.445862</td>\n",
       "      <td>0.488911</td>\n",
       "      <td>0.202599</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.118678</td>\n",
       "      <td>0.166633</td>\n",
       "      <td>0.232214</td>\n",
       "      <td>0.377432</td>\n",
       "      <td>0.495046</td>\n",
       "      <td>0.350338</td>\n",
       "      <td>0.429777</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>35.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>46.000000</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>51.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>58.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</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>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>73.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Age (Yrs)  Gender (Male)  Education (<Class 10)  \\\n",
       "count  71.000000      71.000000              71.000000   \n",
       "mean   51.873239       0.943662               0.140845   \n",
       "std     8.349388       0.232214               0.350338   \n",
       "min    35.000000       0.000000               0.000000   \n",
       "25%    46.000000       1.000000               0.000000   \n",
       "50%    51.000000       1.000000               0.000000   \n",
       "75%    58.500000       1.000000               0.000000   \n",
       "max    73.000000       1.000000               1.000000   \n",
       "\n",
       "       Education (Class 10-12)   Graduate  Higher Edu  Income <20k  \\\n",
       "count                71.000000  71.000000   71.000000    71.000000   \n",
       "mean                  0.183099   0.577465    0.098592     0.070423   \n",
       "std                   0.389500   0.497479    0.300235     0.257679   \n",
       "min                   0.000000   0.000000    0.000000     0.000000   \n",
       "25%                   0.000000   0.000000    0.000000     0.000000   \n",
       "50%                   0.000000   1.000000    0.000000     0.000000   \n",
       "75%                   0.000000   1.000000    0.000000     0.000000   \n",
       "max                   1.000000   1.000000    1.000000     1.000000   \n",
       "\n",
       "       Income 20-40k  Income 40-60k  Income 60-80k  Income >80k  \\\n",
       "count      71.000000      71.000000      71.000000    71.000000   \n",
       "mean        0.239437       0.267606       0.380282     0.042254   \n",
       "std         0.429777       0.445862       0.488911     0.202599   \n",
       "min         0.000000       0.000000       0.000000     0.000000   \n",
       "25%         0.000000       0.000000       0.000000     0.000000   \n",
       "50%         0.000000       0.000000       0.000000     0.000000   \n",
       "75%         0.000000       1.000000       1.000000     0.000000   \n",
       "max         1.000000       1.000000       1.000000     1.000000   \n",
       "\n",
       "       Experience (<1yr)  Experience (1-2yr)  Experience (2-5yr)  \\\n",
       "count               71.0           71.000000           71.000000   \n",
       "mean                 0.0            0.014085            0.028169   \n",
       "std                  0.0            0.118678            0.166633   \n",
       "min                  0.0            0.000000            0.000000   \n",
       "25%                  0.0            0.000000            0.000000   \n",
       "50%                  0.0            0.000000            0.000000   \n",
       "75%                  0.0            0.000000            0.000000   \n",
       "max                  0.0            1.000000            1.000000   \n",
       "\n",
       "       Experience (5-10yr)  Experience (10-20yr)  Experience (20-30yr)  \\\n",
       "count            71.000000             71.000000             71.000000   \n",
       "mean              0.056338              0.169014              0.591549   \n",
       "std               0.232214              0.377432              0.495046   \n",
       "min               0.000000              0.000000              0.000000   \n",
       "25%               0.000000              0.000000              0.000000   \n",
       "50%               0.000000              0.000000              1.000000   \n",
       "75%               0.000000              0.000000              1.000000   \n",
       "max               1.000000              1.000000              1.000000   \n",
       "\n",
       "       Experience (>30yr)  Helmet (Full-mask)  Cluster  \n",
       "count           71.000000           71.000000     71.0  \n",
       "mean             0.140845            0.760563      0.0  \n",
       "std              0.350338            0.429777      0.0  \n",
       "min              0.000000            0.000000      0.0  \n",
       "25%              0.000000            1.000000      0.0  \n",
       "50%              0.000000            1.000000      0.0  \n",
       "75%              0.000000            1.000000      0.0  \n",
       "max              1.000000            1.000000      0.0  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_1 = final_df.loc[final_df['Cluster']==0]\n",
    "cluster_1\n",
    "cluster_1.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "be78feea",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>count</th>\n",
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       "      <td>82.000000</td>\n",
       "      <td>82.0</td>\n",
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       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
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       "      <td>82.000000</td>\n",
       "      <td>82.0</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>38.329268</td>\n",
       "      <td>0.951220</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.085366</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.036585</td>\n",
       "      <td>0.073171</td>\n",
       "      <td>0.073171</td>\n",
       "      <td>0.658537</td>\n",
       "      <td>0.170732</td>\n",
       "      <td>0.024390</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.048780</td>\n",
       "      <td>0.048780</td>\n",
       "      <td>0.024390</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.024390</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.299235</td>\n",
       "      <td>0.216734</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.281145</td>\n",
       "      <td>0.329243</td>\n",
       "      <td>0.188897</td>\n",
       "      <td>0.262019</td>\n",
       "      <td>0.262019</td>\n",
       "      <td>0.477119</td>\n",
       "      <td>0.378590</td>\n",
       "      <td>0.155207</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.216734</td>\n",
       "      <td>0.216734</td>\n",
       "      <td>0.155207</td>\n",
       "      <td>0.355623</td>\n",
       "      <td>0.155207</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.329243</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>35.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>37.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</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>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>40.750000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</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>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>58.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Age (Yrs)  Gender (Male)  Education (<Class 10)  \\\n",
       "count  82.000000      82.000000                   82.0   \n",
       "mean   38.329268       0.951220                    0.0   \n",
       "std     6.299235       0.216734                    0.0   \n",
       "min    28.000000       0.000000                    0.0   \n",
       "25%    35.000000       1.000000                    0.0   \n",
       "50%    37.000000       1.000000                    0.0   \n",
       "75%    40.750000       1.000000                    0.0   \n",
       "max    58.000000       1.000000                    0.0   \n",
       "\n",
       "       Education (Class 10-12)   Graduate  Higher Edu  Income <20k  \\\n",
       "count                82.000000  82.000000   82.000000    82.000000   \n",
       "mean                  0.085366   0.878049    0.036585     0.073171   \n",
       "std                   0.281145   0.329243    0.188897     0.262019   \n",
       "min                   0.000000   0.000000    0.000000     0.000000   \n",
       "25%                   0.000000   1.000000    0.000000     0.000000   \n",
       "50%                   0.000000   1.000000    0.000000     0.000000   \n",
       "75%                   0.000000   1.000000    0.000000     0.000000   \n",
       "max                   1.000000   1.000000    1.000000     1.000000   \n",
       "\n",
       "       Income 20-40k  Income 40-60k  Income 60-80k  Income >80k  \\\n",
       "count      82.000000      82.000000      82.000000    82.000000   \n",
       "mean        0.073171       0.658537       0.170732     0.024390   \n",
       "std         0.262019       0.477119       0.378590     0.155207   \n",
       "min         0.000000       0.000000       0.000000     0.000000   \n",
       "25%         0.000000       0.000000       0.000000     0.000000   \n",
       "50%         0.000000       1.000000       0.000000     0.000000   \n",
       "75%         0.000000       1.000000       0.000000     0.000000   \n",
       "max         1.000000       1.000000       1.000000     1.000000   \n",
       "\n",
       "       Experience (<1yr)  Experience (1-2yr)  Experience (2-5yr)  \\\n",
       "count               82.0           82.000000           82.000000   \n",
       "mean                 0.0            0.048780            0.048780   \n",
       "std                  0.0            0.216734            0.216734   \n",
       "min                  0.0            0.000000            0.000000   \n",
       "25%                  0.0            0.000000            0.000000   \n",
       "50%                  0.0            0.000000            0.000000   \n",
       "75%                  0.0            0.000000            0.000000   \n",
       "max                  0.0            1.000000            1.000000   \n",
       "\n",
       "       Experience (5-10yr)  Experience (10-20yr)  Experience (20-30yr)  \\\n",
       "count            82.000000             82.000000             82.000000   \n",
       "mean              0.024390              0.853659              0.024390   \n",
       "std               0.155207              0.355623              0.155207   \n",
       "min               0.000000              0.000000              0.000000   \n",
       "25%               0.000000              1.000000              0.000000   \n",
       "50%               0.000000              1.000000              0.000000   \n",
       "75%               0.000000              1.000000              0.000000   \n",
       "max               1.000000              1.000000              1.000000   \n",
       "\n",
       "       Experience (>30yr)  Helmet (Full-mask)  Cluster  \n",
       "count                82.0           82.000000     82.0  \n",
       "mean                  0.0            0.878049      1.0  \n",
       "std                   0.0            0.329243      0.0  \n",
       "min                   0.0            0.000000      1.0  \n",
       "25%                   0.0            1.000000      1.0  \n",
       "50%                   0.0            1.000000      1.0  \n",
       "75%                   0.0            1.000000      1.0  \n",
       "max                   0.0            1.000000      1.0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_2 = final_df.loc[final_df['Cluster']==1]\n",
    "cluster_2.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5aefac50",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        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>Age (Yrs)</th>\n",
       "      <th>Gender (Male)</th>\n",
       "      <th>Education (&lt;Class 10)</th>\n",
       "      <th>Education (Class 10-12)</th>\n",
       "      <th>Graduate</th>\n",
       "      <th>Higher Edu</th>\n",
       "      <th>Income &lt;20k</th>\n",
       "      <th>Income 20-40k</th>\n",
       "      <th>Income 40-60k</th>\n",
       "      <th>Income 60-80k</th>\n",
       "      <th>Income &gt;80k</th>\n",
       "      <th>Experience (&lt;1yr)</th>\n",
       "      <th>Experience (1-2yr)</th>\n",
       "      <th>Experience (2-5yr)</th>\n",
       "      <th>Experience (5-10yr)</th>\n",
       "      <th>Experience (10-20yr)</th>\n",
       "      <th>Experience (20-30yr)</th>\n",
       "      <th>Experience (&gt;30yr)</th>\n",
       "      <th>Helmet (Full-mask)</th>\n",
       "      <th>Cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.0</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.00000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.0</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>32.298969</td>\n",
       "      <td>0.958763</td>\n",
       "      <td>0.742268</td>\n",
       "      <td>0.195876</td>\n",
       "      <td>0.030928</td>\n",
       "      <td>0.030928</td>\n",
       "      <td>0.865979</td>\n",
       "      <td>0.092784</td>\n",
       "      <td>0.020619</td>\n",
       "      <td>0.020619</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.051546</td>\n",
       "      <td>0.103093</td>\n",
       "      <td>0.14433</td>\n",
       "      <td>0.494845</td>\n",
       "      <td>0.175258</td>\n",
       "      <td>0.030928</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.824742</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.214780</td>\n",
       "      <td>0.199871</td>\n",
       "      <td>0.439658</td>\n",
       "      <td>0.398935</td>\n",
       "      <td>0.174022</td>\n",
       "      <td>0.174022</td>\n",
       "      <td>0.342444</td>\n",
       "      <td>0.291636</td>\n",
       "      <td>0.142842</td>\n",
       "      <td>0.142842</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.222258</td>\n",
       "      <td>0.305660</td>\n",
       "      <td>0.35325</td>\n",
       "      <td>0.502571</td>\n",
       "      <td>0.382162</td>\n",
       "      <td>0.174022</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.382162</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>26.000000</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>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>50.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Age (Yrs)  Gender (Male)  Education (<Class 10)  \\\n",
       "count  97.000000      97.000000              97.000000   \n",
       "mean   32.298969       0.958763               0.742268   \n",
       "std     8.214780       0.199871               0.439658   \n",
       "min    18.000000       0.000000               0.000000   \n",
       "25%    26.000000       1.000000               0.000000   \n",
       "50%    32.000000       1.000000               1.000000   \n",
       "75%    38.000000       1.000000               1.000000   \n",
       "max    50.000000       1.000000               1.000000   \n",
       "\n",
       "       Education (Class 10-12)   Graduate  Higher Edu  Income <20k  \\\n",
       "count                97.000000  97.000000   97.000000    97.000000   \n",
       "mean                  0.195876   0.030928    0.030928     0.865979   \n",
       "std                   0.398935   0.174022    0.174022     0.342444   \n",
       "min                   0.000000   0.000000    0.000000     0.000000   \n",
       "25%                   0.000000   0.000000    0.000000     1.000000   \n",
       "50%                   0.000000   0.000000    0.000000     1.000000   \n",
       "75%                   0.000000   0.000000    0.000000     1.000000   \n",
       "max                   1.000000   1.000000    1.000000     1.000000   \n",
       "\n",
       "       Income 20-40k  Income 40-60k  Income 60-80k  Income >80k  \\\n",
       "count      97.000000      97.000000      97.000000         97.0   \n",
       "mean        0.092784       0.020619       0.020619          0.0   \n",
       "std         0.291636       0.142842       0.142842          0.0   \n",
       "min         0.000000       0.000000       0.000000          0.0   \n",
       "25%         0.000000       0.000000       0.000000          0.0   \n",
       "50%         0.000000       0.000000       0.000000          0.0   \n",
       "75%         0.000000       0.000000       0.000000          0.0   \n",
       "max         1.000000       1.000000       1.000000          0.0   \n",
       "\n",
       "       Experience (<1yr)  Experience (1-2yr)  Experience (2-5yr)  \\\n",
       "count          97.000000           97.000000            97.00000   \n",
       "mean            0.051546            0.103093             0.14433   \n",
       "std             0.222258            0.305660             0.35325   \n",
       "min             0.000000            0.000000             0.00000   \n",
       "25%             0.000000            0.000000             0.00000   \n",
       "50%             0.000000            0.000000             0.00000   \n",
       "75%             0.000000            0.000000             0.00000   \n",
       "max             1.000000            1.000000             1.00000   \n",
       "\n",
       "       Experience (5-10yr)  Experience (10-20yr)  Experience (20-30yr)  \\\n",
       "count            97.000000             97.000000             97.000000   \n",
       "mean              0.494845              0.175258              0.030928   \n",
       "std               0.502571              0.382162              0.174022   \n",
       "min               0.000000              0.000000              0.000000   \n",
       "25%               0.000000              0.000000              0.000000   \n",
       "50%               0.000000              0.000000              0.000000   \n",
       "75%               1.000000              0.000000              0.000000   \n",
       "max               1.000000              1.000000              1.000000   \n",
       "\n",
       "       Experience (>30yr)  Helmet (Full-mask)  Cluster  \n",
       "count                97.0           97.000000     97.0  \n",
       "mean                  0.0            0.824742      2.0  \n",
       "std                   0.0            0.382162      0.0  \n",
       "min                   0.0            0.000000      2.0  \n",
       "25%                   0.0            1.000000      2.0  \n",
       "50%                   0.0            1.000000      2.0  \n",
       "75%                   0.0            1.000000      2.0  \n",
       "max                   0.0            1.000000      2.0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_3 = final_df.loc[final_df['Cluster']==2]\n",
    "cluster_3.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "3a50b69a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age (Yrs)</th>\n",
       "      <th>Gender (Male)</th>\n",
       "      <th>Education (&lt;Class 10)</th>\n",
       "      <th>Education (Class 10-12)</th>\n",
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       "      <th>Experience (5-10yr)</th>\n",
       "      <th>Experience (10-20yr)</th>\n",
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       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.0</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>35.350877</td>\n",
       "      <td>0.964912</td>\n",
       "      <td>0.061404</td>\n",
       "      <td>0.894737</td>\n",
       "      <td>0.017544</td>\n",
       "      <td>0.026316</td>\n",
       "      <td>0.070175</td>\n",
       "      <td>0.912281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.008772</td>\n",
       "      <td>0.008772</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>0.149123</td>\n",
       "      <td>0.096491</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.412281</td>\n",
       "      <td>0.017544</td>\n",
       "      <td>0.008772</td>\n",
       "      <td>0.780702</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.370432</td>\n",
       "      <td>0.184814</td>\n",
       "      <td>0.241129</td>\n",
       "      <td>0.308247</td>\n",
       "      <td>0.131866</td>\n",
       "      <td>0.160779</td>\n",
       "      <td>0.256570</td>\n",
       "      <td>0.284135</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.093659</td>\n",
       "      <td>0.093659</td>\n",
       "      <td>0.224283</td>\n",
       "      <td>0.357782</td>\n",
       "      <td>0.296567</td>\n",
       "      <td>0.442292</td>\n",
       "      <td>0.494418</td>\n",
       "      <td>0.131866</td>\n",
       "      <td>0.093659</td>\n",
       "      <td>0.415598</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>28.000000</td>\n",
       "      <td>1.000000</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>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>34.500000</td>\n",
       "      <td>1.000000</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>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>42.000000</td>\n",
       "      <td>1.000000</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>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>59.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Age (Yrs)  Gender (Male)  Education (<Class 10)  \\\n",
       "count  114.000000     114.000000             114.000000   \n",
       "mean    35.350877       0.964912               0.061404   \n",
       "std      9.370432       0.184814               0.241129   \n",
       "min     16.000000       0.000000               0.000000   \n",
       "25%     28.000000       1.000000               0.000000   \n",
       "50%     34.500000       1.000000               0.000000   \n",
       "75%     42.000000       1.000000               0.000000   \n",
       "max     59.000000       1.000000               1.000000   \n",
       "\n",
       "       Education (Class 10-12)    Graduate  Higher Edu  Income <20k  \\\n",
       "count               114.000000  114.000000  114.000000   114.000000   \n",
       "mean                  0.894737    0.017544    0.026316     0.070175   \n",
       "std                   0.308247    0.131866    0.160779     0.256570   \n",
       "min                   0.000000    0.000000    0.000000     0.000000   \n",
       "25%                   1.000000    0.000000    0.000000     0.000000   \n",
       "50%                   1.000000    0.000000    0.000000     0.000000   \n",
       "75%                   1.000000    0.000000    0.000000     0.000000   \n",
       "max                   1.000000    1.000000    1.000000     1.000000   \n",
       "\n",
       "       Income 20-40k  Income 40-60k  Income 60-80k  Income >80k  \\\n",
       "count     114.000000          114.0     114.000000   114.000000   \n",
       "mean        0.912281            0.0       0.008772     0.008772   \n",
       "std         0.284135            0.0       0.093659     0.093659   \n",
       "min         0.000000            0.0       0.000000     0.000000   \n",
       "25%         1.000000            0.0       0.000000     0.000000   \n",
       "50%         1.000000            0.0       0.000000     0.000000   \n",
       "75%         1.000000            0.0       0.000000     0.000000   \n",
       "max         1.000000            0.0       1.000000     1.000000   \n",
       "\n",
       "       Experience (<1yr)  Experience (1-2yr)  Experience (2-5yr)  \\\n",
       "count         114.000000          114.000000          114.000000   \n",
       "mean            0.052632            0.149123            0.096491   \n",
       "std             0.224283            0.357782            0.296567   \n",
       "min             0.000000            0.000000            0.000000   \n",
       "25%             0.000000            0.000000            0.000000   \n",
       "50%             0.000000            0.000000            0.000000   \n",
       "75%             0.000000            0.000000            0.000000   \n",
       "max             1.000000            1.000000            1.000000   \n",
       "\n",
       "       Experience (5-10yr)  Experience (10-20yr)  Experience (20-30yr)  \\\n",
       "count           114.000000            114.000000            114.000000   \n",
       "mean              0.263158              0.412281              0.017544   \n",
       "std               0.442292              0.494418              0.131866   \n",
       "min               0.000000              0.000000              0.000000   \n",
       "25%               0.000000              0.000000              0.000000   \n",
       "50%               0.000000              0.000000              0.000000   \n",
       "75%               1.000000              1.000000              0.000000   \n",
       "max               1.000000              1.000000              1.000000   \n",
       "\n",
       "       Experience (>30yr)  Helmet (Full-mask)  Cluster  \n",
       "count          114.000000          114.000000    114.0  \n",
       "mean             0.008772            0.780702      3.0  \n",
       "std              0.093659            0.415598      0.0  \n",
       "min              0.000000            0.000000      3.0  \n",
       "25%              0.000000            1.000000      3.0  \n",
       "50%              0.000000            1.000000      3.0  \n",
       "75%              0.000000            1.000000      3.0  \n",
       "max              1.000000            1.000000      3.0  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_4 = final_df.loc[final_df['Cluster']==3]\n",
    "cluster_4.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "38bc9b01",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Age (Yrs)</th>\n",
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       "      <th>count</th>\n",
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       "      <td>117.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>117.000000</td>\n",
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       "      <td>117.000000</td>\n",
       "      <td>117.0</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>27.931624</td>\n",
       "      <td>0.931624</td>\n",
       "      <td>0.017094</td>\n",
       "      <td>0.051282</td>\n",
       "      <td>0.888889</td>\n",
       "      <td>0.042735</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>0.299145</td>\n",
       "      <td>0.495726</td>\n",
       "      <td>0.068376</td>\n",
       "      <td>0.025641</td>\n",
       "      <td>0.034188</td>\n",
       "      <td>0.059829</td>\n",
       "      <td>0.282051</td>\n",
       "      <td>0.623932</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.880342</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.872029</td>\n",
       "      <td>0.253476</td>\n",
       "      <td>0.130179</td>\n",
       "      <td>0.221521</td>\n",
       "      <td>0.315621</td>\n",
       "      <td>0.203129</td>\n",
       "      <td>0.315621</td>\n",
       "      <td>0.459853</td>\n",
       "      <td>0.502132</td>\n",
       "      <td>0.253476</td>\n",
       "      <td>0.158742</td>\n",
       "      <td>0.182493</td>\n",
       "      <td>0.238190</td>\n",
       "      <td>0.451934</td>\n",
       "      <td>0.486481</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.325957</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>25.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>28.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</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>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>45.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Age (Yrs)  Gender (Male)  Education (<Class 10)  \\\n",
       "count  117.000000     117.000000             117.000000   \n",
       "mean    27.931624       0.931624               0.017094   \n",
       "std      4.872029       0.253476               0.130179   \n",
       "min     17.000000       0.000000               0.000000   \n",
       "25%     25.000000       1.000000               0.000000   \n",
       "50%     28.000000       1.000000               0.000000   \n",
       "75%     30.000000       1.000000               0.000000   \n",
       "max     45.000000       1.000000               1.000000   \n",
       "\n",
       "       Education (Class 10-12)    Graduate  Higher Edu  Income <20k  \\\n",
       "count               117.000000  117.000000  117.000000   117.000000   \n",
       "mean                  0.051282    0.888889    0.042735     0.111111   \n",
       "std                   0.221521    0.315621    0.203129     0.315621   \n",
       "min                   0.000000    0.000000    0.000000     0.000000   \n",
       "25%                   0.000000    1.000000    0.000000     0.000000   \n",
       "50%                   0.000000    1.000000    0.000000     0.000000   \n",
       "75%                   0.000000    1.000000    0.000000     0.000000   \n",
       "max                   1.000000    1.000000    1.000000     1.000000   \n",
       "\n",
       "       Income 20-40k  Income 40-60k  Income 60-80k  Income >80k  \\\n",
       "count     117.000000     117.000000     117.000000   117.000000   \n",
       "mean        0.299145       0.495726       0.068376     0.025641   \n",
       "std         0.459853       0.502132       0.253476     0.158742   \n",
       "min         0.000000       0.000000       0.000000     0.000000   \n",
       "25%         0.000000       0.000000       0.000000     0.000000   \n",
       "50%         0.000000       0.000000       0.000000     0.000000   \n",
       "75%         1.000000       1.000000       0.000000     0.000000   \n",
       "max         1.000000       1.000000       1.000000     1.000000   \n",
       "\n",
       "       Experience (<1yr)  Experience (1-2yr)  Experience (2-5yr)  \\\n",
       "count         117.000000          117.000000          117.000000   \n",
       "mean            0.034188            0.059829            0.282051   \n",
       "std             0.182493            0.238190            0.451934   \n",
       "min             0.000000            0.000000            0.000000   \n",
       "25%             0.000000            0.000000            0.000000   \n",
       "50%             0.000000            0.000000            0.000000   \n",
       "75%             0.000000            0.000000            1.000000   \n",
       "max             1.000000            1.000000            1.000000   \n",
       "\n",
       "       Experience (5-10yr)  Experience (10-20yr)  Experience (20-30yr)  \\\n",
       "count           117.000000                 117.0                 117.0   \n",
       "mean              0.623932                   0.0                   0.0   \n",
       "std               0.486481                   0.0                   0.0   \n",
       "min               0.000000                   0.0                   0.0   \n",
       "25%               0.000000                   0.0                   0.0   \n",
       "50%               1.000000                   0.0                   0.0   \n",
       "75%               1.000000                   0.0                   0.0   \n",
       "max               1.000000                   0.0                   0.0   \n",
       "\n",
       "       Experience (>30yr)  Helmet (Full-mask)  Cluster  \n",
       "count               117.0          117.000000    117.0  \n",
       "mean                  0.0            0.880342      4.0  \n",
       "std                   0.0            0.325957      0.0  \n",
       "min                   0.0            0.000000      4.0  \n",
       "25%                   0.0            1.000000      4.0  \n",
       "50%                   0.0            1.000000      4.0  \n",
       "75%                   0.0            1.000000      4.0  \n",
       "max                   0.0            1.000000      4.0  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_5 = final_df.loc[final_df['Cluster']==4]\n",
    "cluster_5.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "26e4b643",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age (Yrs)</th>\n",
       "      <th>Gender (Male)</th>\n",
       "      <th>Education (&lt;Class 10)</th>\n",
       "      <th>Education (Class 10-12)</th>\n",
       "      <th>Graduate</th>\n",
       "      <th>Higher Edu</th>\n",
       "      <th>Income &lt;20k</th>\n",
       "      <th>Income 20-40k</th>\n",
       "      <th>Income 40-60k</th>\n",
       "      <th>Income 60-80k</th>\n",
       "      <th>Income &gt;80k</th>\n",
       "      <th>Experience (&lt;1yr)</th>\n",
       "      <th>Experience (1-2yr)</th>\n",
       "      <th>Experience (2-5yr)</th>\n",
       "      <th>Experience (5-10yr)</th>\n",
       "      <th>Experience (10-20yr)</th>\n",
       "      <th>Experience (20-30yr)</th>\n",
       "      <th>Experience (&gt;30yr)</th>\n",
       "      <th>Helmet (Full-mask)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cluster</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>51.873239</td>\n",
       "      <td>0.943662</td>\n",
       "      <td>0.140845</td>\n",
       "      <td>0.183099</td>\n",
       "      <td>0.577465</td>\n",
       "      <td>0.098592</td>\n",
       "      <td>0.070423</td>\n",
       "      <td>0.239437</td>\n",
       "      <td>0.267606</td>\n",
       "      <td>0.380282</td>\n",
       "      <td>0.042254</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014085</td>\n",
       "      <td>0.028169</td>\n",
       "      <td>0.056338</td>\n",
       "      <td>0.169014</td>\n",
       "      <td>0.591549</td>\n",
       "      <td>0.140845</td>\n",
       "      <td>0.760563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>38.329268</td>\n",
       "      <td>0.951220</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.085366</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.036585</td>\n",
       "      <td>0.073171</td>\n",
       "      <td>0.073171</td>\n",
       "      <td>0.658537</td>\n",
       "      <td>0.170732</td>\n",
       "      <td>0.024390</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.048780</td>\n",
       "      <td>0.048780</td>\n",
       "      <td>0.024390</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.024390</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.878049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32.298969</td>\n",
       "      <td>0.958763</td>\n",
       "      <td>0.742268</td>\n",
       "      <td>0.195876</td>\n",
       "      <td>0.030928</td>\n",
       "      <td>0.030928</td>\n",
       "      <td>0.865979</td>\n",
       "      <td>0.092784</td>\n",
       "      <td>0.020619</td>\n",
       "      <td>0.020619</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.051546</td>\n",
       "      <td>0.103093</td>\n",
       "      <td>0.144330</td>\n",
       "      <td>0.494845</td>\n",
       "      <td>0.175258</td>\n",
       "      <td>0.030928</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.824742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35.350877</td>\n",
       "      <td>0.964912</td>\n",
       "      <td>0.061404</td>\n",
       "      <td>0.894737</td>\n",
       "      <td>0.017544</td>\n",
       "      <td>0.026316</td>\n",
       "      <td>0.070175</td>\n",
       "      <td>0.912281</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008772</td>\n",
       "      <td>0.008772</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>0.149123</td>\n",
       "      <td>0.096491</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.412281</td>\n",
       "      <td>0.017544</td>\n",
       "      <td>0.008772</td>\n",
       "      <td>0.780702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27.931624</td>\n",
       "      <td>0.931624</td>\n",
       "      <td>0.017094</td>\n",
       "      <td>0.051282</td>\n",
       "      <td>0.888889</td>\n",
       "      <td>0.042735</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>0.299145</td>\n",
       "      <td>0.495726</td>\n",
       "      <td>0.068376</td>\n",
       "      <td>0.025641</td>\n",
       "      <td>0.034188</td>\n",
       "      <td>0.059829</td>\n",
       "      <td>0.282051</td>\n",
       "      <td>0.623932</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.880342</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Age (Yrs)  Gender (Male)  Education (<Class 10)  \\\n",
       "Cluster                                                    \n",
       "0        51.873239       0.943662               0.140845   \n",
       "1        38.329268       0.951220               0.000000   \n",
       "2        32.298969       0.958763               0.742268   \n",
       "3        35.350877       0.964912               0.061404   \n",
       "4        27.931624       0.931624               0.017094   \n",
       "\n",
       "         Education (Class 10-12)  Graduate  Higher Edu  Income <20k  \\\n",
       "Cluster                                                               \n",
       "0                       0.183099  0.577465    0.098592     0.070423   \n",
       "1                       0.085366  0.878049    0.036585     0.073171   \n",
       "2                       0.195876  0.030928    0.030928     0.865979   \n",
       "3                       0.894737  0.017544    0.026316     0.070175   \n",
       "4                       0.051282  0.888889    0.042735     0.111111   \n",
       "\n",
       "         Income 20-40k  Income 40-60k  Income 60-80k  Income >80k  \\\n",
       "Cluster                                                             \n",
       "0             0.239437       0.267606       0.380282     0.042254   \n",
       "1             0.073171       0.658537       0.170732     0.024390   \n",
       "2             0.092784       0.020619       0.020619     0.000000   \n",
       "3             0.912281       0.000000       0.008772     0.008772   \n",
       "4             0.299145       0.495726       0.068376     0.025641   \n",
       "\n",
       "         Experience (<1yr)  Experience (1-2yr)  Experience (2-5yr)  \\\n",
       "Cluster                                                              \n",
       "0                 0.000000            0.014085            0.028169   \n",
       "1                 0.000000            0.048780            0.048780   \n",
       "2                 0.051546            0.103093            0.144330   \n",
       "3                 0.052632            0.149123            0.096491   \n",
       "4                 0.034188            0.059829            0.282051   \n",
       "\n",
       "         Experience (5-10yr)  Experience (10-20yr)  Experience (20-30yr)  \\\n",
       "Cluster                                                                    \n",
       "0                   0.056338              0.169014              0.591549   \n",
       "1                   0.024390              0.853659              0.024390   \n",
       "2                   0.494845              0.175258              0.030928   \n",
       "3                   0.263158              0.412281              0.017544   \n",
       "4                   0.623932              0.000000              0.000000   \n",
       "\n",
       "         Experience (>30yr)  Helmet (Full-mask)  \n",
       "Cluster                                          \n",
       "0                  0.140845            0.760563  \n",
       "1                  0.000000            0.878049  \n",
       "2                  0.000000            0.824742  \n",
       "3                  0.008772            0.780702  \n",
       "4                  0.000000            0.880342  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "overall_mean = final_df.groupby('Cluster').mean()\n",
    "\n",
    "overall_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "85444973",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exporting the datasets to excel:\n",
    "\n",
    "final_df.to_excel('clustered data KMedoids.xlsx')\n",
    "overall_mean.to_excel('mean_for_clusters_kmedoids.xlsx')\n",
    "\n",
    "cluster_1.to_excel('cluster_1_kmedoids.xlsx')\n",
    "cluster_2.to_excel('cluster_2_kmedoids.xlsx')\n",
    "cluster_3.to_excel('cluster_3_kmedoids.xlsx')\n",
    "cluster_4.to_excel('cluster_4_kmedoids.xlsx')\n",
    "cluster_5.to_excel('cluster_5_kmedoids.xlsx')"
   ]
  }
 ],
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