Project-code.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Librerias\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1010, 150)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Data\n",
    "df = pd.read_csv(\"responses.csv\")\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "MUSIC PREFERENCES (19) 0:19\n",
    "\n",
    "MOVIE PREFERENCES (12) 19:31\n",
    "\n",
    "HOBBIES & INTERESTS (32) 31:63\n",
    "\n",
    "PHOBIAS (10) 63:73\n",
    "\n",
    "HEALTH HABITS (3) 73:76\n",
    "\n",
    "PERSONALITY TRAITS, VIEWS ON LIFE & OPINIONS (57) 76:133\n",
    "\n",
    "SPENDING HABITS (7) 133:140\n",
    "\n",
    "DEMOGRAPHICS (10 ) 140:150\n",
    "\n",
    "We will take only: PERSONALITY TRAITS, VIEWS ON LIFE & OPINIONS (57) 76:133"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "      <th>Daily events</th>\n",
       "      <th>Prioritising workload</th>\n",
       "      <th>Writing notes</th>\n",
       "      <th>Workaholism</th>\n",
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       "   Daily events  Prioritising workload  Writing notes  Workaholism  \\\n",
       "0           2.0                    2.0            5.0          4.0   \n",
       "1           3.0                    2.0            4.0          5.0   \n",
       "2           1.0                    2.0            5.0          3.0   \n",
       "3           4.0                    4.0            4.0          5.0   \n",
       "4           3.0                    1.0            2.0          3.0   \n",
       "\n",
       "   Thinking ahead  Final judgement  Reliability  Keeping promises  \\\n",
       "0             2.0              5.0          4.0               4.0   \n",
       "1             4.0              1.0          4.0               4.0   \n",
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       "3             3.0              1.0          3.0               4.0   \n",
       "4             5.0              5.0          5.0               4.0   \n",
       "\n",
       "   Loss of interest  Friends versus money  ...  Happiness in life  \\\n",
       "0               1.0                   3.0  ...                4.0   \n",
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       "4               2.0                   3.0  ...                3.0   \n",
       "\n",
       "   Energy levels  Small - big dogs  Personality  Finding lost valuables  \\\n",
       "0            5.0               1.0          4.0                     3.0   \n",
       "1            3.0               5.0          3.0                     4.0   \n",
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       "3            2.0               1.0          2.0                     1.0   \n",
       "4            5.0               3.0          3.0                     2.0   \n",
       "\n",
       "   Getting up  Interests or hobbies  Parents' advice  Questionnaires or polls  \\\n",
       "0         2.0                   3.0              4.0                      3.0   \n",
       "1         5.0                   3.0              2.0                      3.0   \n",
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       "3         1.0                   NaN              2.0                      4.0   \n",
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       "\n",
       "    Internet usage  \n",
       "0  few hours a day  \n",
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       "3  most of the day  \n",
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       "\n",
       "[5 rows x 57 columns]"
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     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.iloc[:, 76:133]\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Prepare the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>864 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Daily events  Prioritising workload  Writing notes  Workaholism  \\\n",
       "0                1                      1              4            3   \n",
       "1                2                      1              3            4   \n",
       "2                0                      1              4            2   \n",
       "4                2                      0              1            2   \n",
       "5                1                      1              2            2   \n",
       "...            ...                    ...            ...          ...   \n",
       "1005             2                      1              0            3   \n",
       "1006             0                      2              0            4   \n",
       "1007             2                      0              0            0   \n",
       "1008             2                      0              4            0   \n",
       "1009             2                      4              3            4   \n",
       "\n",
       "      Thinking ahead  Final judgement  Reliability  Keeping promises  \\\n",
       "0                  1                4            3                 3   \n",
       "1                  3                0            3                 3   \n",
       "2                  4                2            3                 4   \n",
       "4                  4                4            4                 3   \n",
       "5                  2                0            2                 3   \n",
       "...              ...              ...          ...               ...   \n",
       "1005               1                2            2                 2   \n",
       "1006               4                4            4                 3   \n",
       "1007               3                0            2                 4   \n",
       "1008               2                3            3                 3   \n",
       "1009               3                2            4                 4   \n",
       "\n",
       "      Loss of interest  Friends versus money  ...  Happiness in life  \\\n",
       "0                    0                     2  ...                  3   \n",
       "1                    2                     3  ...                  3   \n",
       "2                    0                     4  ...                  3   \n",
       "4                    1                     2  ...                  2   \n",
       "5                    2                     1  ...                  2   \n",
       "...                ...                   ...  ...                ...   \n",
       "1005                 3                     3  ...                  3   \n",
       "1006                 0                     1  ...                  3   \n",
       "1007                 0                     3  ...                  2   \n",
       "1008                 4                     2  ...                  2   \n",
       "1009                 2                     3  ...                  3   \n",
       "\n",
       "      Energy levels  Small - big dogs  Personality  Finding lost valuables  \\\n",
       "0                 4                 0            3                       2   \n",
       "1                 2                 4            2                       3   \n",
       "2                 3                 2            2                       2   \n",
       "4                 4                 2            2                       1   \n",
       "5                 3                 3            2                       2   \n",
       "...             ...               ...          ...                     ...   \n",
       "1005              2                 2            2                       3   \n",
       "1006              3                 2            4                       2   \n",
       "1007              0                 2            1                       2   \n",
       "1008              1                 1            3                       0   \n",
       "1009              1                 2            3                       0   \n",
       "\n",
       "      Getting up  Interests or hobbies  Parents' advice  \\\n",
       "0              1                     2                3   \n",
       "1              4                     2                1   \n",
       "2              3                     4                2   \n",
       "4              3                     2                2   \n",
       "5              2                     4                2   \n",
       "...          ...                   ...              ...   \n",
       "1005           4                     3                3   \n",
       "1006           0                     2                3   \n",
       "1007           4                     0                3   \n",
       "1008           4                     2                2   \n",
       "1009           1                     1                2   \n",
       "\n",
       "      Questionnaires or polls  Internet usage  \n",
       "0                           2               0  \n",
       "1                           2               0  \n",
       "2                           0               0  \n",
       "4                           2               0  \n",
       "5                           3               0  \n",
       "...                       ...             ...  \n",
       "1005                        2               0  \n",
       "1006                        2               1  \n",
       "1007                        4               2  \n",
       "1008                        2               2  \n",
       "1009                        4               0  \n",
       "\n",
       "[864 rows x 57 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Drop NAs\n",
    "df = df.dropna()\n",
    "#...............................................................................................\n",
    "#Encode categorical data\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "df = df.apply(LabelEncoder().fit_transform)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Choose the factors "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: factor_analyzer in c:\\users\\dell\\anaconda3\\lib\\site-packages (0.3.2)\n",
      "Requirement already satisfied: pandas in c:\\users\\dell\\anaconda3\\lib\\site-packages (from factor_analyzer) (0.25.1)\n",
      "Requirement already satisfied: scipy in c:\\users\\dell\\anaconda3\\lib\\site-packages (from factor_analyzer) (1.3.1)\n",
      "Requirement already satisfied: numpy in c:\\users\\dell\\anaconda3\\lib\\site-packages (from factor_analyzer) (1.16.5)\n",
      "Requirement already satisfied: scikit-learn in c:\\users\\dell\\anaconda3\\lib\\site-packages (from factor_analyzer) (0.21.3)\n",
      "Requirement already satisfied: pytz>=2017.2 in c:\\users\\dell\\anaconda3\\lib\\site-packages (from pandas->factor_analyzer) (2019.3)\n",
      "Requirement already satisfied: python-dateutil>=2.6.1 in c:\\users\\dell\\anaconda3\\lib\\site-packages (from pandas->factor_analyzer) (2.8.0)\n",
      "Requirement already satisfied: joblib>=0.11 in c:\\users\\dell\\anaconda3\\lib\\site-packages (from scikit-learn->factor_analyzer) (0.13.2)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\dell\\anaconda3\\lib\\site-packages (from python-dateutil>=2.6.1->pandas->factor_analyzer) (1.12.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install factor_analyzer "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Try the model with all the variables \n",
    "from factor_analyzer import FactorAnalyzer         # pip install factor_analyzer \n",
    "fa = FactorAnalyzer(rotation=\"varimax\")\n",
    "fa.fit(df) \n",
    "\n",
    "# Check Eigenvalues\n",
    "ev, v = fa.get_eigenvalues()\n",
    "ev\n",
    "\n",
    "# Create scree plot using matplotlib\n",
    "plt.scatter(range(1,df.shape[1]+1),ev)\n",
    "plt.plot(range(1,df.shape[1]+1),ev)\n",
    "plt.title('Scree Plot')\n",
    "plt.xlabel('Factors')\n",
    "plt.ylabel('Eigenvalue')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display, Image\n",
    "display(Image(filename='Varimax.png'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see the most usefull factors for explain the data are between 5-6 until falling significantly.\n",
    "\n",
    "We will fit the model with 5 Factors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Daily events</td>\n",
       "      <td>0.250416</td>\n",
       "      <td>0.058953</td>\n",
       "      <td>0.206877</td>\n",
       "      <td>0.026094</td>\n",
       "      <td>0.028915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Prioritising workload</td>\n",
       "      <td>-0.012803</td>\n",
       "      <td>-0.150045</td>\n",
       "      <td>0.555946</td>\n",
       "      <td>0.078913</td>\n",
       "      <td>0.128156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Writing notes</td>\n",
       "      <td>-0.006039</td>\n",
       "      <td>-0.015927</td>\n",
       "      <td>0.420849</td>\n",
       "      <td>0.225307</td>\n",
       "      <td>0.261380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Workaholism</td>\n",
       "      <td>0.069524</td>\n",
       "      <td>0.029275</td>\n",
       "      <td>0.527082</td>\n",
       "      <td>0.088573</td>\n",
       "      <td>0.032979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Thinking ahead</td>\n",
       "      <td>0.023475</td>\n",
       "      <td>0.127909</td>\n",
       "      <td>0.530457</td>\n",
       "      <td>0.035213</td>\n",
       "      <td>0.055426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Final judgement</td>\n",
       "      <td>0.046188</td>\n",
       "      <td>0.112493</td>\n",
       "      <td>0.119861</td>\n",
       "      <td>0.381338</td>\n",
       "      <td>-0.039756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Reliability</td>\n",
       "      <td>0.061028</td>\n",
       "      <td>-0.102481</td>\n",
       "      <td>0.539373</td>\n",
       "      <td>0.073534</td>\n",
       "      <td>-0.003491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Keeping promises</td>\n",
       "      <td>0.053358</td>\n",
       "      <td>-0.034661</td>\n",
       "      <td>0.420538</td>\n",
       "      <td>0.121450</td>\n",
       "      <td>-0.033511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Loss of interest</td>\n",
       "      <td>0.273777</td>\n",
       "      <td>0.226286</td>\n",
       "      <td>0.003524</td>\n",
       "      <td>-0.149262</td>\n",
       "      <td>0.101882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Friends versus money</td>\n",
       "      <td>0.021279</td>\n",
       "      <td>-0.111839</td>\n",
       "      <td>0.022026</td>\n",
       "      <td>0.381357</td>\n",
       "      <td>-0.045824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Funniness</td>\n",
       "      <td>0.312861</td>\n",
       "      <td>0.131400</td>\n",
       "      <td>-0.043014</td>\n",
       "      <td>-0.018258</td>\n",
       "      <td>-0.026083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Fake</td>\n",
       "      <td>0.091188</td>\n",
       "      <td>0.469616</td>\n",
       "      <td>-0.024535</td>\n",
       "      <td>-0.191798</td>\n",
       "      <td>0.019356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Criminal damage</td>\n",
       "      <td>0.154868</td>\n",
       "      <td>0.177732</td>\n",
       "      <td>-0.112659</td>\n",
       "      <td>-0.240721</td>\n",
       "      <td>0.266761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Decision making</td>\n",
       "      <td>-0.287128</td>\n",
       "      <td>0.102033</td>\n",
       "      <td>0.267415</td>\n",
       "      <td>0.129336</td>\n",
       "      <td>0.158694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Elections</td>\n",
       "      <td>0.074306</td>\n",
       "      <td>-0.015585</td>\n",
       "      <td>0.222003</td>\n",
       "      <td>0.131404</td>\n",
       "      <td>-0.083563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Self-criticism</td>\n",
       "      <td>-0.016858</td>\n",
       "      <td>0.398420</td>\n",
       "      <td>0.229116</td>\n",
       "      <td>0.114144</td>\n",
       "      <td>0.069707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Judgment calls</td>\n",
       "      <td>0.182082</td>\n",
       "      <td>-0.010461</td>\n",
       "      <td>0.102263</td>\n",
       "      <td>0.035675</td>\n",
       "      <td>0.086474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Hypochondria</td>\n",
       "      <td>-0.040254</td>\n",
       "      <td>0.258913</td>\n",
       "      <td>-0.034874</td>\n",
       "      <td>0.042981</td>\n",
       "      <td>0.213548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Empathy</td>\n",
       "      <td>-0.050152</td>\n",
       "      <td>-0.073697</td>\n",
       "      <td>0.059441</td>\n",
       "      <td>0.324982</td>\n",
       "      <td>0.133754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Eating to survive</td>\n",
       "      <td>-0.010608</td>\n",
       "      <td>0.183045</td>\n",
       "      <td>0.003261</td>\n",
       "      <td>-0.015131</td>\n",
       "      <td>-0.018874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Giving</td>\n",
       "      <td>0.082276</td>\n",
       "      <td>-0.154549</td>\n",
       "      <td>0.112481</td>\n",
       "      <td>0.376723</td>\n",
       "      <td>0.234000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Compassion to animals</td>\n",
       "      <td>-0.083505</td>\n",
       "      <td>-0.002767</td>\n",
       "      <td>-0.010424</td>\n",
       "      <td>0.262183</td>\n",
       "      <td>0.192734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Borrowed stuff</td>\n",
       "      <td>-0.097017</td>\n",
       "      <td>-0.023047</td>\n",
       "      <td>0.323253</td>\n",
       "      <td>0.171017</td>\n",
       "      <td>0.071189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Loneliness</td>\n",
       "      <td>-0.199197</td>\n",
       "      <td>0.542350</td>\n",
       "      <td>-0.019272</td>\n",
       "      <td>0.045942</td>\n",
       "      <td>0.190369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Cheating in school</td>\n",
       "      <td>0.216223</td>\n",
       "      <td>-0.063183</td>\n",
       "      <td>-0.384634</td>\n",
       "      <td>-0.083940</td>\n",
       "      <td>0.208210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Health</td>\n",
       "      <td>-0.012267</td>\n",
       "      <td>0.027867</td>\n",
       "      <td>0.131645</td>\n",
       "      <td>0.184296</td>\n",
       "      <td>0.437826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Changing the past</td>\n",
       "      <td>-0.016622</td>\n",
       "      <td>0.482307</td>\n",
       "      <td>-0.161320</td>\n",
       "      <td>0.073843</td>\n",
       "      <td>0.159231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>God</td>\n",
       "      <td>0.047894</td>\n",
       "      <td>0.032281</td>\n",
       "      <td>0.027136</td>\n",
       "      <td>0.453873</td>\n",
       "      <td>-0.025963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Dreams</td>\n",
       "      <td>0.207076</td>\n",
       "      <td>-0.187723</td>\n",
       "      <td>0.078634</td>\n",
       "      <td>0.037709</td>\n",
       "      <td>-0.124853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Charity</td>\n",
       "      <td>0.163161</td>\n",
       "      <td>0.116834</td>\n",
       "      <td>0.156898</td>\n",
       "      <td>0.354953</td>\n",
       "      <td>-0.067795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Number of friends</td>\n",
       "      <td>0.514994</td>\n",
       "      <td>-0.321738</td>\n",
       "      <td>-0.086711</td>\n",
       "      <td>0.241070</td>\n",
       "      <td>-0.006859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Punctuality</td>\n",
       "      <td>0.004662</td>\n",
       "      <td>0.090531</td>\n",
       "      <td>-0.143569</td>\n",
       "      <td>0.069648</td>\n",
       "      <td>0.078111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Lying</td>\n",
       "      <td>-0.095933</td>\n",
       "      <td>-0.193370</td>\n",
       "      <td>0.001775</td>\n",
       "      <td>0.138092</td>\n",
       "      <td>0.006950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Waiting</td>\n",
       "      <td>0.032019</td>\n",
       "      <td>-0.067715</td>\n",
       "      <td>-0.000820</td>\n",
       "      <td>0.075966</td>\n",
       "      <td>-0.329606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>New environment</td>\n",
       "      <td>0.470076</td>\n",
       "      <td>-0.129745</td>\n",
       "      <td>-0.058912</td>\n",
       "      <td>0.005400</td>\n",
       "      <td>-0.230743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Mood swings</td>\n",
       "      <td>-0.086477</td>\n",
       "      <td>0.353226</td>\n",
       "      <td>-0.041005</td>\n",
       "      <td>0.031490</td>\n",
       "      <td>0.404388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Appearence and gestures</td>\n",
       "      <td>0.227246</td>\n",
       "      <td>-0.004762</td>\n",
       "      <td>0.105894</td>\n",
       "      <td>0.068825</td>\n",
       "      <td>0.303119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Socializing</td>\n",
       "      <td>0.537811</td>\n",
       "      <td>-0.096245</td>\n",
       "      <td>-0.048127</td>\n",
       "      <td>0.135323</td>\n",
       "      <td>-0.039204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Achievements</td>\n",
       "      <td>0.252835</td>\n",
       "      <td>0.048658</td>\n",
       "      <td>-0.042799</td>\n",
       "      <td>-0.082401</td>\n",
       "      <td>0.111902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Responding to a serious letter</td>\n",
       "      <td>-0.126985</td>\n",
       "      <td>0.087976</td>\n",
       "      <td>-0.026876</td>\n",
       "      <td>0.022940</td>\n",
       "      <td>0.013346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Children</td>\n",
       "      <td>0.079877</td>\n",
       "      <td>-0.134254</td>\n",
       "      <td>0.033040</td>\n",
       "      <td>0.440103</td>\n",
       "      <td>0.075663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Assertiveness</td>\n",
       "      <td>0.353462</td>\n",
       "      <td>-0.094372</td>\n",
       "      <td>0.002509</td>\n",
       "      <td>-0.067185</td>\n",
       "      <td>0.044117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Getting angry</td>\n",
       "      <td>0.051167</td>\n",
       "      <td>0.176922</td>\n",
       "      <td>-0.086069</td>\n",
       "      <td>-0.070837</td>\n",
       "      <td>0.532025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Knowing the right people</td>\n",
       "      <td>0.478657</td>\n",
       "      <td>0.022868</td>\n",
       "      <td>0.113503</td>\n",
       "      <td>-0.045359</td>\n",
       "      <td>0.227230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Public speaking</td>\n",
       "      <td>-0.385674</td>\n",
       "      <td>0.104662</td>\n",
       "      <td>0.069712</td>\n",
       "      <td>0.030447</td>\n",
       "      <td>0.190834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Unpopularity</td>\n",
       "      <td>-0.082146</td>\n",
       "      <td>0.229228</td>\n",
       "      <td>0.079173</td>\n",
       "      <td>0.241031</td>\n",
       "      <td>-0.031212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Life struggles</td>\n",
       "      <td>-0.226293</td>\n",
       "      <td>0.057892</td>\n",
       "      <td>-0.059615</td>\n",
       "      <td>0.384875</td>\n",
       "      <td>0.392060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Happiness in life</td>\n",
       "      <td>0.288585</td>\n",
       "      <td>-0.541050</td>\n",
       "      <td>0.158473</td>\n",
       "      <td>0.051235</td>\n",
       "      <td>-0.064525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Energy levels</td>\n",
       "      <td>0.499978</td>\n",
       "      <td>-0.478860</td>\n",
       "      <td>0.037918</td>\n",
       "      <td>0.122773</td>\n",
       "      <td>-0.025001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Small - big dogs</td>\n",
       "      <td>0.206696</td>\n",
       "      <td>0.040211</td>\n",
       "      <td>-0.143225</td>\n",
       "      <td>-0.203991</td>\n",
       "      <td>-0.131298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Personality</td>\n",
       "      <td>0.259646</td>\n",
       "      <td>-0.393197</td>\n",
       "      <td>0.064236</td>\n",
       "      <td>0.049013</td>\n",
       "      <td>-0.056988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Finding lost valuables</td>\n",
       "      <td>-0.127907</td>\n",
       "      <td>-0.011367</td>\n",
       "      <td>0.163354</td>\n",
       "      <td>0.391951</td>\n",
       "      <td>-0.101749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Getting up</td>\n",
       "      <td>0.012217</td>\n",
       "      <td>0.150551</td>\n",
       "      <td>-0.312297</td>\n",
       "      <td>0.082580</td>\n",
       "      <td>0.121198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Interests or hobbies</td>\n",
       "      <td>0.465627</td>\n",
       "      <td>-0.253289</td>\n",
       "      <td>0.065015</td>\n",
       "      <td>0.144827</td>\n",
       "      <td>-0.078694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Parents' advice</td>\n",
       "      <td>0.022594</td>\n",
       "      <td>-0.032871</td>\n",
       "      <td>0.243628</td>\n",
       "      <td>0.282252</td>\n",
       "      <td>0.113225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Questionnaires or polls</td>\n",
       "      <td>-0.045177</td>\n",
       "      <td>0.114865</td>\n",
       "      <td>0.154309</td>\n",
       "      <td>0.188501</td>\n",
       "      <td>-0.032532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Internet usage</td>\n",
       "      <td>-0.046077</td>\n",
       "      <td>0.075435</td>\n",
       "      <td>-0.007799</td>\n",
       "      <td>-0.081575</td>\n",
       "      <td>0.048144</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       0         1         2         3  \\\n",
       "Daily events                    0.250416  0.058953  0.206877  0.026094   \n",
       "Prioritising workload          -0.012803 -0.150045  0.555946  0.078913   \n",
       "Writing notes                  -0.006039 -0.015927  0.420849  0.225307   \n",
       "Workaholism                     0.069524  0.029275  0.527082  0.088573   \n",
       "Thinking ahead                  0.023475  0.127909  0.530457  0.035213   \n",
       "Final judgement                 0.046188  0.112493  0.119861  0.381338   \n",
       "Reliability                     0.061028 -0.102481  0.539373  0.073534   \n",
       "Keeping promises                0.053358 -0.034661  0.420538  0.121450   \n",
       "Loss of interest                0.273777  0.226286  0.003524 -0.149262   \n",
       "Friends versus money            0.021279 -0.111839  0.022026  0.381357   \n",
       "Funniness                       0.312861  0.131400 -0.043014 -0.018258   \n",
       "Fake                            0.091188  0.469616 -0.024535 -0.191798   \n",
       "Criminal damage                 0.154868  0.177732 -0.112659 -0.240721   \n",
       "Decision making                -0.287128  0.102033  0.267415  0.129336   \n",
       "Elections                       0.074306 -0.015585  0.222003  0.131404   \n",
       "Self-criticism                 -0.016858  0.398420  0.229116  0.114144   \n",
       "Judgment calls                  0.182082 -0.010461  0.102263  0.035675   \n",
       "Hypochondria                   -0.040254  0.258913 -0.034874  0.042981   \n",
       "Empathy                        -0.050152 -0.073697  0.059441  0.324982   \n",
       "Eating to survive              -0.010608  0.183045  0.003261 -0.015131   \n",
       "Giving                          0.082276 -0.154549  0.112481  0.376723   \n",
       "Compassion to animals          -0.083505 -0.002767 -0.010424  0.262183   \n",
       "Borrowed stuff                 -0.097017 -0.023047  0.323253  0.171017   \n",
       "Loneliness                     -0.199197  0.542350 -0.019272  0.045942   \n",
       "Cheating in school              0.216223 -0.063183 -0.384634 -0.083940   \n",
       "Health                         -0.012267  0.027867  0.131645  0.184296   \n",
       "Changing the past              -0.016622  0.482307 -0.161320  0.073843   \n",
       "God                             0.047894  0.032281  0.027136  0.453873   \n",
       "Dreams                          0.207076 -0.187723  0.078634  0.037709   \n",
       "Charity                         0.163161  0.116834  0.156898  0.354953   \n",
       "Number of friends               0.514994 -0.321738 -0.086711  0.241070   \n",
       "Punctuality                     0.004662  0.090531 -0.143569  0.069648   \n",
       "Lying                          -0.095933 -0.193370  0.001775  0.138092   \n",
       "Waiting                         0.032019 -0.067715 -0.000820  0.075966   \n",
       "New environment                 0.470076 -0.129745 -0.058912  0.005400   \n",
       "Mood swings                    -0.086477  0.353226 -0.041005  0.031490   \n",
       "Appearence and gestures         0.227246 -0.004762  0.105894  0.068825   \n",
       "Socializing                     0.537811 -0.096245 -0.048127  0.135323   \n",
       "Achievements                    0.252835  0.048658 -0.042799 -0.082401   \n",
       "Responding to a serious letter -0.126985  0.087976 -0.026876  0.022940   \n",
       "Children                        0.079877 -0.134254  0.033040  0.440103   \n",
       "Assertiveness                   0.353462 -0.094372  0.002509 -0.067185   \n",
       "Getting angry                   0.051167  0.176922 -0.086069 -0.070837   \n",
       "Knowing the right people        0.478657  0.022868  0.113503 -0.045359   \n",
       "Public speaking                -0.385674  0.104662  0.069712  0.030447   \n",
       "Unpopularity                   -0.082146  0.229228  0.079173  0.241031   \n",
       "Life struggles                 -0.226293  0.057892 -0.059615  0.384875   \n",
       "Happiness in life               0.288585 -0.541050  0.158473  0.051235   \n",
       "Energy levels                   0.499978 -0.478860  0.037918  0.122773   \n",
       "Small - big dogs                0.206696  0.040211 -0.143225 -0.203991   \n",
       "Personality                     0.259646 -0.393197  0.064236  0.049013   \n",
       "Finding lost valuables         -0.127907 -0.011367  0.163354  0.391951   \n",
       "Getting up                      0.012217  0.150551 -0.312297  0.082580   \n",
       "Interests or hobbies            0.465627 -0.253289  0.065015  0.144827   \n",
       "Parents' advice                 0.022594 -0.032871  0.243628  0.282252   \n",
       "Questionnaires or polls        -0.045177  0.114865  0.154309  0.188501   \n",
       "Internet usage                 -0.046077  0.075435 -0.007799 -0.081575   \n",
       "\n",
       "                                       4  \n",
       "Daily events                    0.028915  \n",
       "Prioritising workload           0.128156  \n",
       "Writing notes                   0.261380  \n",
       "Workaholism                     0.032979  \n",
       "Thinking ahead                  0.055426  \n",
       "Final judgement                -0.039756  \n",
       "Reliability                    -0.003491  \n",
       "Keeping promises               -0.033511  \n",
       "Loss of interest                0.101882  \n",
       "Friends versus money           -0.045824  \n",
       "Funniness                      -0.026083  \n",
       "Fake                            0.019356  \n",
       "Criminal damage                 0.266761  \n",
       "Decision making                 0.158694  \n",
       "Elections                      -0.083563  \n",
       "Self-criticism                  0.069707  \n",
       "Judgment calls                  0.086474  \n",
       "Hypochondria                    0.213548  \n",
       "Empathy                         0.133754  \n",
       "Eating to survive              -0.018874  \n",
       "Giving                          0.234000  \n",
       "Compassion to animals           0.192734  \n",
       "Borrowed stuff                  0.071189  \n",
       "Loneliness                      0.190369  \n",
       "Cheating in school              0.208210  \n",
       "Health                          0.437826  \n",
       "Changing the past               0.159231  \n",
       "God                            -0.025963  \n",
       "Dreams                         -0.124853  \n",
       "Charity                        -0.067795  \n",
       "Number of friends              -0.006859  \n",
       "Punctuality                     0.078111  \n",
       "Lying                           0.006950  \n",
       "Waiting                        -0.329606  \n",
       "New environment                -0.230743  \n",
       "Mood swings                     0.404388  \n",
       "Appearence and gestures         0.303119  \n",
       "Socializing                    -0.039204  \n",
       "Achievements                    0.111902  \n",
       "Responding to a serious letter  0.013346  \n",
       "Children                        0.075663  \n",
       "Assertiveness                   0.044117  \n",
       "Getting angry                   0.532025  \n",
       "Knowing the right people        0.227230  \n",
       "Public speaking                 0.190834  \n",
       "Unpopularity                   -0.031212  \n",
       "Life struggles                  0.392060  \n",
       "Happiness in life              -0.064525  \n",
       "Energy levels                  -0.025001  \n",
       "Small - big dogs               -0.131298  \n",
       "Personality                    -0.056988  \n",
       "Finding lost valuables         -0.101749  \n",
       "Getting up                      0.121198  \n",
       "Interests or hobbies           -0.078694  \n",
       "Parents' advice                 0.113225  \n",
       "Questionnaires or polls        -0.032532  \n",
       "Internet usage                  0.048144  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Factor analysis with 5 fators\n",
    "fa = FactorAnalyzer(5, rotation=\"varimax\")\n",
    "fa.fit(df)\n",
    "AF = fa.loadings_\n",
    "AF = pd.DataFrame(AF)\n",
    "AF.index = df.columns\n",
    "AF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FACTOR</th>\n",
       "      <th>Variable</th>\n",
       "      <th>Varianza_Explica</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>New environment</td>\n",
       "      <td>0.470076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Energy levels</td>\n",
       "      <td>0.499978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>Number of friends</td>\n",
       "      <td>0.514994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>Socializing</td>\n",
       "      <td>0.537811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Knowing the right people</td>\n",
       "      <td>0.478657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>Mood swings</td>\n",
       "      <td>0.353226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>Self-criticism</td>\n",
       "      <td>0.398420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>Fake</td>\n",
       "      <td>0.469616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Changing the past</td>\n",
       "      <td>0.482307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>Loneliness</td>\n",
       "      <td>0.542350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>Writing notes</td>\n",
       "      <td>0.420849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>Workaholism</td>\n",
       "      <td>0.527082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>Thinking ahead</td>\n",
       "      <td>0.530457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>Prioritising workload</td>\n",
       "      <td>0.555946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>Reliability</td>\n",
       "      <td>0.539373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>Friends versus money</td>\n",
       "      <td>0.381357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "      <td>Life struggles</td>\n",
       "      <td>0.384875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>Finding lost valuables</td>\n",
       "      <td>0.391951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>Children</td>\n",
       "      <td>0.440103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>3</td>\n",
       "      <td>God</td>\n",
       "      <td>0.453873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>Appearence and gestures</td>\n",
       "      <td>0.303119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>Life struggles</td>\n",
       "      <td>0.392060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>4</td>\n",
       "      <td>Mood swings</td>\n",
       "      <td>0.404388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>Health</td>\n",
       "      <td>0.437826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>Getting angry</td>\n",
       "      <td>0.532025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    FACTOR                  Variable  Varianza_Explica\n",
       "0        0           New environment          0.470076\n",
       "1        0             Energy levels          0.499978\n",
       "2        0         Number of friends          0.514994\n",
       "3        0               Socializing          0.537811\n",
       "4        0  Knowing the right people          0.478657\n",
       "5        1               Mood swings          0.353226\n",
       "6        1            Self-criticism          0.398420\n",
       "7        1                      Fake          0.469616\n",
       "8        1         Changing the past          0.482307\n",
       "9        1                Loneliness          0.542350\n",
       "10       2             Writing notes          0.420849\n",
       "11       2               Workaholism          0.527082\n",
       "12       2            Thinking ahead          0.530457\n",
       "13       2     Prioritising workload          0.555946\n",
       "14       2               Reliability          0.539373\n",
       "15       3      Friends versus money          0.381357\n",
       "16       3            Life struggles          0.384875\n",
       "17       3    Finding lost valuables          0.391951\n",
       "18       3                  Children          0.440103\n",
       "19       3                       God          0.453873\n",
       "20       4   Appearence and gestures          0.303119\n",
       "21       4            Life struggles          0.392060\n",
       "22       4               Mood swings          0.404388\n",
       "23       4                    Health          0.437826\n",
       "24       4             Getting angry          0.532025"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Get Top variables for each Factor \n",
    "F = AF.unstack()\n",
    "F = pd.DataFrame(F).reset_index()\n",
    "F = F.sort_values(['level_0',0], ascending=False).groupby('level_0').head(5)    # Top 5 \n",
    "F = F.sort_values(by=\"level_0\")\n",
    "F.columns=[\"FACTOR\",\"Variable\",\"Varianza_Explica\"]\n",
    "F = F.reset_index().drop([\"index\"],axis=1)\n",
    "F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>FACTOR</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>New environment</td>\n",
       "      <td>Mood swings</td>\n",
       "      <td>Writing notes</td>\n",
       "      <td>Friends versus money</td>\n",
       "      <td>Appearence and gestures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Energy levels</td>\n",
       "      <td>Self-criticism</td>\n",
       "      <td>Workaholism</td>\n",
       "      <td>Life struggles</td>\n",
       "      <td>Life struggles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Number of friends</td>\n",
       "      <td>Fake</td>\n",
       "      <td>Thinking ahead</td>\n",
       "      <td>Finding lost valuables</td>\n",
       "      <td>Mood swings</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Socializing</td>\n",
       "      <td>Changing the past</td>\n",
       "      <td>Prioritising workload</td>\n",
       "      <td>Children</td>\n",
       "      <td>Health</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Knowing the right people</td>\n",
       "      <td>Loneliness</td>\n",
       "      <td>Reliability</td>\n",
       "      <td>God</td>\n",
       "      <td>Getting angry</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "FACTOR                         0                  1                      2  \\\n",
       "0                New environment        Mood swings          Writing notes   \n",
       "1                  Energy levels     Self-criticism            Workaholism   \n",
       "2              Number of friends               Fake         Thinking ahead   \n",
       "3                    Socializing  Changing the past  Prioritising workload   \n",
       "4       Knowing the right people         Loneliness            Reliability   \n",
       "\n",
       "FACTOR                       3                        4  \n",
       "0         Friends versus money  Appearence and gestures  \n",
       "1               Life struggles           Life struggles  \n",
       "2       Finding lost valuables              Mood swings  \n",
       "3                     Children                   Health  \n",
       "4                          God            Getting angry  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Show the Top for each Factor \n",
    "F = F.pivot(columns='FACTOR')[\"Variable\"]\n",
    "F.apply(lambda x: pd.Series(x.dropna().to_numpy()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FACTOR 1: Energy levels, Number of friends, Socializing...\n",
    "\n",
    "Could be: Extraversion\n",
    "\n",
    "FACTOR 2: Self-ciricism, Fake, Loneliness...\n",
    "\n",
    "Looks very similar to \"Neuroticism\"\n",
    "\n",
    "Factor 3: Thinking ahead, Prioritising workload...\n",
    "\n",
    "very similar to \"Conscientiousness\"\n",
    "\n",
    "Factor 4: Children, God, Finding lost valuables\n",
    "\n",
    "This factor could be something like \"religious\" or \"conservative\", maybe have lowest scores of a \"Openness\" in Big Five model.\n",
    "\n",
    "Factor 5: Appearence and gestures, Mood swings\n",
    "\n",
    "Mmmm it could be \"Agreeableness\". What do you think it could be represent?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first three Factors are very clear: Extraversion, Neuroticism and Conscientiousness. The other two not to much. Anyway is a very interesting approximation\n",
    "\n",
    "Maybe doing first a PCA for remove hight correlate variables like \"God\" and \"Final judgement\"could help.\n",
    "\n",
    "What do you think?\n",
    "\n",
    "Thanks you!"
   ]
  }
 ],
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