FA K Medoids cluster 3 & 4.ipynb

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   "source": [
    "# Factor Analysis on K-Medoids clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1f94de7c",
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      "text/plain": [
       "     Q 1  Q 2  Q 3  Q 4  Q 5  Q 6  Q 7  Q 8  Q 9  Q 10  ...  Q 28  Q 29  Q 30  \\\n",
       "0      6    5    6    3    6    7    7    1    6     6  ...     2     1     6   \n",
       "1      4    4    3    2    2    5    2    1    1     3  ...     1     4     3   \n",
       "2      6    7    6    5    3    4    1    1    4     1  ...     1     5     5   \n",
       "3      1    1    2    6    2    1    1    1    2     1  ...     2     2     1   \n",
       "4      4    7    4    6    6    4    4    3    3     3  ...     7     1     7   \n",
       "..   ...  ...  ...  ...  ...  ...  ...  ...  ...   ...  ...   ...   ...   ...   \n",
       "476    5    1    5    3    5    3    1    1    5     2  ...     1     5     2   \n",
       "477    6    7    5    5    6    5    1    1    5     1  ...     1     6     2   \n",
       "478    2    4    3    3    6    2    1    1    4     2  ...     1     5     2   \n",
       "479    5    7    5    5    7    3    2    1    5     1  ...     2     6     2   \n",
       "480    6    1    3    4    4    2    2    1    4     2  ...     1     4     2   \n",
       "\n",
       "     Q 31  Q 32  Q 33  Q 34  Q 35  Q 36  Cluster  \n",
       "0       2     2     6     7     2     4        2  \n",
       "1       4     3     4     3     3     3        1  \n",
       "2       1     6     6     1     6     6        4  \n",
       "3       1     1     2     1     2     2        2  \n",
       "4       1     3     1     3     1     3        3  \n",
       "..    ...   ...   ...   ...   ...   ...      ...  \n",
       "476     1     5     3     1     3     3        4  \n",
       "477     1     5     1     1     2     2        4  \n",
       "478     1     2     2     1     1     1        0  \n",
       "479     1     5     2     1     3     2        1  \n",
       "480     1     4     2     1     1     1        1  \n",
       "\n",
       "[481 rows x 37 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from factor_analyzer import FactorAnalyzer\n",
    "from factor_analyzer.factor_analyzer import calculate_bartlett_sphericity, calculate_kmo\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#First the unnecessary columns are removed:\n",
    "\n",
    "df = pd.read_excel('Asansol MRBQ Data.xlsx')\n",
    "df = df.drop(columns = ['TOT2'])\n",
    "\n",
    "df_2 = pd.read_excel('clustered data KMedoids.xlsx')\n",
    "\n",
    "clusters = list(df_2['Cluster'])\n",
    "\n",
    "df['Cluster'] = clusters\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a02d954b",
   "metadata": {},
   "source": [
    "## Factor Analysis on third cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "61215ced",
   "metadata": {},
   "outputs": [
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       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>419</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>97 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Q 1  Q 2  Q 3  Q 4  Q 5  Q 6  Q 7  Q 8  Q 9  Q 10  ...  Q 28  Q 29  Q 30  \\\n",
       "0      6    5    6    3    6    7    7    1    6     6  ...     2     1     6   \n",
       "3      1    1    2    6    2    1    1    1    2     1  ...     2     2     1   \n",
       "5      4    4    6    6    5    7    5    6    5     6  ...     7     6     6   \n",
       "7      1    2    1    1    2    6    3    1    2     1  ...     1     3     1   \n",
       "12     7    3    7    3    4    4    1    1    3     4  ...     1     1     1   \n",
       "..   ...  ...  ...  ...  ...  ...  ...  ...  ...   ...  ...   ...   ...   ...   \n",
       "412    4    5    6    6    5    6    4    2    2     2  ...     4     3     3   \n",
       "419    3    3    5    7    4    6    5    4    4     4  ...     4     5     5   \n",
       "420    4    4    6    6    4    6    5    5    5     5  ...     5     4     5   \n",
       "423    5    6    6    6    3    6    2    3    4     3  ...     3     4     4   \n",
       "424    2    2    5    6    5    6    5    2    3     3  ...     5     3     3   \n",
       "\n",
       "     Q 31  Q 32  Q 33  Q 34  Q 35  Q 36  Cluster  \n",
       "0       2     2     6     7     2     4        2  \n",
       "3       1     1     2     1     2     2        2  \n",
       "5       5     5     5     6     6     6        2  \n",
       "7       3     4     2     1     2     6        2  \n",
       "12      3     3     3     1     1     1        2  \n",
       "..    ...   ...   ...   ...   ...   ...      ...  \n",
       "412     3     4     3     3     1     1        2  \n",
       "419     5     5     4     5     5     6        2  \n",
       "420     4     5     4     5     6     6        2  \n",
       "423     2     3     3     1     1     1        2  \n",
       "424     3     3     4     1     1     1        2  \n",
       "\n",
       "[97 rows x 37 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Only the rows belionging to the 3rd cluster are filtered out.\n",
    "\n",
    "cluster_3 = df.loc[df['Cluster']==2]\n",
    "cluster_3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5232678e",
   "metadata": {},
   "outputs": [
    {
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       "      <td>5</td>\n",
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       "      <td>1</td>\n",
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       "</table>\n",
       "<p>97 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Q 1  Q 2  Q 3  Q 4  Q 5  Q 6  Q 7  Q 8  Q 9  Q 10  ...  Q 27  Q 28  Q 29  \\\n",
       "0      6    5    6    3    6    7    7    1    6     6  ...     6     2     1   \n",
       "3      1    1    2    6    2    1    1    1    2     1  ...     1     2     2   \n",
       "5      4    4    6    6    5    7    5    6    5     6  ...     5     7     6   \n",
       "7      1    2    1    1    2    6    3    1    2     1  ...     2     1     3   \n",
       "12     7    3    7    3    4    4    1    1    3     4  ...     3     1     1   \n",
       "..   ...  ...  ...  ...  ...  ...  ...  ...  ...   ...  ...   ...   ...   ...   \n",
       "412    4    5    6    6    5    6    4    2    2     2  ...     4     4     3   \n",
       "419    3    3    5    7    4    6    5    4    4     4  ...     5     4     5   \n",
       "420    4    4    6    6    4    6    5    5    5     5  ...     5     5     4   \n",
       "423    5    6    6    6    3    6    2    3    4     3  ...     3     3     4   \n",
       "424    2    2    5    6    5    6    5    2    3     3  ...     3     5     3   \n",
       "\n",
       "     Q 30  Q 31  Q 32  Q 33  Q 34  Q 35  Q 36  \n",
       "0       6     2     2     6     7     2     4  \n",
       "3       1     1     1     2     1     2     2  \n",
       "5       6     5     5     5     6     6     6  \n",
       "7       1     3     4     2     1     2     6  \n",
       "12      1     3     3     3     1     1     1  \n",
       "..    ...   ...   ...   ...   ...   ...   ...  \n",
       "412     3     3     4     3     3     1     1  \n",
       "419     5     5     5     4     5     5     6  \n",
       "420     5     4     5     4     5     6     6  \n",
       "423     4     2     3     3     1     1     1  \n",
       "424     3     3     3     4     1     1     1  \n",
       "\n",
       "[97 rows x 36 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_3 = cluster_3.drop(columns=['Cluster'])\n",
    "cluster_3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1ff86d47",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KMO per variable: [0.90348323 0.8354255  0.89755818 0.89949466 0.92557899 0.89835217\n",
      " 0.87142431 0.81656984 0.91131359 0.82453465 0.83515815 0.69050166\n",
      " 0.88923261 0.91579316 0.82786773 0.85597112 0.86197529 0.89381583\n",
      " 0.88961638 0.8106654  0.86734288 0.91518729 0.93963517 0.94832543\n",
      " 0.83723105 0.80430007 0.92804156 0.93404506 0.91874298 0.82538671\n",
      " 0.88943005 0.91942005 0.89291784 0.80238686 0.87058907 0.83173558]\n",
      "Overall KMO: 0.8763989652682782\n"
     ]
    }
   ],
   "source": [
    "# Next the KMO (Kiaser-Meyer-Olkin) test was used to determine whether the cluster is suitable for factor analysis\n",
    "# The closer the overall KMO is to 1, the better suited the dataset.\n",
    "\n",
    "kmo_all, kmo_model = calculate_kmo(cluster_3)\n",
    "\n",
    "print(\"KMO per variable:\", kmo_all)\n",
    "print(\"Overall KMO:\", kmo_model)\n",
    "\n",
    "# Since the cluster has a reasonable KMO value, going ahead with the Factor Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e7e366a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Q 1</th>\n",
       "      <th>Q 2</th>\n",
       "      <th>Q 3</th>\n",
       "      <th>Q 4</th>\n",
       "      <th>Q 5</th>\n",
       "      <th>Q 6</th>\n",
       "      <th>Q 7</th>\n",
       "      <th>Q 8</th>\n",
       "      <th>Q 9</th>\n",
       "      <th>Q 10</th>\n",
       "      <th>...</th>\n",
       "      <th>Q 27</th>\n",
       "      <th>Q 28</th>\n",
       "      <th>Q 29</th>\n",
       "      <th>Q 30</th>\n",
       "      <th>Q 31</th>\n",
       "      <th>Q 32</th>\n",
       "      <th>Q 33</th>\n",
       "      <th>Q 34</th>\n",
       "      <th>Q 35</th>\n",
       "      <th>Q 36</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Q 1</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.726961</td>\n",
       "      <td>0.728817</td>\n",
       "      <td>0.573756</td>\n",
       "      <td>0.613404</td>\n",
       "      <td>0.641348</td>\n",
       "      <td>0.343419</td>\n",
       "      <td>0.256477</td>\n",
       "      <td>0.380395</td>\n",
       "      <td>0.394561</td>\n",
       "      <td>...</td>\n",
       "      <td>0.568128</td>\n",
       "      <td>0.330949</td>\n",
       "      <td>0.478370</td>\n",
       "      <td>0.415517</td>\n",
       "      <td>0.436911</td>\n",
       "      <td>0.575061</td>\n",
       "      <td>0.459879</td>\n",
       "      <td>0.374333</td>\n",
       "      <td>0.236396</td>\n",
       "      <td>0.232407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 2</th>\n",
       "      <td>0.726961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.613709</td>\n",
       "      <td>0.533695</td>\n",
       "      <td>0.470221</td>\n",
       "      <td>0.592311</td>\n",
       "      <td>0.294810</td>\n",
       "      <td>0.234318</td>\n",
       "      <td>0.347751</td>\n",
       "      <td>0.324106</td>\n",
       "      <td>...</td>\n",
       "      <td>0.453776</td>\n",
       "      <td>0.312127</td>\n",
       "      <td>0.357938</td>\n",
       "      <td>0.431474</td>\n",
       "      <td>0.380224</td>\n",
       "      <td>0.537370</td>\n",
       "      <td>0.423989</td>\n",
       "      <td>0.259691</td>\n",
       "      <td>0.246147</td>\n",
       "      <td>0.264367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 3</th>\n",
       "      <td>0.728817</td>\n",
       "      <td>0.613709</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.600716</td>\n",
       "      <td>0.588781</td>\n",
       "      <td>0.673235</td>\n",
       "      <td>0.540645</td>\n",
       "      <td>0.288426</td>\n",
       "      <td>0.425865</td>\n",
       "      <td>0.450771</td>\n",
       "      <td>...</td>\n",
       "      <td>0.630271</td>\n",
       "      <td>0.403319</td>\n",
       "      <td>0.489362</td>\n",
       "      <td>0.454901</td>\n",
       "      <td>0.573294</td>\n",
       "      <td>0.480809</td>\n",
       "      <td>0.496521</td>\n",
       "      <td>0.423025</td>\n",
       "      <td>0.345510</td>\n",
       "      <td>0.295951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 4</th>\n",
       "      <td>0.573756</td>\n",
       "      <td>0.533695</td>\n",
       "      <td>0.600716</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.632202</td>\n",
       "      <td>0.641325</td>\n",
       "      <td>0.306769</td>\n",
       "      <td>0.389939</td>\n",
       "      <td>0.393116</td>\n",
       "      <td>0.334390</td>\n",
       "      <td>...</td>\n",
       "      <td>0.456369</td>\n",
       "      <td>0.500917</td>\n",
       "      <td>0.528306</td>\n",
       "      <td>0.470354</td>\n",
       "      <td>0.499578</td>\n",
       "      <td>0.572078</td>\n",
       "      <td>0.465465</td>\n",
       "      <td>0.314221</td>\n",
       "      <td>0.406090</td>\n",
       "      <td>0.384220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 5</th>\n",
       "      <td>0.613404</td>\n",
       "      <td>0.470221</td>\n",
       "      <td>0.588781</td>\n",
       "      <td>0.632202</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.687783</td>\n",
       "      <td>0.427058</td>\n",
       "      <td>0.406784</td>\n",
       "      <td>0.554752</td>\n",
       "      <td>0.415815</td>\n",
       "      <td>...</td>\n",
       "      <td>0.552827</td>\n",
       "      <td>0.563569</td>\n",
       "      <td>0.558792</td>\n",
       "      <td>0.561794</td>\n",
       "      <td>0.600689</td>\n",
       "      <td>0.626625</td>\n",
       "      <td>0.647329</td>\n",
       "      <td>0.515176</td>\n",
       "      <td>0.444949</td>\n",
       "      <td>0.492237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 6</th>\n",
       "      <td>0.641348</td>\n",
       "      <td>0.592311</td>\n",
       "      <td>0.673235</td>\n",
       "      <td>0.641325</td>\n",
       "      <td>0.687783</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.448279</td>\n",
       "      <td>0.374035</td>\n",
       "      <td>0.465835</td>\n",
       "      <td>0.424787</td>\n",
       "      <td>...</td>\n",
       "      <td>0.580182</td>\n",
       "      <td>0.554844</td>\n",
       "      <td>0.558169</td>\n",
       "      <td>0.637624</td>\n",
       "      <td>0.618549</td>\n",
       "      <td>0.621910</td>\n",
       "      <td>0.561770</td>\n",
       "      <td>0.452783</td>\n",
       "      <td>0.367093</td>\n",
       "      <td>0.457570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 7</th>\n",
       "      <td>0.343419</td>\n",
       "      <td>0.294810</td>\n",
       "      <td>0.540645</td>\n",
       "      <td>0.306769</td>\n",
       "      <td>0.427058</td>\n",
       "      <td>0.448279</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.201529</td>\n",
       "      <td>0.403301</td>\n",
       "      <td>0.620033</td>\n",
       "      <td>...</td>\n",
       "      <td>0.461985</td>\n",
       "      <td>0.456775</td>\n",
       "      <td>0.283229</td>\n",
       "      <td>0.435956</td>\n",
       "      <td>0.506129</td>\n",
       "      <td>0.439575</td>\n",
       "      <td>0.356167</td>\n",
       "      <td>0.564629</td>\n",
       "      <td>0.346697</td>\n",
       "      <td>0.331191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 8</th>\n",
       "      <td>0.256477</td>\n",
       "      <td>0.234318</td>\n",
       "      <td>0.288426</td>\n",
       "      <td>0.389939</td>\n",
       "      <td>0.406784</td>\n",
       "      <td>0.374035</td>\n",
       "      <td>0.201529</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.215740</td>\n",
       "      <td>0.357383</td>\n",
       "      <td>...</td>\n",
       "      <td>0.206002</td>\n",
       "      <td>0.647682</td>\n",
       "      <td>0.273247</td>\n",
       "      <td>0.418308</td>\n",
       "      <td>0.457026</td>\n",
       "      <td>0.363239</td>\n",
       "      <td>0.286221</td>\n",
       "      <td>0.558056</td>\n",
       "      <td>0.471130</td>\n",
       "      <td>0.378503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 9</th>\n",
       "      <td>0.380395</td>\n",
       "      <td>0.347751</td>\n",
       "      <td>0.425865</td>\n",
       "      <td>0.393116</td>\n",
       "      <td>0.554752</td>\n",
       "      <td>0.465835</td>\n",
       "      <td>0.403301</td>\n",
       "      <td>0.215740</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.485859</td>\n",
       "      <td>...</td>\n",
       "      <td>0.589154</td>\n",
       "      <td>0.366277</td>\n",
       "      <td>0.508102</td>\n",
       "      <td>0.507467</td>\n",
       "      <td>0.416263</td>\n",
       "      <td>0.389485</td>\n",
       "      <td>0.506160</td>\n",
       "      <td>0.385551</td>\n",
       "      <td>0.504548</td>\n",
       "      <td>0.435495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 10</th>\n",
       "      <td>0.394561</td>\n",
       "      <td>0.324106</td>\n",
       "      <td>0.450771</td>\n",
       "      <td>0.334390</td>\n",
       "      <td>0.415815</td>\n",
       "      <td>0.424787</td>\n",
       "      <td>0.620033</td>\n",
       "      <td>0.357383</td>\n",
       "      <td>0.485859</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.565703</td>\n",
       "      <td>0.501559</td>\n",
       "      <td>0.276875</td>\n",
       "      <td>0.541169</td>\n",
       "      <td>0.473641</td>\n",
       "      <td>0.351747</td>\n",
       "      <td>0.452751</td>\n",
       "      <td>0.510935</td>\n",
       "      <td>0.447951</td>\n",
       "      <td>0.292265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 11</th>\n",
       "      <td>0.266138</td>\n",
       "      <td>0.254649</td>\n",
       "      <td>0.423112</td>\n",
       "      <td>0.173569</td>\n",
       "      <td>0.380875</td>\n",
       "      <td>0.283057</td>\n",
       "      <td>0.505926</td>\n",
       "      <td>0.206594</td>\n",
       "      <td>0.473468</td>\n",
       "      <td>0.434889</td>\n",
       "      <td>...</td>\n",
       "      <td>0.337970</td>\n",
       "      <td>0.295313</td>\n",
       "      <td>0.282033</td>\n",
       "      <td>0.314199</td>\n",
       "      <td>0.343369</td>\n",
       "      <td>0.201555</td>\n",
       "      <td>0.284499</td>\n",
       "      <td>0.350261</td>\n",
       "      <td>0.428425</td>\n",
       "      <td>0.389986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 12</th>\n",
       "      <td>0.353925</td>\n",
       "      <td>0.119253</td>\n",
       "      <td>0.334730</td>\n",
       "      <td>0.205515</td>\n",
       "      <td>0.300359</td>\n",
       "      <td>0.250863</td>\n",
       "      <td>0.099262</td>\n",
       "      <td>-0.053633</td>\n",
       "      <td>0.392674</td>\n",
       "      <td>0.277876</td>\n",
       "      <td>...</td>\n",
       "      <td>0.470955</td>\n",
       "      <td>-0.053296</td>\n",
       "      <td>0.455881</td>\n",
       "      <td>-0.039882</td>\n",
       "      <td>0.136519</td>\n",
       "      <td>0.170035</td>\n",
       "      <td>0.419671</td>\n",
       "      <td>-0.007443</td>\n",
       "      <td>0.189604</td>\n",
       "      <td>0.168527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 13</th>\n",
       "      <td>0.573291</td>\n",
       "      <td>0.429523</td>\n",
       "      <td>0.569264</td>\n",
       "      <td>0.487825</td>\n",
       "      <td>0.529824</td>\n",
       "      <td>0.570674</td>\n",
       "      <td>0.414489</td>\n",
       "      <td>0.322349</td>\n",
       "      <td>0.397430</td>\n",
       "      <td>0.381110</td>\n",
       "      <td>...</td>\n",
       "      <td>0.447106</td>\n",
       "      <td>0.413930</td>\n",
       "      <td>0.527715</td>\n",
       "      <td>0.332645</td>\n",
       "      <td>0.377020</td>\n",
       "      <td>0.504032</td>\n",
       "      <td>0.421159</td>\n",
       "      <td>0.410121</td>\n",
       "      <td>0.279154</td>\n",
       "      <td>0.282502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 14</th>\n",
       "      <td>0.528386</td>\n",
       "      <td>0.475268</td>\n",
       "      <td>0.461271</td>\n",
       "      <td>0.363528</td>\n",
       "      <td>0.482935</td>\n",
       "      <td>0.459601</td>\n",
       "      <td>0.236958</td>\n",
       "      <td>0.282978</td>\n",
       "      <td>0.317617</td>\n",
       "      <td>0.286931</td>\n",
       "      <td>...</td>\n",
       "      <td>0.297154</td>\n",
       "      <td>0.315696</td>\n",
       "      <td>0.348223</td>\n",
       "      <td>0.366220</td>\n",
       "      <td>0.292851</td>\n",
       "      <td>0.447472</td>\n",
       "      <td>0.255085</td>\n",
       "      <td>0.240039</td>\n",
       "      <td>0.277103</td>\n",
       "      <td>0.268900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 15</th>\n",
       "      <td>0.544752</td>\n",
       "      <td>0.437478</td>\n",
       "      <td>0.518982</td>\n",
       "      <td>0.549309</td>\n",
       "      <td>0.616461</td>\n",
       "      <td>0.523940</td>\n",
       "      <td>0.384113</td>\n",
       "      <td>0.320888</td>\n",
       "      <td>0.612997</td>\n",
       "      <td>0.419955</td>\n",
       "      <td>...</td>\n",
       "      <td>0.526622</td>\n",
       "      <td>0.436655</td>\n",
       "      <td>0.608581</td>\n",
       "      <td>0.346394</td>\n",
       "      <td>0.481616</td>\n",
       "      <td>0.461792</td>\n",
       "      <td>0.510623</td>\n",
       "      <td>0.353276</td>\n",
       "      <td>0.397723</td>\n",
       "      <td>0.331954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 16</th>\n",
       "      <td>0.347759</td>\n",
       "      <td>0.369557</td>\n",
       "      <td>0.358185</td>\n",
       "      <td>0.399357</td>\n",
       "      <td>0.519742</td>\n",
       "      <td>0.556205</td>\n",
       "      <td>0.555988</td>\n",
       "      <td>0.375512</td>\n",
       "      <td>0.292023</td>\n",
       "      <td>0.474295</td>\n",
       "      <td>...</td>\n",
       "      <td>0.335012</td>\n",
       "      <td>0.566162</td>\n",
       "      <td>0.262358</td>\n",
       "      <td>0.551207</td>\n",
       "      <td>0.476219</td>\n",
       "      <td>0.481774</td>\n",
       "      <td>0.457022</td>\n",
       "      <td>0.569842</td>\n",
       "      <td>0.355869</td>\n",
       "      <td>0.306561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 17</th>\n",
       "      <td>0.549374</td>\n",
       "      <td>0.383863</td>\n",
       "      <td>0.600387</td>\n",
       "      <td>0.392496</td>\n",
       "      <td>0.464511</td>\n",
       "      <td>0.602325</td>\n",
       "      <td>0.293306</td>\n",
       "      <td>0.159822</td>\n",
       "      <td>0.393651</td>\n",
       "      <td>0.398286</td>\n",
       "      <td>...</td>\n",
       "      <td>0.609779</td>\n",
       "      <td>0.270473</td>\n",
       "      <td>0.520210</td>\n",
       "      <td>0.327685</td>\n",
       "      <td>0.463257</td>\n",
       "      <td>0.413713</td>\n",
       "      <td>0.510931</td>\n",
       "      <td>0.253743</td>\n",
       "      <td>0.198840</td>\n",
       "      <td>0.175782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 18</th>\n",
       "      <td>0.500073</td>\n",
       "      <td>0.464309</td>\n",
       "      <td>0.588270</td>\n",
       "      <td>0.434090</td>\n",
       "      <td>0.523581</td>\n",
       "      <td>0.515649</td>\n",
       "      <td>0.428621</td>\n",
       "      <td>0.443523</td>\n",
       "      <td>0.387692</td>\n",
       "      <td>0.399109</td>\n",
       "      <td>...</td>\n",
       "      <td>0.392061</td>\n",
       "      <td>0.590575</td>\n",
       "      <td>0.397637</td>\n",
       "      <td>0.531213</td>\n",
       "      <td>0.664112</td>\n",
       "      <td>0.429255</td>\n",
       "      <td>0.395946</td>\n",
       "      <td>0.414522</td>\n",
       "      <td>0.354854</td>\n",
       "      <td>0.268212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 19</th>\n",
       "      <td>0.501333</td>\n",
       "      <td>0.520103</td>\n",
       "      <td>0.482076</td>\n",
       "      <td>0.465888</td>\n",
       "      <td>0.588758</td>\n",
       "      <td>0.526954</td>\n",
       "      <td>0.485400</td>\n",
       "      <td>0.184270</td>\n",
       "      <td>0.458182</td>\n",
       "      <td>0.413526</td>\n",
       "      <td>...</td>\n",
       "      <td>0.548950</td>\n",
       "      <td>0.356815</td>\n",
       "      <td>0.455646</td>\n",
       "      <td>0.541923</td>\n",
       "      <td>0.366159</td>\n",
       "      <td>0.539288</td>\n",
       "      <td>0.479419</td>\n",
       "      <td>0.408309</td>\n",
       "      <td>0.422074</td>\n",
       "      <td>0.338758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 20</th>\n",
       "      <td>0.389335</td>\n",
       "      <td>0.411969</td>\n",
       "      <td>0.315982</td>\n",
       "      <td>0.314142</td>\n",
       "      <td>0.379022</td>\n",
       "      <td>0.343555</td>\n",
       "      <td>0.113743</td>\n",
       "      <td>0.269512</td>\n",
       "      <td>0.364936</td>\n",
       "      <td>0.056835</td>\n",
       "      <td>...</td>\n",
       "      <td>0.381269</td>\n",
       "      <td>0.335803</td>\n",
       "      <td>0.428076</td>\n",
       "      <td>0.521237</td>\n",
       "      <td>0.231371</td>\n",
       "      <td>0.509778</td>\n",
       "      <td>0.347203</td>\n",
       "      <td>0.320082</td>\n",
       "      <td>0.351322</td>\n",
       "      <td>0.331727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 21</th>\n",
       "      <td>0.229338</td>\n",
       "      <td>0.175462</td>\n",
       "      <td>0.300567</td>\n",
       "      <td>0.451479</td>\n",
       "      <td>0.440647</td>\n",
       "      <td>0.402585</td>\n",
       "      <td>0.332654</td>\n",
       "      <td>0.443406</td>\n",
       "      <td>0.349824</td>\n",
       "      <td>0.396366</td>\n",
       "      <td>...</td>\n",
       "      <td>0.450152</td>\n",
       "      <td>0.621590</td>\n",
       "      <td>0.365393</td>\n",
       "      <td>0.423936</td>\n",
       "      <td>0.658380</td>\n",
       "      <td>0.422312</td>\n",
       "      <td>0.521976</td>\n",
       "      <td>0.402908</td>\n",
       "      <td>0.504359</td>\n",
       "      <td>0.384298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 22</th>\n",
       "      <td>0.517287</td>\n",
       "      <td>0.314913</td>\n",
       "      <td>0.446425</td>\n",
       "      <td>0.419936</td>\n",
       "      <td>0.626200</td>\n",
       "      <td>0.481659</td>\n",
       "      <td>0.293567</td>\n",
       "      <td>0.038874</td>\n",
       "      <td>0.488941</td>\n",
       "      <td>0.368103</td>\n",
       "      <td>...</td>\n",
       "      <td>0.630940</td>\n",
       "      <td>0.281257</td>\n",
       "      <td>0.542798</td>\n",
       "      <td>0.354276</td>\n",
       "      <td>0.390586</td>\n",
       "      <td>0.440882</td>\n",
       "      <td>0.700141</td>\n",
       "      <td>0.291576</td>\n",
       "      <td>0.272703</td>\n",
       "      <td>0.248076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 23</th>\n",
       "      <td>0.390338</td>\n",
       "      <td>0.341695</td>\n",
       "      <td>0.471927</td>\n",
       "      <td>0.456645</td>\n",
       "      <td>0.503271</td>\n",
       "      <td>0.534676</td>\n",
       "      <td>0.373160</td>\n",
       "      <td>0.539484</td>\n",
       "      <td>0.422420</td>\n",
       "      <td>0.379185</td>\n",
       "      <td>...</td>\n",
       "      <td>0.505137</td>\n",
       "      <td>0.593881</td>\n",
       "      <td>0.415267</td>\n",
       "      <td>0.571857</td>\n",
       "      <td>0.536599</td>\n",
       "      <td>0.520747</td>\n",
       "      <td>0.445519</td>\n",
       "      <td>0.589190</td>\n",
       "      <td>0.547799</td>\n",
       "      <td>0.514354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 24</th>\n",
       "      <td>0.377376</td>\n",
       "      <td>0.363202</td>\n",
       "      <td>0.353488</td>\n",
       "      <td>0.410552</td>\n",
       "      <td>0.426420</td>\n",
       "      <td>0.424642</td>\n",
       "      <td>0.340939</td>\n",
       "      <td>0.358624</td>\n",
       "      <td>0.402817</td>\n",
       "      <td>0.270030</td>\n",
       "      <td>...</td>\n",
       "      <td>0.381887</td>\n",
       "      <td>0.393994</td>\n",
       "      <td>0.379065</td>\n",
       "      <td>0.320569</td>\n",
       "      <td>0.287055</td>\n",
       "      <td>0.415992</td>\n",
       "      <td>0.333442</td>\n",
       "      <td>0.403466</td>\n",
       "      <td>0.440413</td>\n",
       "      <td>0.447252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 25</th>\n",
       "      <td>0.226840</td>\n",
       "      <td>0.198122</td>\n",
       "      <td>0.220640</td>\n",
       "      <td>0.347455</td>\n",
       "      <td>0.452337</td>\n",
       "      <td>0.297515</td>\n",
       "      <td>0.193593</td>\n",
       "      <td>0.316162</td>\n",
       "      <td>0.384972</td>\n",
       "      <td>0.244523</td>\n",
       "      <td>...</td>\n",
       "      <td>0.254740</td>\n",
       "      <td>0.316917</td>\n",
       "      <td>0.411153</td>\n",
       "      <td>0.176558</td>\n",
       "      <td>0.226988</td>\n",
       "      <td>0.336210</td>\n",
       "      <td>0.410335</td>\n",
       "      <td>0.294882</td>\n",
       "      <td>0.411094</td>\n",
       "      <td>0.418154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 26</th>\n",
       "      <td>0.236295</td>\n",
       "      <td>0.236936</td>\n",
       "      <td>0.263683</td>\n",
       "      <td>0.397495</td>\n",
       "      <td>0.413328</td>\n",
       "      <td>0.315125</td>\n",
       "      <td>0.253359</td>\n",
       "      <td>0.348899</td>\n",
       "      <td>0.488665</td>\n",
       "      <td>0.345829</td>\n",
       "      <td>...</td>\n",
       "      <td>0.291836</td>\n",
       "      <td>0.438820</td>\n",
       "      <td>0.438891</td>\n",
       "      <td>0.278487</td>\n",
       "      <td>0.367285</td>\n",
       "      <td>0.377227</td>\n",
       "      <td>0.351901</td>\n",
       "      <td>0.320376</td>\n",
       "      <td>0.541897</td>\n",
       "      <td>0.484143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 27</th>\n",
       "      <td>0.568128</td>\n",
       "      <td>0.453776</td>\n",
       "      <td>0.630271</td>\n",
       "      <td>0.456369</td>\n",
       "      <td>0.552827</td>\n",
       "      <td>0.580182</td>\n",
       "      <td>0.461985</td>\n",
       "      <td>0.206002</td>\n",
       "      <td>0.589154</td>\n",
       "      <td>0.565703</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.375795</td>\n",
       "      <td>0.549055</td>\n",
       "      <td>0.524526</td>\n",
       "      <td>0.528818</td>\n",
       "      <td>0.490522</td>\n",
       "      <td>0.706563</td>\n",
       "      <td>0.526922</td>\n",
       "      <td>0.498590</td>\n",
       "      <td>0.466582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 28</th>\n",
       "      <td>0.330949</td>\n",
       "      <td>0.312127</td>\n",
       "      <td>0.403319</td>\n",
       "      <td>0.500917</td>\n",
       "      <td>0.563569</td>\n",
       "      <td>0.554844</td>\n",
       "      <td>0.456775</td>\n",
       "      <td>0.647682</td>\n",
       "      <td>0.366277</td>\n",
       "      <td>0.501559</td>\n",
       "      <td>...</td>\n",
       "      <td>0.375795</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.353679</td>\n",
       "      <td>0.689739</td>\n",
       "      <td>0.678342</td>\n",
       "      <td>0.520982</td>\n",
       "      <td>0.465957</td>\n",
       "      <td>0.662679</td>\n",
       "      <td>0.578142</td>\n",
       "      <td>0.473011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 29</th>\n",
       "      <td>0.478370</td>\n",
       "      <td>0.357938</td>\n",
       "      <td>0.489362</td>\n",
       "      <td>0.528306</td>\n",
       "      <td>0.558792</td>\n",
       "      <td>0.558169</td>\n",
       "      <td>0.283229</td>\n",
       "      <td>0.273247</td>\n",
       "      <td>0.508102</td>\n",
       "      <td>0.276875</td>\n",
       "      <td>...</td>\n",
       "      <td>0.549055</td>\n",
       "      <td>0.353679</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.365006</td>\n",
       "      <td>0.472500</td>\n",
       "      <td>0.582133</td>\n",
       "      <td>0.492604</td>\n",
       "      <td>0.267000</td>\n",
       "      <td>0.460058</td>\n",
       "      <td>0.365461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 30</th>\n",
       "      <td>0.415517</td>\n",
       "      <td>0.431474</td>\n",
       "      <td>0.454901</td>\n",
       "      <td>0.470354</td>\n",
       "      <td>0.561794</td>\n",
       "      <td>0.637624</td>\n",
       "      <td>0.435956</td>\n",
       "      <td>0.418308</td>\n",
       "      <td>0.507467</td>\n",
       "      <td>0.541169</td>\n",
       "      <td>...</td>\n",
       "      <td>0.524526</td>\n",
       "      <td>0.689739</td>\n",
       "      <td>0.365006</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.521864</td>\n",
       "      <td>0.468015</td>\n",
       "      <td>0.571134</td>\n",
       "      <td>0.670640</td>\n",
       "      <td>0.488761</td>\n",
       "      <td>0.451520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 31</th>\n",
       "      <td>0.436911</td>\n",
       "      <td>0.380224</td>\n",
       "      <td>0.573294</td>\n",
       "      <td>0.499578</td>\n",
       "      <td>0.600689</td>\n",
       "      <td>0.618549</td>\n",
       "      <td>0.506129</td>\n",
       "      <td>0.457026</td>\n",
       "      <td>0.416263</td>\n",
       "      <td>0.473641</td>\n",
       "      <td>...</td>\n",
       "      <td>0.528818</td>\n",
       "      <td>0.678342</td>\n",
       "      <td>0.472500</td>\n",
       "      <td>0.521864</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.578610</td>\n",
       "      <td>0.504627</td>\n",
       "      <td>0.514833</td>\n",
       "      <td>0.531840</td>\n",
       "      <td>0.447846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 32</th>\n",
       "      <td>0.575061</td>\n",
       "      <td>0.537370</td>\n",
       "      <td>0.480809</td>\n",
       "      <td>0.572078</td>\n",
       "      <td>0.626625</td>\n",
       "      <td>0.621910</td>\n",
       "      <td>0.439575</td>\n",
       "      <td>0.363239</td>\n",
       "      <td>0.389485</td>\n",
       "      <td>0.351747</td>\n",
       "      <td>...</td>\n",
       "      <td>0.490522</td>\n",
       "      <td>0.520982</td>\n",
       "      <td>0.582133</td>\n",
       "      <td>0.468015</td>\n",
       "      <td>0.578610</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.429675</td>\n",
       "      <td>0.460815</td>\n",
       "      <td>0.476943</td>\n",
       "      <td>0.512796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 33</th>\n",
       "      <td>0.459879</td>\n",
       "      <td>0.423989</td>\n",
       "      <td>0.496521</td>\n",
       "      <td>0.465465</td>\n",
       "      <td>0.647329</td>\n",
       "      <td>0.561770</td>\n",
       "      <td>0.356167</td>\n",
       "      <td>0.286221</td>\n",
       "      <td>0.506160</td>\n",
       "      <td>0.452751</td>\n",
       "      <td>...</td>\n",
       "      <td>0.706563</td>\n",
       "      <td>0.465957</td>\n",
       "      <td>0.492604</td>\n",
       "      <td>0.571134</td>\n",
       "      <td>0.504627</td>\n",
       "      <td>0.429675</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.565133</td>\n",
       "      <td>0.513610</td>\n",
       "      <td>0.438922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 34</th>\n",
       "      <td>0.374333</td>\n",
       "      <td>0.259691</td>\n",
       "      <td>0.423025</td>\n",
       "      <td>0.314221</td>\n",
       "      <td>0.515176</td>\n",
       "      <td>0.452783</td>\n",
       "      <td>0.564629</td>\n",
       "      <td>0.558056</td>\n",
       "      <td>0.385551</td>\n",
       "      <td>0.510935</td>\n",
       "      <td>...</td>\n",
       "      <td>0.526922</td>\n",
       "      <td>0.662679</td>\n",
       "      <td>0.267000</td>\n",
       "      <td>0.670640</td>\n",
       "      <td>0.514833</td>\n",
       "      <td>0.460815</td>\n",
       "      <td>0.565133</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.580683</td>\n",
       "      <td>0.600214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 35</th>\n",
       "      <td>0.236396</td>\n",
       "      <td>0.246147</td>\n",
       "      <td>0.345510</td>\n",
       "      <td>0.406090</td>\n",
       "      <td>0.444949</td>\n",
       "      <td>0.367093</td>\n",
       "      <td>0.346697</td>\n",
       "      <td>0.471130</td>\n",
       "      <td>0.504548</td>\n",
       "      <td>0.447951</td>\n",
       "      <td>...</td>\n",
       "      <td>0.498590</td>\n",
       "      <td>0.578142</td>\n",
       "      <td>0.460058</td>\n",
       "      <td>0.488761</td>\n",
       "      <td>0.531840</td>\n",
       "      <td>0.476943</td>\n",
       "      <td>0.513610</td>\n",
       "      <td>0.580683</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.754890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 36</th>\n",
       "      <td>0.232407</td>\n",
       "      <td>0.264367</td>\n",
       "      <td>0.295951</td>\n",
       "      <td>0.384220</td>\n",
       "      <td>0.492237</td>\n",
       "      <td>0.457570</td>\n",
       "      <td>0.331191</td>\n",
       "      <td>0.378503</td>\n",
       "      <td>0.435495</td>\n",
       "      <td>0.292265</td>\n",
       "      <td>...</td>\n",
       "      <td>0.466582</td>\n",
       "      <td>0.473011</td>\n",
       "      <td>0.365461</td>\n",
       "      <td>0.451520</td>\n",
       "      <td>0.447846</td>\n",
       "      <td>0.512796</td>\n",
       "      <td>0.438922</td>\n",
       "      <td>0.600214</td>\n",
       "      <td>0.754890</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>36 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Q 1       Q 2       Q 3       Q 4       Q 5       Q 6       Q 7  \\\n",
       "Q 1   1.000000  0.726961  0.728817  0.573756  0.613404  0.641348  0.343419   \n",
       "Q 2   0.726961  1.000000  0.613709  0.533695  0.470221  0.592311  0.294810   \n",
       "Q 3   0.728817  0.613709  1.000000  0.600716  0.588781  0.673235  0.540645   \n",
       "Q 4   0.573756  0.533695  0.600716  1.000000  0.632202  0.641325  0.306769   \n",
       "Q 5   0.613404  0.470221  0.588781  0.632202  1.000000  0.687783  0.427058   \n",
       "Q 6   0.641348  0.592311  0.673235  0.641325  0.687783  1.000000  0.448279   \n",
       "Q 7   0.343419  0.294810  0.540645  0.306769  0.427058  0.448279  1.000000   \n",
       "Q 8   0.256477  0.234318  0.288426  0.389939  0.406784  0.374035  0.201529   \n",
       "Q 9   0.380395  0.347751  0.425865  0.393116  0.554752  0.465835  0.403301   \n",
       "Q 10  0.394561  0.324106  0.450771  0.334390  0.415815  0.424787  0.620033   \n",
       "Q 11  0.266138  0.254649  0.423112  0.173569  0.380875  0.283057  0.505926   \n",
       "Q 12  0.353925  0.119253  0.334730  0.205515  0.300359  0.250863  0.099262   \n",
       "Q 13  0.573291  0.429523  0.569264  0.487825  0.529824  0.570674  0.414489   \n",
       "Q 14  0.528386  0.475268  0.461271  0.363528  0.482935  0.459601  0.236958   \n",
       "Q 15  0.544752  0.437478  0.518982  0.549309  0.616461  0.523940  0.384113   \n",
       "Q 16  0.347759  0.369557  0.358185  0.399357  0.519742  0.556205  0.555988   \n",
       "Q 17  0.549374  0.383863  0.600387  0.392496  0.464511  0.602325  0.293306   \n",
       "Q 18  0.500073  0.464309  0.588270  0.434090  0.523581  0.515649  0.428621   \n",
       "Q 19  0.501333  0.520103  0.482076  0.465888  0.588758  0.526954  0.485400   \n",
       "Q 20  0.389335  0.411969  0.315982  0.314142  0.379022  0.343555  0.113743   \n",
       "Q 21  0.229338  0.175462  0.300567  0.451479  0.440647  0.402585  0.332654   \n",
       "Q 22  0.517287  0.314913  0.446425  0.419936  0.626200  0.481659  0.293567   \n",
       "Q 23  0.390338  0.341695  0.471927  0.456645  0.503271  0.534676  0.373160   \n",
       "Q 24  0.377376  0.363202  0.353488  0.410552  0.426420  0.424642  0.340939   \n",
       "Q 25  0.226840  0.198122  0.220640  0.347455  0.452337  0.297515  0.193593   \n",
       "Q 26  0.236295  0.236936  0.263683  0.397495  0.413328  0.315125  0.253359   \n",
       "Q 27  0.568128  0.453776  0.630271  0.456369  0.552827  0.580182  0.461985   \n",
       "Q 28  0.330949  0.312127  0.403319  0.500917  0.563569  0.554844  0.456775   \n",
       "Q 29  0.478370  0.357938  0.489362  0.528306  0.558792  0.558169  0.283229   \n",
       "Q 30  0.415517  0.431474  0.454901  0.470354  0.561794  0.637624  0.435956   \n",
       "Q 31  0.436911  0.380224  0.573294  0.499578  0.600689  0.618549  0.506129   \n",
       "Q 32  0.575061  0.537370  0.480809  0.572078  0.626625  0.621910  0.439575   \n",
       "Q 33  0.459879  0.423989  0.496521  0.465465  0.647329  0.561770  0.356167   \n",
       "Q 34  0.374333  0.259691  0.423025  0.314221  0.515176  0.452783  0.564629   \n",
       "Q 35  0.236396  0.246147  0.345510  0.406090  0.444949  0.367093  0.346697   \n",
       "Q 36  0.232407  0.264367  0.295951  0.384220  0.492237  0.457570  0.331191   \n",
       "\n",
       "           Q 8       Q 9      Q 10  ...      Q 27      Q 28      Q 29  \\\n",
       "Q 1   0.256477  0.380395  0.394561  ...  0.568128  0.330949  0.478370   \n",
       "Q 2   0.234318  0.347751  0.324106  ...  0.453776  0.312127  0.357938   \n",
       "Q 3   0.288426  0.425865  0.450771  ...  0.630271  0.403319  0.489362   \n",
       "Q 4   0.389939  0.393116  0.334390  ...  0.456369  0.500917  0.528306   \n",
       "Q 5   0.406784  0.554752  0.415815  ...  0.552827  0.563569  0.558792   \n",
       "Q 6   0.374035  0.465835  0.424787  ...  0.580182  0.554844  0.558169   \n",
       "Q 7   0.201529  0.403301  0.620033  ...  0.461985  0.456775  0.283229   \n",
       "Q 8   1.000000  0.215740  0.357383  ...  0.206002  0.647682  0.273247   \n",
       "Q 9   0.215740  1.000000  0.485859  ...  0.589154  0.366277  0.508102   \n",
       "Q 10  0.357383  0.485859  1.000000  ...  0.565703  0.501559  0.276875   \n",
       "Q 11  0.206594  0.473468  0.434889  ...  0.337970  0.295313  0.282033   \n",
       "Q 12 -0.053633  0.392674  0.277876  ...  0.470955 -0.053296  0.455881   \n",
       "Q 13  0.322349  0.397430  0.381110  ...  0.447106  0.413930  0.527715   \n",
       "Q 14  0.282978  0.317617  0.286931  ...  0.297154  0.315696  0.348223   \n",
       "Q 15  0.320888  0.612997  0.419955  ...  0.526622  0.436655  0.608581   \n",
       "Q 16  0.375512  0.292023  0.474295  ...  0.335012  0.566162  0.262358   \n",
       "Q 17  0.159822  0.393651  0.398286  ...  0.609779  0.270473  0.520210   \n",
       "Q 18  0.443523  0.387692  0.399109  ...  0.392061  0.590575  0.397637   \n",
       "Q 19  0.184270  0.458182  0.413526  ...  0.548950  0.356815  0.455646   \n",
       "Q 20  0.269512  0.364936  0.056835  ...  0.381269  0.335803  0.428076   \n",
       "Q 21  0.443406  0.349824  0.396366  ...  0.450152  0.621590  0.365393   \n",
       "Q 22  0.038874  0.488941  0.368103  ...  0.630940  0.281257  0.542798   \n",
       "Q 23  0.539484  0.422420  0.379185  ...  0.505137  0.593881  0.415267   \n",
       "Q 24  0.358624  0.402817  0.270030  ...  0.381887  0.393994  0.379065   \n",
       "Q 25  0.316162  0.384972  0.244523  ...  0.254740  0.316917  0.411153   \n",
       "Q 26  0.348899  0.488665  0.345829  ...  0.291836  0.438820  0.438891   \n",
       "Q 27  0.206002  0.589154  0.565703  ...  1.000000  0.375795  0.549055   \n",
       "Q 28  0.647682  0.366277  0.501559  ...  0.375795  1.000000  0.353679   \n",
       "Q 29  0.273247  0.508102  0.276875  ...  0.549055  0.353679  1.000000   \n",
       "Q 30  0.418308  0.507467  0.541169  ...  0.524526  0.689739  0.365006   \n",
       "Q 31  0.457026  0.416263  0.473641  ...  0.528818  0.678342  0.472500   \n",
       "Q 32  0.363239  0.389485  0.351747  ...  0.490522  0.520982  0.582133   \n",
       "Q 33  0.286221  0.506160  0.452751  ...  0.706563  0.465957  0.492604   \n",
       "Q 34  0.558056  0.385551  0.510935  ...  0.526922  0.662679  0.267000   \n",
       "Q 35  0.471130  0.504548  0.447951  ...  0.498590  0.578142  0.460058   \n",
       "Q 36  0.378503  0.435495  0.292265  ...  0.466582  0.473011  0.365461   \n",
       "\n",
       "          Q 30      Q 31      Q 32      Q 33      Q 34      Q 35      Q 36  \n",
       "Q 1   0.415517  0.436911  0.575061  0.459879  0.374333  0.236396  0.232407  \n",
       "Q 2   0.431474  0.380224  0.537370  0.423989  0.259691  0.246147  0.264367  \n",
       "Q 3   0.454901  0.573294  0.480809  0.496521  0.423025  0.345510  0.295951  \n",
       "Q 4   0.470354  0.499578  0.572078  0.465465  0.314221  0.406090  0.384220  \n",
       "Q 5   0.561794  0.600689  0.626625  0.647329  0.515176  0.444949  0.492237  \n",
       "Q 6   0.637624  0.618549  0.621910  0.561770  0.452783  0.367093  0.457570  \n",
       "Q 7   0.435956  0.506129  0.439575  0.356167  0.564629  0.346697  0.331191  \n",
       "Q 8   0.418308  0.457026  0.363239  0.286221  0.558056  0.471130  0.378503  \n",
       "Q 9   0.507467  0.416263  0.389485  0.506160  0.385551  0.504548  0.435495  \n",
       "Q 10  0.541169  0.473641  0.351747  0.452751  0.510935  0.447951  0.292265  \n",
       "Q 11  0.314199  0.343369  0.201555  0.284499  0.350261  0.428425  0.389986  \n",
       "Q 12 -0.039882  0.136519  0.170035  0.419671 -0.007443  0.189604  0.168527  \n",
       "Q 13  0.332645  0.377020  0.504032  0.421159  0.410121  0.279154  0.282502  \n",
       "Q 14  0.366220  0.292851  0.447472  0.255085  0.240039  0.277103  0.268900  \n",
       "Q 15  0.346394  0.481616  0.461792  0.510623  0.353276  0.397723  0.331954  \n",
       "Q 16  0.551207  0.476219  0.481774  0.457022  0.569842  0.355869  0.306561  \n",
       "Q 17  0.327685  0.463257  0.413713  0.510931  0.253743  0.198840  0.175782  \n",
       "Q 18  0.531213  0.664112  0.429255  0.395946  0.414522  0.354854  0.268212  \n",
       "Q 19  0.541923  0.366159  0.539288  0.479419  0.408309  0.422074  0.338758  \n",
       "Q 20  0.521237  0.231371  0.509778  0.347203  0.320082  0.351322  0.331727  \n",
       "Q 21  0.423936  0.658380  0.422312  0.521976  0.402908  0.504359  0.384298  \n",
       "Q 22  0.354276  0.390586  0.440882  0.700141  0.291576  0.272703  0.248076  \n",
       "Q 23  0.571857  0.536599  0.520747  0.445519  0.589190  0.547799  0.514354  \n",
       "Q 24  0.320569  0.287055  0.415992  0.333442  0.403466  0.440413  0.447252  \n",
       "Q 25  0.176558  0.226988  0.336210  0.410335  0.294882  0.411094  0.418154  \n",
       "Q 26  0.278487  0.367285  0.377227  0.351901  0.320376  0.541897  0.484143  \n",
       "Q 27  0.524526  0.528818  0.490522  0.706563  0.526922  0.498590  0.466582  \n",
       "Q 28  0.689739  0.678342  0.520982  0.465957  0.662679  0.578142  0.473011  \n",
       "Q 29  0.365006  0.472500  0.582133  0.492604  0.267000  0.460058  0.365461  \n",
       "Q 30  1.000000  0.521864  0.468015  0.571134  0.670640  0.488761  0.451520  \n",
       "Q 31  0.521864  1.000000  0.578610  0.504627  0.514833  0.531840  0.447846  \n",
       "Q 32  0.468015  0.578610  1.000000  0.429675  0.460815  0.476943  0.512796  \n",
       "Q 33  0.571134  0.504627  0.429675  1.000000  0.565133  0.513610  0.438922  \n",
       "Q 34  0.670640  0.514833  0.460815  0.565133  1.000000  0.580683  0.600214  \n",
       "Q 35  0.488761  0.531840  0.476943  0.513610  0.580683  1.000000  0.754890  \n",
       "Q 36  0.451520  0.447846  0.512796  0.438922  0.600214  0.754890  1.000000  \n",
       "\n",
       "[36 rows x 36 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The original correlation matrix for the third cluster:\n",
    "cluster_3.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7cbdbd08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Eigenvalues</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15.517620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.704774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.136638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.732961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.402243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.324381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.977872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.939764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.907371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.771325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.717843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.596624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.583216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.537283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.524516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.472078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.453721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.395412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.355130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.325201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.309686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.270048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.251145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.226741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.212466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.184771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.165790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.160039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.153274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.142677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.134700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.119366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.102441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.076101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.066323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.048459</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Eigenvalues\n",
       "0     15.517620\n",
       "1      2.704774\n",
       "2      2.136638\n",
       "3      1.732961\n",
       "4      1.402243\n",
       "5      1.324381\n",
       "6      0.977872\n",
       "7      0.939764\n",
       "8      0.907371\n",
       "9      0.771325\n",
       "10     0.717843\n",
       "11     0.596624\n",
       "12     0.583216\n",
       "13     0.537283\n",
       "14     0.524516\n",
       "15     0.472078\n",
       "16     0.453721\n",
       "17     0.395412\n",
       "18     0.355130\n",
       "19     0.325201\n",
       "20     0.309686\n",
       "21     0.270048\n",
       "22     0.251145\n",
       "23     0.226741\n",
       "24     0.212466\n",
       "25     0.184771\n",
       "26     0.165790\n",
       "27     0.160039\n",
       "28     0.153274\n",
       "29     0.142677\n",
       "30     0.134700\n",
       "31     0.119366\n",
       "32     0.102441\n",
       "33     0.076101\n",
       "34     0.066323\n",
       "35     0.048459"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The eigenvalues are calculated for the third cluster\n",
    "\n",
    "fa_1 = FactorAnalyzer(n_factors=3, rotation='oblimin').fit(cluster_3)\n",
    "fa_1.loadings_\n",
    "\n",
    "eigenvalues, _ = fa_1.get_eigenvalues()\n",
    "eigen_values = list(eigenvalues)\n",
    "\n",
    "data_ev = pd.DataFrame(eigen_values,columns=['Eigenvalues'])\n",
    "\n",
    "data_ev\n",
    "\n",
    "# In this case, since the first 6 eigenvalues are greater than 1, the no. of factors is take to be 6."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ceca7c16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The factor loadings for the 6 Factors are presented in the form of a heatmap:\n",
    "\n",
    "fa_2 = FactorAnalyzer(n_factors=6, rotation='oblimin').fit(cluster_3)\n",
    "loadings = fa_2.loadings_\n",
    "\n",
    "plt.figure(figsize=(12, 12)) \n",
    "sns.heatmap(loadings, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
    "plt.title('Heatmap of Factor Loadings')\n",
    "plt.xlabel('Factors')\n",
    "plt.ylabel('Variables')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b2bfb8a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.380403</td>\n",
       "      <td>0.209602</td>\n",
       "      <td>0.394674</td>\n",
       "      <td>0.290906</td>\n",
       "      <td>0.423011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.380403</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.243327</td>\n",
       "      <td>0.394161</td>\n",
       "      <td>0.358487</td>\n",
       "      <td>0.194834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.209602</td>\n",
       "      <td>0.243327</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.214309</td>\n",
       "      <td>0.193404</td>\n",
       "      <td>0.277711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.394674</td>\n",
       "      <td>0.394161</td>\n",
       "      <td>0.214309</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.302745</td>\n",
       "      <td>0.328090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.290906</td>\n",
       "      <td>0.358487</td>\n",
       "      <td>0.193404</td>\n",
       "      <td>0.302745</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.137348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.423011</td>\n",
       "      <td>0.194834</td>\n",
       "      <td>0.277711</td>\n",
       "      <td>0.328090</td>\n",
       "      <td>0.137348</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5\n",
       "0  1.000000  0.380403  0.209602  0.394674  0.290906  0.423011\n",
       "1  0.380403  1.000000  0.243327  0.394161  0.358487  0.194834\n",
       "2  0.209602  0.243327  1.000000  0.214309  0.193404  0.277711\n",
       "3  0.394674  0.394161  0.214309  1.000000  0.302745  0.328090\n",
       "4  0.290906  0.358487  0.193404  0.302745  1.000000  0.137348\n",
       "5  0.423011  0.194834  0.277711  0.328090  0.137348  1.000000"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_mat_factors_3 = pd.DataFrame(fa_2.phi_)\n",
    "corr_mat_factors_3\n",
    "\n",
    "# The correlation matrix between the 6 Factors themselves:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1fb1162",
   "metadata": {},
   "source": [
    "## Factor Analysis of the fourth cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "515aab6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      "text/plain": [
       "     Q 1  Q 2  Q 3  Q 4  Q 5  Q 6  Q 7  Q 8  Q 9  Q 10  ...  Q 28  Q 29  Q 30  \\\n",
       "4      4    7    4    6    6    4    4    3    3     3  ...     7     1     7   \n",
       "8      7    6    7    3    3    3    1    4    6     7  ...     1     1     1   \n",
       "10     5    6    5    5    2    4    1    1    4     1  ...     1     6     4   \n",
       "22     3    6    3    3    4    1    1    1    3     1  ...     1     3     2   \n",
       "24     6    1    4    3    4    7    1    1    4     1  ...     1     3     3   \n",
       "..   ...  ...  ...  ...  ...  ...  ...  ...  ...   ...  ...   ...   ...   ...   \n",
       "405    1    2    1    1    1    1    2    1    2     1  ...     2     1     2   \n",
       "409    1    2    1    1    1    1    1    2    1     2  ...     1     1     1   \n",
       "410    4    5    5    5    4    6    3    4    4     2  ...     3     4     4   \n",
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       "427    5    5    6    6    4    7    4    3    6     4  ...     4     5     4   \n",
       "\n",
       "     Q 31  Q 32  Q 33  Q 34  Q 35  Q 36  Cluster  \n",
       "4       1     3     1     3     1     3        3  \n",
       "8       4     1     3     1     1     1        3  \n",
       "10      1     4     3     1     2     1        3  \n",
       "22      1     1     2     1     2     2        3  \n",
       "24      4     1     3     1     1     1        3  \n",
       "..    ...   ...   ...   ...   ...   ...      ...  \n",
       "405     1     1     1     1     1     1        3  \n",
       "409     1     1     1     1     1     1        3  \n",
       "410     3     3     3     3     2     2        3  \n",
       "425     5     5     5     5     5     5        3  \n",
       "427     4     5     4     4     5     6        3  \n",
       "\n",
       "[114 rows x 37 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Only the rows belionging to the 4th cluster are filtered out.\n",
    "\n",
    "cluster_4 = df.loc[df['Cluster']==3]\n",
    "cluster_4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "bb0c9e56",
   "metadata": {},
   "outputs": [
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>114 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Q 1  Q 2  Q 3  Q 4  Q 5  Q 6  Q 7  Q 8  Q 9  Q 10  ...  Q 27  Q 28  Q 29  \\\n",
       "4      4    7    4    6    6    4    4    3    3     3  ...     3     7     1   \n",
       "8      7    6    7    3    3    3    1    4    6     7  ...     7     1     1   \n",
       "10     5    6    5    5    2    4    1    1    4     1  ...     2     1     6   \n",
       "22     3    6    3    3    4    1    1    1    3     1  ...     3     1     3   \n",
       "24     6    1    4    3    4    7    1    1    4     1  ...     4     1     3   \n",
       "..   ...  ...  ...  ...  ...  ...  ...  ...  ...   ...  ...   ...   ...   ...   \n",
       "405    1    2    1    1    1    1    2    1    2     1  ...     1     2     1   \n",
       "409    1    2    1    1    1    1    1    2    1     2  ...     3     1     1   \n",
       "410    4    5    5    5    4    6    3    4    4     2  ...     3     3     4   \n",
       "425    3    6    7    6    4    6    5    4    4     3  ...     4     4     4   \n",
       "427    5    5    6    6    4    7    4    3    6     4  ...     4     4     5   \n",
       "\n",
       "     Q 30  Q 31  Q 32  Q 33  Q 34  Q 35  Q 36  \n",
       "4       7     1     3     1     3     1     3  \n",
       "8       1     4     1     3     1     1     1  \n",
       "10      4     1     4     3     1     2     1  \n",
       "22      2     1     1     2     1     2     2  \n",
       "24      3     4     1     3     1     1     1  \n",
       "..    ...   ...   ...   ...   ...   ...   ...  \n",
       "405     2     1     1     1     1     1     1  \n",
       "409     1     1     1     1     1     1     1  \n",
       "410     4     3     3     3     3     2     2  \n",
       "425     4     5     5     5     5     5     5  \n",
       "427     4     4     5     4     4     5     6  \n",
       "\n",
       "[114 rows x 36 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_4 = cluster_4.drop(columns=['Cluster'])\n",
    "cluster_4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ca573f93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KMO per variable: [0.9064693  0.80068888 0.93784398 0.91328119 0.89906454 0.87489443\n",
      " 0.80934307 0.79798246 0.90939638 0.82709031 0.58981948 0.82341909\n",
      " 0.84455059 0.83582326 0.8685629  0.90048414 0.85397739 0.80662724\n",
      " 0.89694898 0.83850205 0.87538047 0.88052623 0.72322942 0.67589569\n",
      " 0.84985764 0.78854205 0.91686961 0.90029612 0.84210417 0.89261925\n",
      " 0.84816499 0.84660175 0.88286373 0.86474214 0.83947089 0.82453979]\n",
      "Overall KMO: 0.8582586988899688\n"
     ]
    }
   ],
   "source": [
    "# Next the KMO (Kiaser-Meyer-Olkin) test was used to determine whether the cluster is suitable for factor analysis\n",
    "# The closer the overall KMO is to 1, the better suited the dataset.\n",
    "\n",
    "kmo_all, kmo_model = calculate_kmo(cluster_4)\n",
    "\n",
    "print(\"KMO per variable:\", kmo_all)\n",
    "print(\"Overall KMO:\", kmo_model)\n",
    "\n",
    "# Since the cluster has a reasonable KMO value, going ahead with the Factor Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "2f0eb439",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Q 1</th>\n",
       "      <th>Q 2</th>\n",
       "      <th>Q 3</th>\n",
       "      <th>Q 4</th>\n",
       "      <th>Q 5</th>\n",
       "      <th>Q 6</th>\n",
       "      <th>Q 7</th>\n",
       "      <th>Q 8</th>\n",
       "      <th>Q 9</th>\n",
       "      <th>Q 10</th>\n",
       "      <th>...</th>\n",
       "      <th>Q 27</th>\n",
       "      <th>Q 28</th>\n",
       "      <th>Q 29</th>\n",
       "      <th>Q 30</th>\n",
       "      <th>Q 31</th>\n",
       "      <th>Q 32</th>\n",
       "      <th>Q 33</th>\n",
       "      <th>Q 34</th>\n",
       "      <th>Q 35</th>\n",
       "      <th>Q 36</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Q 1</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.573871</td>\n",
       "      <td>0.669154</td>\n",
       "      <td>0.526101</td>\n",
       "      <td>0.646792</td>\n",
       "      <td>0.482355</td>\n",
       "      <td>0.272468</td>\n",
       "      <td>0.207093</td>\n",
       "      <td>0.489250</td>\n",
       "      <td>0.344058</td>\n",
       "      <td>...</td>\n",
       "      <td>0.596699</td>\n",
       "      <td>0.132476</td>\n",
       "      <td>0.366544</td>\n",
       "      <td>0.239243</td>\n",
       "      <td>0.503735</td>\n",
       "      <td>0.353691</td>\n",
       "      <td>0.451214</td>\n",
       "      <td>0.133794</td>\n",
       "      <td>0.287450</td>\n",
       "      <td>0.295776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 2</th>\n",
       "      <td>0.573871</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.479748</td>\n",
       "      <td>0.437800</td>\n",
       "      <td>0.471129</td>\n",
       "      <td>0.375128</td>\n",
       "      <td>0.243092</td>\n",
       "      <td>0.218233</td>\n",
       "      <td>0.293271</td>\n",
       "      <td>0.208458</td>\n",
       "      <td>...</td>\n",
       "      <td>0.424651</td>\n",
       "      <td>0.178961</td>\n",
       "      <td>0.149044</td>\n",
       "      <td>0.381380</td>\n",
       "      <td>0.203405</td>\n",
       "      <td>0.367809</td>\n",
       "      <td>0.218704</td>\n",
       "      <td>0.171684</td>\n",
       "      <td>0.303920</td>\n",
       "      <td>0.320168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 3</th>\n",
       "      <td>0.669154</td>\n",
       "      <td>0.479748</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.777419</td>\n",
       "      <td>0.675575</td>\n",
       "      <td>0.669176</td>\n",
       "      <td>0.498279</td>\n",
       "      <td>0.461279</td>\n",
       "      <td>0.590553</td>\n",
       "      <td>0.473465</td>\n",
       "      <td>...</td>\n",
       "      <td>0.640392</td>\n",
       "      <td>0.343883</td>\n",
       "      <td>0.442548</td>\n",
       "      <td>0.439897</td>\n",
       "      <td>0.607603</td>\n",
       "      <td>0.520565</td>\n",
       "      <td>0.647261</td>\n",
       "      <td>0.465462</td>\n",
       "      <td>0.454006</td>\n",
       "      <td>0.450558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 4</th>\n",
       "      <td>0.526101</td>\n",
       "      <td>0.437800</td>\n",
       "      <td>0.777419</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.625374</td>\n",
       "      <td>0.682040</td>\n",
       "      <td>0.456330</td>\n",
       "      <td>0.410793</td>\n",
       "      <td>0.478073</td>\n",
       "      <td>0.437129</td>\n",
       "      <td>...</td>\n",
       "      <td>0.538583</td>\n",
       "      <td>0.342517</td>\n",
       "      <td>0.514073</td>\n",
       "      <td>0.518876</td>\n",
       "      <td>0.522054</td>\n",
       "      <td>0.448060</td>\n",
       "      <td>0.597286</td>\n",
       "      <td>0.541454</td>\n",
       "      <td>0.449094</td>\n",
       "      <td>0.482900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 5</th>\n",
       "      <td>0.646792</td>\n",
       "      <td>0.471129</td>\n",
       "      <td>0.675575</td>\n",
       "      <td>0.625374</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.622860</td>\n",
       "      <td>0.385462</td>\n",
       "      <td>0.385270</td>\n",
       "      <td>0.498897</td>\n",
       "      <td>0.423784</td>\n",
       "      <td>...</td>\n",
       "      <td>0.612249</td>\n",
       "      <td>0.480914</td>\n",
       "      <td>0.493033</td>\n",
       "      <td>0.438491</td>\n",
       "      <td>0.592683</td>\n",
       "      <td>0.582985</td>\n",
       "      <td>0.665871</td>\n",
       "      <td>0.384299</td>\n",
       "      <td>0.440640</td>\n",
       "      <td>0.421336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 6</th>\n",
       "      <td>0.482355</td>\n",
       "      <td>0.375128</td>\n",
       "      <td>0.669176</td>\n",
       "      <td>0.682040</td>\n",
       "      <td>0.622860</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.510452</td>\n",
       "      <td>0.393451</td>\n",
       "      <td>0.365699</td>\n",
       "      <td>0.439968</td>\n",
       "      <td>...</td>\n",
       "      <td>0.461831</td>\n",
       "      <td>0.501933</td>\n",
       "      <td>0.451923</td>\n",
       "      <td>0.508442</td>\n",
       "      <td>0.657301</td>\n",
       "      <td>0.464458</td>\n",
       "      <td>0.569817</td>\n",
       "      <td>0.571561</td>\n",
       "      <td>0.516192</td>\n",
       "      <td>0.498304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 7</th>\n",
       "      <td>0.272468</td>\n",
       "      <td>0.243092</td>\n",
       "      <td>0.498279</td>\n",
       "      <td>0.456330</td>\n",
       "      <td>0.385462</td>\n",
       "      <td>0.510452</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.334455</td>\n",
       "      <td>0.147805</td>\n",
       "      <td>0.463795</td>\n",
       "      <td>...</td>\n",
       "      <td>0.317513</td>\n",
       "      <td>0.496875</td>\n",
       "      <td>0.105365</td>\n",
       "      <td>0.335551</td>\n",
       "      <td>0.552608</td>\n",
       "      <td>0.372131</td>\n",
       "      <td>0.372525</td>\n",
       "      <td>0.439540</td>\n",
       "      <td>0.383394</td>\n",
       "      <td>0.318140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 8</th>\n",
       "      <td>0.207093</td>\n",
       "      <td>0.218233</td>\n",
       "      <td>0.461279</td>\n",
       "      <td>0.410793</td>\n",
       "      <td>0.385270</td>\n",
       "      <td>0.393451</td>\n",
       "      <td>0.334455</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.273900</td>\n",
       "      <td>0.375014</td>\n",
       "      <td>...</td>\n",
       "      <td>0.356514</td>\n",
       "      <td>0.448058</td>\n",
       "      <td>0.071285</td>\n",
       "      <td>0.290304</td>\n",
       "      <td>0.389796</td>\n",
       "      <td>0.391614</td>\n",
       "      <td>0.441025</td>\n",
       "      <td>0.499979</td>\n",
       "      <td>0.316359</td>\n",
       "      <td>0.351067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 9</th>\n",
       "      <td>0.489250</td>\n",
       "      <td>0.293271</td>\n",
       "      <td>0.590553</td>\n",
       "      <td>0.478073</td>\n",
       "      <td>0.498897</td>\n",
       "      <td>0.365699</td>\n",
       "      <td>0.147805</td>\n",
       "      <td>0.273900</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.136058</td>\n",
       "      <td>...</td>\n",
       "      <td>0.642071</td>\n",
       "      <td>0.082524</td>\n",
       "      <td>0.546009</td>\n",
       "      <td>0.319898</td>\n",
       "      <td>0.330892</td>\n",
       "      <td>0.457684</td>\n",
       "      <td>0.487169</td>\n",
       "      <td>0.141105</td>\n",
       "      <td>0.378409</td>\n",
       "      <td>0.359018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 10</th>\n",
       "      <td>0.344058</td>\n",
       "      <td>0.208458</td>\n",
       "      <td>0.473465</td>\n",
       "      <td>0.437129</td>\n",
       "      <td>0.423784</td>\n",
       "      <td>0.439968</td>\n",
       "      <td>0.463795</td>\n",
       "      <td>0.375014</td>\n",
       "      <td>0.136058</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.411286</td>\n",
       "      <td>0.375520</td>\n",
       "      <td>0.064800</td>\n",
       "      <td>0.295031</td>\n",
       "      <td>0.468539</td>\n",
       "      <td>0.307211</td>\n",
       "      <td>0.443923</td>\n",
       "      <td>0.447151</td>\n",
       "      <td>0.286626</td>\n",
       "      <td>0.319226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 11</th>\n",
       "      <td>0.212885</td>\n",
       "      <td>0.300356</td>\n",
       "      <td>0.237931</td>\n",
       "      <td>0.229674</td>\n",
       "      <td>0.245429</td>\n",
       "      <td>0.227829</td>\n",
       "      <td>0.438921</td>\n",
       "      <td>0.243410</td>\n",
       "      <td>0.086862</td>\n",
       "      <td>0.278251</td>\n",
       "      <td>...</td>\n",
       "      <td>0.126211</td>\n",
       "      <td>0.243637</td>\n",
       "      <td>0.032842</td>\n",
       "      <td>0.138204</td>\n",
       "      <td>0.188098</td>\n",
       "      <td>0.078951</td>\n",
       "      <td>0.043536</td>\n",
       "      <td>0.293112</td>\n",
       "      <td>0.077306</td>\n",
       "      <td>0.119966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 12</th>\n",
       "      <td>0.485771</td>\n",
       "      <td>0.192712</td>\n",
       "      <td>0.448536</td>\n",
       "      <td>0.368435</td>\n",
       "      <td>0.512567</td>\n",
       "      <td>0.255803</td>\n",
       "      <td>0.079118</td>\n",
       "      <td>0.086111</td>\n",
       "      <td>0.578083</td>\n",
       "      <td>0.142430</td>\n",
       "      <td>...</td>\n",
       "      <td>0.463277</td>\n",
       "      <td>0.072368</td>\n",
       "      <td>0.582370</td>\n",
       "      <td>0.086725</td>\n",
       "      <td>0.260195</td>\n",
       "      <td>0.137390</td>\n",
       "      <td>0.380688</td>\n",
       "      <td>-0.002908</td>\n",
       "      <td>0.109275</td>\n",
       "      <td>0.144195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 13</th>\n",
       "      <td>0.531661</td>\n",
       "      <td>0.381853</td>\n",
       "      <td>0.505081</td>\n",
       "      <td>0.416312</td>\n",
       "      <td>0.384865</td>\n",
       "      <td>0.339536</td>\n",
       "      <td>0.243788</td>\n",
       "      <td>0.125916</td>\n",
       "      <td>0.389025</td>\n",
       "      <td>0.388226</td>\n",
       "      <td>...</td>\n",
       "      <td>0.360102</td>\n",
       "      <td>0.147434</td>\n",
       "      <td>0.276871</td>\n",
       "      <td>0.323174</td>\n",
       "      <td>0.287376</td>\n",
       "      <td>0.320871</td>\n",
       "      <td>0.352125</td>\n",
       "      <td>0.224569</td>\n",
       "      <td>0.138421</td>\n",
       "      <td>0.210523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 14</th>\n",
       "      <td>0.234956</td>\n",
       "      <td>0.279152</td>\n",
       "      <td>0.446884</td>\n",
       "      <td>0.296873</td>\n",
       "      <td>0.342993</td>\n",
       "      <td>0.259022</td>\n",
       "      <td>0.282497</td>\n",
       "      <td>0.287095</td>\n",
       "      <td>0.480431</td>\n",
       "      <td>0.344274</td>\n",
       "      <td>...</td>\n",
       "      <td>0.565062</td>\n",
       "      <td>0.276317</td>\n",
       "      <td>0.235351</td>\n",
       "      <td>0.229977</td>\n",
       "      <td>0.237232</td>\n",
       "      <td>0.427916</td>\n",
       "      <td>0.296961</td>\n",
       "      <td>0.161410</td>\n",
       "      <td>0.240800</td>\n",
       "      <td>0.220581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 15</th>\n",
       "      <td>0.540789</td>\n",
       "      <td>0.250022</td>\n",
       "      <td>0.529837</td>\n",
       "      <td>0.553818</td>\n",
       "      <td>0.616161</td>\n",
       "      <td>0.433325</td>\n",
       "      <td>0.264597</td>\n",
       "      <td>0.200784</td>\n",
       "      <td>0.544331</td>\n",
       "      <td>0.126101</td>\n",
       "      <td>...</td>\n",
       "      <td>0.534510</td>\n",
       "      <td>0.155800</td>\n",
       "      <td>0.653527</td>\n",
       "      <td>0.205928</td>\n",
       "      <td>0.395048</td>\n",
       "      <td>0.367299</td>\n",
       "      <td>0.469067</td>\n",
       "      <td>0.142692</td>\n",
       "      <td>0.294464</td>\n",
       "      <td>0.307636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 16</th>\n",
       "      <td>0.383788</td>\n",
       "      <td>0.366315</td>\n",
       "      <td>0.580080</td>\n",
       "      <td>0.592155</td>\n",
       "      <td>0.569715</td>\n",
       "      <td>0.566782</td>\n",
       "      <td>0.574869</td>\n",
       "      <td>0.486514</td>\n",
       "      <td>0.175145</td>\n",
       "      <td>0.483145</td>\n",
       "      <td>...</td>\n",
       "      <td>0.418794</td>\n",
       "      <td>0.522041</td>\n",
       "      <td>0.118111</td>\n",
       "      <td>0.421833</td>\n",
       "      <td>0.549998</td>\n",
       "      <td>0.419746</td>\n",
       "      <td>0.434111</td>\n",
       "      <td>0.525296</td>\n",
       "      <td>0.358512</td>\n",
       "      <td>0.277313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 17</th>\n",
       "      <td>0.557866</td>\n",
       "      <td>0.255706</td>\n",
       "      <td>0.693521</td>\n",
       "      <td>0.588662</td>\n",
       "      <td>0.476016</td>\n",
       "      <td>0.547413</td>\n",
       "      <td>0.421292</td>\n",
       "      <td>0.372441</td>\n",
       "      <td>0.389358</td>\n",
       "      <td>0.384839</td>\n",
       "      <td>...</td>\n",
       "      <td>0.409348</td>\n",
       "      <td>0.250300</td>\n",
       "      <td>0.308748</td>\n",
       "      <td>0.357654</td>\n",
       "      <td>0.599524</td>\n",
       "      <td>0.490145</td>\n",
       "      <td>0.499790</td>\n",
       "      <td>0.307287</td>\n",
       "      <td>0.253477</td>\n",
       "      <td>0.301171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 18</th>\n",
       "      <td>0.547908</td>\n",
       "      <td>0.418934</td>\n",
       "      <td>0.567729</td>\n",
       "      <td>0.585816</td>\n",
       "      <td>0.521348</td>\n",
       "      <td>0.582003</td>\n",
       "      <td>0.557519</td>\n",
       "      <td>0.366257</td>\n",
       "      <td>0.230471</td>\n",
       "      <td>0.566288</td>\n",
       "      <td>...</td>\n",
       "      <td>0.425224</td>\n",
       "      <td>0.319046</td>\n",
       "      <td>0.285870</td>\n",
       "      <td>0.343589</td>\n",
       "      <td>0.630401</td>\n",
       "      <td>0.400510</td>\n",
       "      <td>0.415854</td>\n",
       "      <td>0.418966</td>\n",
       "      <td>0.381991</td>\n",
       "      <td>0.388221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 19</th>\n",
       "      <td>0.597085</td>\n",
       "      <td>0.598435</td>\n",
       "      <td>0.655558</td>\n",
       "      <td>0.622731</td>\n",
       "      <td>0.743904</td>\n",
       "      <td>0.590301</td>\n",
       "      <td>0.446755</td>\n",
       "      <td>0.284478</td>\n",
       "      <td>0.475203</td>\n",
       "      <td>0.415155</td>\n",
       "      <td>...</td>\n",
       "      <td>0.549471</td>\n",
       "      <td>0.367729</td>\n",
       "      <td>0.439203</td>\n",
       "      <td>0.413245</td>\n",
       "      <td>0.433079</td>\n",
       "      <td>0.568993</td>\n",
       "      <td>0.425994</td>\n",
       "      <td>0.291376</td>\n",
       "      <td>0.327518</td>\n",
       "      <td>0.321281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 20</th>\n",
       "      <td>0.241674</td>\n",
       "      <td>0.390000</td>\n",
       "      <td>0.360902</td>\n",
       "      <td>0.419749</td>\n",
       "      <td>0.492733</td>\n",
       "      <td>0.393906</td>\n",
       "      <td>0.150814</td>\n",
       "      <td>0.189757</td>\n",
       "      <td>0.453087</td>\n",
       "      <td>0.232041</td>\n",
       "      <td>...</td>\n",
       "      <td>0.433472</td>\n",
       "      <td>0.322649</td>\n",
       "      <td>0.451570</td>\n",
       "      <td>0.486199</td>\n",
       "      <td>0.230808</td>\n",
       "      <td>0.399269</td>\n",
       "      <td>0.333998</td>\n",
       "      <td>0.232783</td>\n",
       "      <td>0.384962</td>\n",
       "      <td>0.416951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 21</th>\n",
       "      <td>0.205974</td>\n",
       "      <td>0.155859</td>\n",
       "      <td>0.511335</td>\n",
       "      <td>0.520046</td>\n",
       "      <td>0.530016</td>\n",
       "      <td>0.422337</td>\n",
       "      <td>0.440246</td>\n",
       "      <td>0.443286</td>\n",
       "      <td>0.388644</td>\n",
       "      <td>0.391105</td>\n",
       "      <td>...</td>\n",
       "      <td>0.444209</td>\n",
       "      <td>0.574714</td>\n",
       "      <td>0.360072</td>\n",
       "      <td>0.500443</td>\n",
       "      <td>0.418010</td>\n",
       "      <td>0.422712</td>\n",
       "      <td>0.579700</td>\n",
       "      <td>0.502213</td>\n",
       "      <td>0.417638</td>\n",
       "      <td>0.410642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 22</th>\n",
       "      <td>0.508031</td>\n",
       "      <td>0.270957</td>\n",
       "      <td>0.613128</td>\n",
       "      <td>0.499354</td>\n",
       "      <td>0.642458</td>\n",
       "      <td>0.479720</td>\n",
       "      <td>0.268593</td>\n",
       "      <td>0.128798</td>\n",
       "      <td>0.587875</td>\n",
       "      <td>0.358712</td>\n",
       "      <td>...</td>\n",
       "      <td>0.544182</td>\n",
       "      <td>0.233592</td>\n",
       "      <td>0.589565</td>\n",
       "      <td>0.292790</td>\n",
       "      <td>0.310642</td>\n",
       "      <td>0.421417</td>\n",
       "      <td>0.540671</td>\n",
       "      <td>0.196931</td>\n",
       "      <td>0.360584</td>\n",
       "      <td>0.352849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 23</th>\n",
       "      <td>0.129460</td>\n",
       "      <td>0.281114</td>\n",
       "      <td>0.293702</td>\n",
       "      <td>0.308419</td>\n",
       "      <td>0.462208</td>\n",
       "      <td>0.248560</td>\n",
       "      <td>0.316071</td>\n",
       "      <td>0.363229</td>\n",
       "      <td>0.084834</td>\n",
       "      <td>0.255400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.203536</td>\n",
       "      <td>0.613435</td>\n",
       "      <td>0.085401</td>\n",
       "      <td>0.360153</td>\n",
       "      <td>0.330995</td>\n",
       "      <td>0.263420</td>\n",
       "      <td>0.260361</td>\n",
       "      <td>0.424391</td>\n",
       "      <td>0.236666</td>\n",
       "      <td>0.308776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 24</th>\n",
       "      <td>0.116045</td>\n",
       "      <td>0.260093</td>\n",
       "      <td>0.230861</td>\n",
       "      <td>0.228442</td>\n",
       "      <td>0.288966</td>\n",
       "      <td>0.325550</td>\n",
       "      <td>0.186768</td>\n",
       "      <td>0.206253</td>\n",
       "      <td>-0.004484</td>\n",
       "      <td>0.176512</td>\n",
       "      <td>...</td>\n",
       "      <td>0.122706</td>\n",
       "      <td>0.394023</td>\n",
       "      <td>0.063794</td>\n",
       "      <td>0.179300</td>\n",
       "      <td>0.220058</td>\n",
       "      <td>0.241250</td>\n",
       "      <td>0.108851</td>\n",
       "      <td>0.293458</td>\n",
       "      <td>0.101080</td>\n",
       "      <td>0.010201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 25</th>\n",
       "      <td>0.090660</td>\n",
       "      <td>0.041564</td>\n",
       "      <td>0.266107</td>\n",
       "      <td>0.256195</td>\n",
       "      <td>0.406784</td>\n",
       "      <td>0.356551</td>\n",
       "      <td>0.282266</td>\n",
       "      <td>0.187836</td>\n",
       "      <td>0.338182</td>\n",
       "      <td>0.290400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.302326</td>\n",
       "      <td>0.493779</td>\n",
       "      <td>0.291527</td>\n",
       "      <td>0.281040</td>\n",
       "      <td>0.284758</td>\n",
       "      <td>0.313350</td>\n",
       "      <td>0.403633</td>\n",
       "      <td>0.351413</td>\n",
       "      <td>0.274293</td>\n",
       "      <td>0.268039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 26</th>\n",
       "      <td>0.188796</td>\n",
       "      <td>0.146522</td>\n",
       "      <td>0.372148</td>\n",
       "      <td>0.312097</td>\n",
       "      <td>0.340354</td>\n",
       "      <td>0.357163</td>\n",
       "      <td>0.326283</td>\n",
       "      <td>0.239169</td>\n",
       "      <td>0.315536</td>\n",
       "      <td>0.319197</td>\n",
       "      <td>...</td>\n",
       "      <td>0.450321</td>\n",
       "      <td>0.310568</td>\n",
       "      <td>0.205522</td>\n",
       "      <td>0.310030</td>\n",
       "      <td>0.247215</td>\n",
       "      <td>0.415799</td>\n",
       "      <td>0.341310</td>\n",
       "      <td>0.207189</td>\n",
       "      <td>0.388574</td>\n",
       "      <td>0.429327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 27</th>\n",
       "      <td>0.596699</td>\n",
       "      <td>0.424651</td>\n",
       "      <td>0.640392</td>\n",
       "      <td>0.538583</td>\n",
       "      <td>0.612249</td>\n",
       "      <td>0.461831</td>\n",
       "      <td>0.317513</td>\n",
       "      <td>0.356514</td>\n",
       "      <td>0.642071</td>\n",
       "      <td>0.411286</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.202714</td>\n",
       "      <td>0.434773</td>\n",
       "      <td>0.344251</td>\n",
       "      <td>0.480031</td>\n",
       "      <td>0.483976</td>\n",
       "      <td>0.597642</td>\n",
       "      <td>0.206303</td>\n",
       "      <td>0.473865</td>\n",
       "      <td>0.435564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 28</th>\n",
       "      <td>0.132476</td>\n",
       "      <td>0.178961</td>\n",
       "      <td>0.343883</td>\n",
       "      <td>0.342517</td>\n",
       "      <td>0.480914</td>\n",
       "      <td>0.501933</td>\n",
       "      <td>0.496875</td>\n",
       "      <td>0.448058</td>\n",
       "      <td>0.082524</td>\n",
       "      <td>0.375520</td>\n",
       "      <td>...</td>\n",
       "      <td>0.202714</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.117809</td>\n",
       "      <td>0.473585</td>\n",
       "      <td>0.438350</td>\n",
       "      <td>0.318174</td>\n",
       "      <td>0.384442</td>\n",
       "      <td>0.554824</td>\n",
       "      <td>0.348581</td>\n",
       "      <td>0.318435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 29</th>\n",
       "      <td>0.366544</td>\n",
       "      <td>0.149044</td>\n",
       "      <td>0.442548</td>\n",
       "      <td>0.514073</td>\n",
       "      <td>0.493033</td>\n",
       "      <td>0.451923</td>\n",
       "      <td>0.105365</td>\n",
       "      <td>0.071285</td>\n",
       "      <td>0.546009</td>\n",
       "      <td>0.064800</td>\n",
       "      <td>...</td>\n",
       "      <td>0.434773</td>\n",
       "      <td>0.117809</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.247393</td>\n",
       "      <td>0.321493</td>\n",
       "      <td>0.442981</td>\n",
       "      <td>0.573960</td>\n",
       "      <td>0.233037</td>\n",
       "      <td>0.481229</td>\n",
       "      <td>0.376310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 30</th>\n",
       "      <td>0.239243</td>\n",
       "      <td>0.381380</td>\n",
       "      <td>0.439897</td>\n",
       "      <td>0.518876</td>\n",
       "      <td>0.438491</td>\n",
       "      <td>0.508442</td>\n",
       "      <td>0.335551</td>\n",
       "      <td>0.290304</td>\n",
       "      <td>0.319898</td>\n",
       "      <td>0.295031</td>\n",
       "      <td>...</td>\n",
       "      <td>0.344251</td>\n",
       "      <td>0.473585</td>\n",
       "      <td>0.247393</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.349955</td>\n",
       "      <td>0.362550</td>\n",
       "      <td>0.371622</td>\n",
       "      <td>0.387877</td>\n",
       "      <td>0.443595</td>\n",
       "      <td>0.517715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 31</th>\n",
       "      <td>0.503735</td>\n",
       "      <td>0.203405</td>\n",
       "      <td>0.607603</td>\n",
       "      <td>0.522054</td>\n",
       "      <td>0.592683</td>\n",
       "      <td>0.657301</td>\n",
       "      <td>0.552608</td>\n",
       "      <td>0.389796</td>\n",
       "      <td>0.330892</td>\n",
       "      <td>0.468539</td>\n",
       "      <td>...</td>\n",
       "      <td>0.480031</td>\n",
       "      <td>0.438350</td>\n",
       "      <td>0.321493</td>\n",
       "      <td>0.349955</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.413797</td>\n",
       "      <td>0.576400</td>\n",
       "      <td>0.564796</td>\n",
       "      <td>0.329534</td>\n",
       "      <td>0.310442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 32</th>\n",
       "      <td>0.353691</td>\n",
       "      <td>0.367809</td>\n",
       "      <td>0.520565</td>\n",
       "      <td>0.448060</td>\n",
       "      <td>0.582985</td>\n",
       "      <td>0.464458</td>\n",
       "      <td>0.372131</td>\n",
       "      <td>0.391614</td>\n",
       "      <td>0.457684</td>\n",
       "      <td>0.307211</td>\n",
       "      <td>...</td>\n",
       "      <td>0.483976</td>\n",
       "      <td>0.318174</td>\n",
       "      <td>0.442981</td>\n",
       "      <td>0.362550</td>\n",
       "      <td>0.413797</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.582713</td>\n",
       "      <td>0.328180</td>\n",
       "      <td>0.510443</td>\n",
       "      <td>0.416973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 33</th>\n",
       "      <td>0.451214</td>\n",
       "      <td>0.218704</td>\n",
       "      <td>0.647261</td>\n",
       "      <td>0.597286</td>\n",
       "      <td>0.665871</td>\n",
       "      <td>0.569817</td>\n",
       "      <td>0.372525</td>\n",
       "      <td>0.441025</td>\n",
       "      <td>0.487169</td>\n",
       "      <td>0.443923</td>\n",
       "      <td>...</td>\n",
       "      <td>0.597642</td>\n",
       "      <td>0.384442</td>\n",
       "      <td>0.573960</td>\n",
       "      <td>0.371622</td>\n",
       "      <td>0.576400</td>\n",
       "      <td>0.582713</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.490884</td>\n",
       "      <td>0.620403</td>\n",
       "      <td>0.532142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 34</th>\n",
       "      <td>0.133794</td>\n",
       "      <td>0.171684</td>\n",
       "      <td>0.465462</td>\n",
       "      <td>0.541454</td>\n",
       "      <td>0.384299</td>\n",
       "      <td>0.571561</td>\n",
       "      <td>0.439540</td>\n",
       "      <td>0.499979</td>\n",
       "      <td>0.141105</td>\n",
       "      <td>0.447151</td>\n",
       "      <td>...</td>\n",
       "      <td>0.206303</td>\n",
       "      <td>0.554824</td>\n",
       "      <td>0.233037</td>\n",
       "      <td>0.387877</td>\n",
       "      <td>0.564796</td>\n",
       "      <td>0.328180</td>\n",
       "      <td>0.490884</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.475592</td>\n",
       "      <td>0.490727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 35</th>\n",
       "      <td>0.287450</td>\n",
       "      <td>0.303920</td>\n",
       "      <td>0.454006</td>\n",
       "      <td>0.449094</td>\n",
       "      <td>0.440640</td>\n",
       "      <td>0.516192</td>\n",
       "      <td>0.383394</td>\n",
       "      <td>0.316359</td>\n",
       "      <td>0.378409</td>\n",
       "      <td>0.286626</td>\n",
       "      <td>...</td>\n",
       "      <td>0.473865</td>\n",
       "      <td>0.348581</td>\n",
       "      <td>0.481229</td>\n",
       "      <td>0.443595</td>\n",
       "      <td>0.329534</td>\n",
       "      <td>0.510443</td>\n",
       "      <td>0.620403</td>\n",
       "      <td>0.475592</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.850720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q 36</th>\n",
       "      <td>0.295776</td>\n",
       "      <td>0.320168</td>\n",
       "      <td>0.450558</td>\n",
       "      <td>0.482900</td>\n",
       "      <td>0.421336</td>\n",
       "      <td>0.498304</td>\n",
       "      <td>0.318140</td>\n",
       "      <td>0.351067</td>\n",
       "      <td>0.359018</td>\n",
       "      <td>0.319226</td>\n",
       "      <td>...</td>\n",
       "      <td>0.435564</td>\n",
       "      <td>0.318435</td>\n",
       "      <td>0.376310</td>\n",
       "      <td>0.517715</td>\n",
       "      <td>0.310442</td>\n",
       "      <td>0.416973</td>\n",
       "      <td>0.532142</td>\n",
       "      <td>0.490727</td>\n",
       "      <td>0.850720</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>36 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Q 1       Q 2       Q 3       Q 4       Q 5       Q 6       Q 7  \\\n",
       "Q 1   1.000000  0.573871  0.669154  0.526101  0.646792  0.482355  0.272468   \n",
       "Q 2   0.573871  1.000000  0.479748  0.437800  0.471129  0.375128  0.243092   \n",
       "Q 3   0.669154  0.479748  1.000000  0.777419  0.675575  0.669176  0.498279   \n",
       "Q 4   0.526101  0.437800  0.777419  1.000000  0.625374  0.682040  0.456330   \n",
       "Q 5   0.646792  0.471129  0.675575  0.625374  1.000000  0.622860  0.385462   \n",
       "Q 6   0.482355  0.375128  0.669176  0.682040  0.622860  1.000000  0.510452   \n",
       "Q 7   0.272468  0.243092  0.498279  0.456330  0.385462  0.510452  1.000000   \n",
       "Q 8   0.207093  0.218233  0.461279  0.410793  0.385270  0.393451  0.334455   \n",
       "Q 9   0.489250  0.293271  0.590553  0.478073  0.498897  0.365699  0.147805   \n",
       "Q 10  0.344058  0.208458  0.473465  0.437129  0.423784  0.439968  0.463795   \n",
       "Q 11  0.212885  0.300356  0.237931  0.229674  0.245429  0.227829  0.438921   \n",
       "Q 12  0.485771  0.192712  0.448536  0.368435  0.512567  0.255803  0.079118   \n",
       "Q 13  0.531661  0.381853  0.505081  0.416312  0.384865  0.339536  0.243788   \n",
       "Q 14  0.234956  0.279152  0.446884  0.296873  0.342993  0.259022  0.282497   \n",
       "Q 15  0.540789  0.250022  0.529837  0.553818  0.616161  0.433325  0.264597   \n",
       "Q 16  0.383788  0.366315  0.580080  0.592155  0.569715  0.566782  0.574869   \n",
       "Q 17  0.557866  0.255706  0.693521  0.588662  0.476016  0.547413  0.421292   \n",
       "Q 18  0.547908  0.418934  0.567729  0.585816  0.521348  0.582003  0.557519   \n",
       "Q 19  0.597085  0.598435  0.655558  0.622731  0.743904  0.590301  0.446755   \n",
       "Q 20  0.241674  0.390000  0.360902  0.419749  0.492733  0.393906  0.150814   \n",
       "Q 21  0.205974  0.155859  0.511335  0.520046  0.530016  0.422337  0.440246   \n",
       "Q 22  0.508031  0.270957  0.613128  0.499354  0.642458  0.479720  0.268593   \n",
       "Q 23  0.129460  0.281114  0.293702  0.308419  0.462208  0.248560  0.316071   \n",
       "Q 24  0.116045  0.260093  0.230861  0.228442  0.288966  0.325550  0.186768   \n",
       "Q 25  0.090660  0.041564  0.266107  0.256195  0.406784  0.356551  0.282266   \n",
       "Q 26  0.188796  0.146522  0.372148  0.312097  0.340354  0.357163  0.326283   \n",
       "Q 27  0.596699  0.424651  0.640392  0.538583  0.612249  0.461831  0.317513   \n",
       "Q 28  0.132476  0.178961  0.343883  0.342517  0.480914  0.501933  0.496875   \n",
       "Q 29  0.366544  0.149044  0.442548  0.514073  0.493033  0.451923  0.105365   \n",
       "Q 30  0.239243  0.381380  0.439897  0.518876  0.438491  0.508442  0.335551   \n",
       "Q 31  0.503735  0.203405  0.607603  0.522054  0.592683  0.657301  0.552608   \n",
       "Q 32  0.353691  0.367809  0.520565  0.448060  0.582985  0.464458  0.372131   \n",
       "Q 33  0.451214  0.218704  0.647261  0.597286  0.665871  0.569817  0.372525   \n",
       "Q 34  0.133794  0.171684  0.465462  0.541454  0.384299  0.571561  0.439540   \n",
       "Q 35  0.287450  0.303920  0.454006  0.449094  0.440640  0.516192  0.383394   \n",
       "Q 36  0.295776  0.320168  0.450558  0.482900  0.421336  0.498304  0.318140   \n",
       "\n",
       "           Q 8       Q 9      Q 10  ...      Q 27      Q 28      Q 29  \\\n",
       "Q 1   0.207093  0.489250  0.344058  ...  0.596699  0.132476  0.366544   \n",
       "Q 2   0.218233  0.293271  0.208458  ...  0.424651  0.178961  0.149044   \n",
       "Q 3   0.461279  0.590553  0.473465  ...  0.640392  0.343883  0.442548   \n",
       "Q 4   0.410793  0.478073  0.437129  ...  0.538583  0.342517  0.514073   \n",
       "Q 5   0.385270  0.498897  0.423784  ...  0.612249  0.480914  0.493033   \n",
       "Q 6   0.393451  0.365699  0.439968  ...  0.461831  0.501933  0.451923   \n",
       "Q 7   0.334455  0.147805  0.463795  ...  0.317513  0.496875  0.105365   \n",
       "Q 8   1.000000  0.273900  0.375014  ...  0.356514  0.448058  0.071285   \n",
       "Q 9   0.273900  1.000000  0.136058  ...  0.642071  0.082524  0.546009   \n",
       "Q 10  0.375014  0.136058  1.000000  ...  0.411286  0.375520  0.064800   \n",
       "Q 11  0.243410  0.086862  0.278251  ...  0.126211  0.243637  0.032842   \n",
       "Q 12  0.086111  0.578083  0.142430  ...  0.463277  0.072368  0.582370   \n",
       "Q 13  0.125916  0.389025  0.388226  ...  0.360102  0.147434  0.276871   \n",
       "Q 14  0.287095  0.480431  0.344274  ...  0.565062  0.276317  0.235351   \n",
       "Q 15  0.200784  0.544331  0.126101  ...  0.534510  0.155800  0.653527   \n",
       "Q 16  0.486514  0.175145  0.483145  ...  0.418794  0.522041  0.118111   \n",
       "Q 17  0.372441  0.389358  0.384839  ...  0.409348  0.250300  0.308748   \n",
       "Q 18  0.366257  0.230471  0.566288  ...  0.425224  0.319046  0.285870   \n",
       "Q 19  0.284478  0.475203  0.415155  ...  0.549471  0.367729  0.439203   \n",
       "Q 20  0.189757  0.453087  0.232041  ...  0.433472  0.322649  0.451570   \n",
       "Q 21  0.443286  0.388644  0.391105  ...  0.444209  0.574714  0.360072   \n",
       "Q 22  0.128798  0.587875  0.358712  ...  0.544182  0.233592  0.589565   \n",
       "Q 23  0.363229  0.084834  0.255400  ...  0.203536  0.613435  0.085401   \n",
       "Q 24  0.206253 -0.004484  0.176512  ...  0.122706  0.394023  0.063794   \n",
       "Q 25  0.187836  0.338182  0.290400  ...  0.302326  0.493779  0.291527   \n",
       "Q 26  0.239169  0.315536  0.319197  ...  0.450321  0.310568  0.205522   \n",
       "Q 27  0.356514  0.642071  0.411286  ...  1.000000  0.202714  0.434773   \n",
       "Q 28  0.448058  0.082524  0.375520  ...  0.202714  1.000000  0.117809   \n",
       "Q 29  0.071285  0.546009  0.064800  ...  0.434773  0.117809  1.000000   \n",
       "Q 30  0.290304  0.319898  0.295031  ...  0.344251  0.473585  0.247393   \n",
       "Q 31  0.389796  0.330892  0.468539  ...  0.480031  0.438350  0.321493   \n",
       "Q 32  0.391614  0.457684  0.307211  ...  0.483976  0.318174  0.442981   \n",
       "Q 33  0.441025  0.487169  0.443923  ...  0.597642  0.384442  0.573960   \n",
       "Q 34  0.499979  0.141105  0.447151  ...  0.206303  0.554824  0.233037   \n",
       "Q 35  0.316359  0.378409  0.286626  ...  0.473865  0.348581  0.481229   \n",
       "Q 36  0.351067  0.359018  0.319226  ...  0.435564  0.318435  0.376310   \n",
       "\n",
       "          Q 30      Q 31      Q 32      Q 33      Q 34      Q 35      Q 36  \n",
       "Q 1   0.239243  0.503735  0.353691  0.451214  0.133794  0.287450  0.295776  \n",
       "Q 2   0.381380  0.203405  0.367809  0.218704  0.171684  0.303920  0.320168  \n",
       "Q 3   0.439897  0.607603  0.520565  0.647261  0.465462  0.454006  0.450558  \n",
       "Q 4   0.518876  0.522054  0.448060  0.597286  0.541454  0.449094  0.482900  \n",
       "Q 5   0.438491  0.592683  0.582985  0.665871  0.384299  0.440640  0.421336  \n",
       "Q 6   0.508442  0.657301  0.464458  0.569817  0.571561  0.516192  0.498304  \n",
       "Q 7   0.335551  0.552608  0.372131  0.372525  0.439540  0.383394  0.318140  \n",
       "Q 8   0.290304  0.389796  0.391614  0.441025  0.499979  0.316359  0.351067  \n",
       "Q 9   0.319898  0.330892  0.457684  0.487169  0.141105  0.378409  0.359018  \n",
       "Q 10  0.295031  0.468539  0.307211  0.443923  0.447151  0.286626  0.319226  \n",
       "Q 11  0.138204  0.188098  0.078951  0.043536  0.293112  0.077306  0.119966  \n",
       "Q 12  0.086725  0.260195  0.137390  0.380688 -0.002908  0.109275  0.144195  \n",
       "Q 13  0.323174  0.287376  0.320871  0.352125  0.224569  0.138421  0.210523  \n",
       "Q 14  0.229977  0.237232  0.427916  0.296961  0.161410  0.240800  0.220581  \n",
       "Q 15  0.205928  0.395048  0.367299  0.469067  0.142692  0.294464  0.307636  \n",
       "Q 16  0.421833  0.549998  0.419746  0.434111  0.525296  0.358512  0.277313  \n",
       "Q 17  0.357654  0.599524  0.490145  0.499790  0.307287  0.253477  0.301171  \n",
       "Q 18  0.343589  0.630401  0.400510  0.415854  0.418966  0.381991  0.388221  \n",
       "Q 19  0.413245  0.433079  0.568993  0.425994  0.291376  0.327518  0.321281  \n",
       "Q 20  0.486199  0.230808  0.399269  0.333998  0.232783  0.384962  0.416951  \n",
       "Q 21  0.500443  0.418010  0.422712  0.579700  0.502213  0.417638  0.410642  \n",
       "Q 22  0.292790  0.310642  0.421417  0.540671  0.196931  0.360584  0.352849  \n",
       "Q 23  0.360153  0.330995  0.263420  0.260361  0.424391  0.236666  0.308776  \n",
       "Q 24  0.179300  0.220058  0.241250  0.108851  0.293458  0.101080  0.010201  \n",
       "Q 25  0.281040  0.284758  0.313350  0.403633  0.351413  0.274293  0.268039  \n",
       "Q 26  0.310030  0.247215  0.415799  0.341310  0.207189  0.388574  0.429327  \n",
       "Q 27  0.344251  0.480031  0.483976  0.597642  0.206303  0.473865  0.435564  \n",
       "Q 28  0.473585  0.438350  0.318174  0.384442  0.554824  0.348581  0.318435  \n",
       "Q 29  0.247393  0.321493  0.442981  0.573960  0.233037  0.481229  0.376310  \n",
       "Q 30  1.000000  0.349955  0.362550  0.371622  0.387877  0.443595  0.517715  \n",
       "Q 31  0.349955  1.000000  0.413797  0.576400  0.564796  0.329534  0.310442  \n",
       "Q 32  0.362550  0.413797  1.000000  0.582713  0.328180  0.510443  0.416973  \n",
       "Q 33  0.371622  0.576400  0.582713  1.000000  0.490884  0.620403  0.532142  \n",
       "Q 34  0.387877  0.564796  0.328180  0.490884  1.000000  0.475592  0.490727  \n",
       "Q 35  0.443595  0.329534  0.510443  0.620403  0.475592  1.000000  0.850720  \n",
       "Q 36  0.517715  0.310442  0.416973  0.532142  0.490727  0.850720  1.000000  \n",
       "\n",
       "[36 rows x 36 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_4.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "194a6732",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Eigenvalues</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14.135491</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.213459</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.442564</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.717121</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.441203</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.355351</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.145638</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.928956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.854214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.807336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.755456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.678577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.642457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.598047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.551852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.516600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.453386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.415351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.357611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.334968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.316505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.308779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.281389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.240561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.231403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.205281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.163089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.153715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.146088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.119226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.108767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.092097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.082079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.078193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.067588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.059602</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Eigenvalues\n",
       "0     14.135491\n",
       "1      3.213459\n",
       "2      2.442564\n",
       "3      1.717121\n",
       "4      1.441203\n",
       "5      1.355351\n",
       "6      1.145638\n",
       "7      0.928956\n",
       "8      0.854214\n",
       "9      0.807336\n",
       "10     0.755456\n",
       "11     0.678577\n",
       "12     0.642457\n",
       "13     0.598047\n",
       "14     0.551852\n",
       "15     0.516600\n",
       "16     0.453386\n",
       "17     0.415351\n",
       "18     0.357611\n",
       "19     0.334968\n",
       "20     0.316505\n",
       "21     0.308779\n",
       "22     0.281389\n",
       "23     0.240561\n",
       "24     0.231403\n",
       "25     0.205281\n",
       "26     0.163089\n",
       "27     0.153715\n",
       "28     0.146088\n",
       "29     0.119226\n",
       "30     0.108767\n",
       "31     0.092097\n",
       "32     0.082079\n",
       "33     0.078193\n",
       "34     0.067588\n",
       "35     0.059602"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The eigenvalues are calculated for the fourth cluster\n",
    "\n",
    "fa_3 = FactorAnalyzer(n_factors=3, rotation='oblimin').fit(cluster_4)\n",
    "fa_3.loadings_\n",
    "\n",
    "eigenvalues_2, _ = fa_3.get_eigenvalues()\n",
    "eigen_values_2 = list(eigenvalues_2)\n",
    "\n",
    "data_ev = pd.DataFrame(eigen_values_2,columns=['Eigenvalues'])\n",
    "\n",
    "data_ev\n",
    "\n",
    "# In this case, since the first 7 eigenvalues are greater than 1, the no. of factors is take to be 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "cdf558b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The factor loadings for the 7 Factors are presented in the form of a heatmap:\n",
    "\n",
    "fa_4 = FactorAnalyzer(n_factors=7, rotation='oblimin').fit(cluster_4)\n",
    "loadings_2 = fa_4.loadings_\n",
    "\n",
    "plt.figure(figsize=(12, 12)) \n",
    "sns.heatmap(loadings_2, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
    "plt.title('Heatmap of Factor Loadings')\n",
    "plt.xlabel('Factors')\n",
    "plt.ylabel('Variables')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "be2637d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.283135</td>\n",
       "      <td>0.318060</td>\n",
       "      <td>0.375586</td>\n",
       "      <td>0.300554</td>\n",
       "      <td>0.238707</td>\n",
       "      <td>0.235777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.283135</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.116738</td>\n",
       "      <td>0.298502</td>\n",
       "      <td>0.246074</td>\n",
       "      <td>0.084685</td>\n",
       "      <td>0.457021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.318060</td>\n",
       "      <td>0.116738</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.356141</td>\n",
       "      <td>0.096703</td>\n",
       "      <td>0.212280</td>\n",
       "      <td>0.267798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.375586</td>\n",
       "      <td>0.298502</td>\n",
       "      <td>0.356141</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.173159</td>\n",
       "      <td>0.114586</td>\n",
       "      <td>0.333810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.300554</td>\n",
       "      <td>0.246074</td>\n",
       "      <td>0.096703</td>\n",
       "      <td>0.173159</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.158443</td>\n",
       "      <td>0.209946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.238707</td>\n",
       "      <td>0.084685</td>\n",
       "      <td>0.212280</td>\n",
       "      <td>0.114586</td>\n",
       "      <td>0.158443</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.195101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.235777</td>\n",
       "      <td>0.457021</td>\n",
       "      <td>0.267798</td>\n",
       "      <td>0.333810</td>\n",
       "      <td>0.209946</td>\n",
       "      <td>0.195101</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6\n",
       "0  1.000000  0.283135  0.318060  0.375586  0.300554  0.238707  0.235777\n",
       "1  0.283135  1.000000  0.116738  0.298502  0.246074  0.084685  0.457021\n",
       "2  0.318060  0.116738  1.000000  0.356141  0.096703  0.212280  0.267798\n",
       "3  0.375586  0.298502  0.356141  1.000000  0.173159  0.114586  0.333810\n",
       "4  0.300554  0.246074  0.096703  0.173159  1.000000  0.158443  0.209946\n",
       "5  0.238707  0.084685  0.212280  0.114586  0.158443  1.000000  0.195101\n",
       "6  0.235777  0.457021  0.267798  0.333810  0.209946  0.195101  1.000000"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_mat_factors_4 = pd.DataFrame(fa_4.phi_)\n",
    "corr_mat_factors_4\n",
    "\n",
    "# The correlation matrix between the 9 Factors themselves:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "e247dde8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exporting to Excel\n",
    "\n",
    "corr_mat_factors_4.to_excel('FA4_KMedoids.xlsx')\n",
    "corr_mat_factors_3.to_excel('FA3_KMedoids.xlsx')"
   ]
  }
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