2_processing/1_personality_score_calculation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extract personality traits from Onboarding survey\n",
    " - Author: Mario Frei, 2024"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "7-_NLLA-5S-U"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import seaborn as sns\n",
    "import math\n",
    "import pandas as pd\n",
    "\n",
    "#import plotly.express as px\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly.graph_objects as go"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Configurations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "onboarding_survey_path = '../1_data/1_onboarding_survey_all_participants.csv'\n",
    "weekly_survey_path = '../1_data/2_weekly_survey_data_all_participants.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parse data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "vIuv-6u06buP"
   },
   "outputs": [],
   "source": [
    "# Read data\n",
    "df = pd.read_csv(onboarding_survey_path)\n",
    "\n",
    "#  Rename participant ID column\n",
    "df['id_participant'] = df['Experiment tag (for example orenth04, provided by the researcher)'].str.lower()\n",
    "df = df.drop(columns=['Experiment tag (for example orenth04, provided by the researcher)'])\n",
    "\n",
    "# Clean up participant ID values\n",
    "df['id_participant'] = df['id_participant'].str.replace(' ', '')\n",
    "df['id_participant'] = df['id_participant'].str.replace('\\n', '')\n",
    "\n",
    "df = df.set_index('id_participant', drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Big Five personality traits\n",
    "- Sources:\n",
    "  - https://gosling.psy.utexas.edu/wp-content/uploads/2014/09/tipi.pdf\n",
    "  - https://gosling.psy.utexas.edu/scales-weve-developed/ten-item-personality-measure-tipi/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mario\\AppData\\Local\\Temp\\ipykernel_1924\\2069624797.py:27: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "  df_5 = df_5.replace(map)\n"
     ]
    },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Extraverted, enthusiastic</th>\n",
       "      <th>Critical, quarrelsome</th>\n",
       "      <th>Dependable, self-disciplined</th>\n",
       "      <th>Anxious, easily upset</th>\n",
       "      <th>Open to new experience, complex</th>\n",
       "      <th>Reserved, quiet</th>\n",
       "      <th>Sympathetic, warm</th>\n",
       "      <th>Disorganized, careless</th>\n",
       "      <th>Calm, emotionally stable</th>\n",
       "      <th>Conventional, unreactive</th>\n",
       "      <th>Extraversion</th>\n",
       "      <th>Agreeableness</th>\n",
       "      <th>Conscientiousness</th>\n",
       "      <th>Emotional Stability</th>\n",
       "      <th>Openness to Experience</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id_participant</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>orenth01</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>3.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth02</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth03</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth04</th>\n",
       "      <td>3</td>\n",
       "      <td>2</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",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth05</th>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "                Extraverted, enthusiastic  Critical, quarrelsome  \\\n",
       "id_participant                                                     \n",
       "orenth01                                4                      2   \n",
       "orenth02                                7                      6   \n",
       "orenth03                                2                      3   \n",
       "orenth04                                3                      2   \n",
       "orenth05                                4                      3   \n",
       "\n",
       "                Dependable, self-disciplined  Anxious, easily upset  \\\n",
       "id_participant                                                        \n",
       "orenth01                                   3                      3   \n",
       "orenth02                                   4                      3   \n",
       "orenth03                                   3                      6   \n",
       "orenth04                                   5                      5   \n",
       "orenth05                                   5                      5   \n",
       "\n",
       "                Open to new experience, complex  Reserved, quiet  \\\n",
       "id_participant                                                     \n",
       "orenth01                                      5                5   \n",
       "orenth02                                      6                6   \n",
       "orenth03                                      4                6   \n",
       "orenth04                                      5                5   \n",
       "orenth05                                      5                4   \n",
       "\n",
       "                Sympathetic, warm  Disorganized, careless  \\\n",
       "id_participant                                              \n",
       "orenth01                        6                       5   \n",
       "orenth02                        5                       2   \n",
       "orenth03                        6                       5   \n",
       "orenth04                        5                       5   \n",
       "orenth05                        4                       5   \n",
       "\n",
       "                Calm, emotionally stable  Conventional, unreactive  \\\n",
       "id_participant                                                       \n",
       "orenth01                               6                         7   \n",
       "orenth02                               6                         6   \n",
       "orenth03                               3                         3   \n",
       "orenth04                               3                         4   \n",
       "orenth05                               5                         4   \n",
       "\n",
       "                Extraversion  Agreeableness  Conscientiousness  \\\n",
       "id_participant                                                   \n",
       "orenth01                 3.5            6.0                3.0   \n",
       "orenth02                 4.5            3.5                5.0   \n",
       "orenth03                 2.0            5.5                3.0   \n",
       "orenth04                 3.0            5.5                4.0   \n",
       "orenth05                 4.0            4.5                4.0   \n",
       "\n",
       "                Emotional Stability  Openness to Experience  \n",
       "id_participant                                               \n",
       "orenth01                        5.5                     3.0  \n",
       "orenth02                        5.5                     4.0  \n",
       "orenth03                        2.5                     4.5  \n",
       "orenth04                        3.0                     4.5  \n",
       "orenth05                        4.0                     4.5  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select columns for Big Five\n",
    "columns_big_five =[\n",
    "    'Extraverted, enthusiastic', \n",
    "    'Critical, quarrelsome',\n",
    "    'Dependable, self-disciplined', \n",
    "    'Anxious, easily upset',\n",
    "    'Open to new experience, complex', \n",
    "    'Reserved, quiet',\n",
    "    'Sympathetic, warm', \n",
    "    'Disorganized, careless',\n",
    "    'Calm, emotionally stable', \n",
    "    'Conventional, unreactive'\n",
    "]\n",
    "df_5 = df[columns_big_five]\n",
    "\n",
    "# Map responses from string scale to integer scale\n",
    "map ={\n",
    "    'Strongly disagree': 1,\n",
    "    'Disagree': 2,\n",
    "    'Somewhat disagree': 3,\n",
    "    'Neither agree nor disagree': 4,\n",
    "    'Somewhat agree': 5,\n",
    "    'Agree': 6,\n",
    "    'Strongly agree': 7\n",
    "}\n",
    "\n",
    "df_5 = df_5.replace(map)\n",
    "\n",
    "# Compute Big Five personality traits\n",
    "df_5['Extraversion'] = (df_5['Extraverted, enthusiastic'] + (8 - df_5['Reserved, quiet'])) / 2\n",
    "df_5['Agreeableness'] = (df_5['Sympathetic, warm'] + (8 - df_5['Critical, quarrelsome'])) / 2\n",
    "df_5['Conscientiousness'] = (df_5['Dependable, self-disciplined'] + (8 - df_5['Disorganized, careless'])) / 2\n",
    "df_5['Emotional Stability'] = (df_5['Calm, emotionally stable'] + (8 - df_5['Anxious, easily upset'])) / 2\n",
    "df_5['Openness to Experience'] = (df_5['Open to new experience, complex'] + (8 - df_5['Conventional, unreactive'])) / 2\n",
    "\n",
    "# Show results\n",
    "df_5.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Highly Sensitive Person Scale (HSP-12)\n",
    "- Sources:\n",
    "    - https://sensitivityresearch.com/self-tests/adult-self-test/\n",
    "    - https://www.sciencedirect.com/science/article/pii/S0092656623000399\n",
    "    - https://psycnet.apa.org/buy/1997-05290-010\n",
    "- Sensitivity: \n",
    "    - Low: 1-4\n",
    "    - Medium:4-4.5\n",
    "    - High: 4.5-7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sensitivity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id_participant</th>\n",
       "      <th></th>\n",
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       "      <th>orenth01</th>\n",
       "      <td>4.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth02</th>\n",
       "      <td>4.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth03</th>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth04</th>\n",
       "      <td>5.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth05</th>\n",
       "      <td>4.333333</td>\n",
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       "      <th>orenth06</th>\n",
       "      <td>3.75</td>\n",
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       "      <th>orenth07</th>\n",
       "      <td>5.166667</td>\n",
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       "    <tr>\n",
       "      <th>orenth08</th>\n",
       "      <td>4.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth09</th>\n",
       "      <td>5.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth11</th>\n",
       "      <td>3.5</td>\n",
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      "text/plain": [
       "               sensitivity\n",
       "id_participant            \n",
       "orenth01              4.25\n",
       "orenth02          4.666667\n",
       "orenth03               4.5\n",
       "orenth04              5.25\n",
       "orenth05          4.333333\n",
       "orenth06              3.75\n",
       "orenth07          5.166667\n",
       "orenth08          4.583333\n",
       "orenth09          5.333333\n",
       "orenth11               3.5"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select columns for Sensitivity\n",
    "columns_sensitivity = [\n",
    "    'Do you seem to be aware of subtleties in your environment?',\n",
    "    'Are you easily overwhelmed by things like bright lights, strong smells, coarse fabrics, or sirens close by?',\n",
    "    'Do you have a rich, complex inner life?',\n",
    "    'Do you get rattled when you have a lot to do in a short amount of time?',\n",
    "    'Are you deeply moved by the arts or music?',\n",
    "    'Are you annoyed when people try to get you to do too many things at once?',\n",
    "    'Do you make a point to avoid violent movies and TV shows?',\n",
    "    'Do you find it unpleasant to have a lot going on at once?',\n",
    "    'Do changes in your life shake you up?',\n",
    "    'Do you notice and enjoy delicate or fine scents, tastes, sounds, works of art?',\n",
    "    'Are you bothered by intense stimuli, like loud noises or chaotic scenes?',\n",
    "    'When you must compete or be observed while performing a task, do you become so nervous or shaky that you do much worse than you would otherwise?'\n",
    "    ]\n",
    "df_s = df[columns_sensitivity]\n",
    "\n",
    "# Remove strings from responses\n",
    "df_s= df_s.replace({'7 (Extremely)': 7, '1 (Not at All)': 1, '1  (Not at All)': 1, '1  (Not at all)':1})\n",
    "df_s.loc[:,columns_sensitivity] = df_s.loc[:,columns_sensitivity].astype(int)                                                  \n",
    "\n",
    "# Compute sensitivity score\n",
    "df_s['sensitivity']= df_s.loc[:,columns_sensitivity].mean(axis=1)\n",
    "\n",
    "# Show result\n",
    "df_s[['sensitivity']].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Satisfaction with life (SWLS)\n",
    "- Sources:\n",
    "    - https://labs.psychology.illinois.edu/~ediener/SWLS.html\n",
    "    - https://positivepsychology.com/life-satisfaction-scales/\n",
    "- Scores:\n",
    "    - 30 – 35 Very high score; highly satisfied \n",
    "    - 25 - 29 High score \n",
    "    - 20 – 24 Average score \n",
    "    - 15 – 19 Slightly below average in life satisfaction \n",
    "    - 10 – 14 Dissatisfied\n",
    "    -  5 -  9 Exremely dissatisfied"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mario\\AppData\\Local\\Temp\\ipykernel_1924\\827251819.py:20: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "  df_swls= df_swls.replace(map)\n"
     ]
    },
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       "      <th></th>\n",
       "      <th>In most ways my life is close to my ideal.</th>\n",
       "      <th>The conditions of my life are excellent.</th>\n",
       "      <th>I am satisfied with my life.</th>\n",
       "      <th>So far I have gotten the important things I want in life.</th>\n",
       "      <th>If I could live my life over, I would change almost nothing.</th>\n",
       "      <th>swls</th>\n",
       "      <th>swls_str</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id_participant</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>orenth01</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>22</td>\n",
       "      <td>Average score</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth02</th>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>26</td>\n",
       "      <td>High score</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth03</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>Average score</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth04</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>Slightly below average in life satisfaction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth05</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>24</td>\n",
       "      <td>Average score</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                In most ways my life is close to my ideal.  \\\n",
       "id_participant                                               \n",
       "orenth01                                                 4   \n",
       "orenth02                                                 6   \n",
       "orenth03                                                 3   \n",
       "orenth04                                                 3   \n",
       "orenth05                                                 5   \n",
       "\n",
       "               The conditions of my life are excellent.  \\\n",
       "id_participant                                            \n",
       "orenth01                                              5   \n",
       "orenth02                                              5   \n",
       "orenth03                                              4   \n",
       "orenth04                                              5   \n",
       "orenth05                                              5   \n",
       "\n",
       "                I am satisfied with my life.  \\\n",
       "id_participant                                 \n",
       "orenth01                                   5   \n",
       "orenth02                                   6   \n",
       "orenth03                                   5   \n",
       "orenth04                                   4   \n",
       "orenth05                                   5   \n",
       "\n",
       "                So far I have gotten the important things I want in life.  \\\n",
       "id_participant                                                              \n",
       "orenth01                                                        3           \n",
       "orenth02                                                        2           \n",
       "orenth03                                                        5           \n",
       "orenth04                                                        4           \n",
       "orenth05                                                        5           \n",
       "\n",
       "                If I could live my life over, I would change almost nothing.  \\\n",
       "id_participant                                                                 \n",
       "orenth01                                                        5              \n",
       "orenth02                                                        7              \n",
       "orenth03                                                        3              \n",
       "orenth04                                                        2              \n",
       "orenth05                                                        4              \n",
       "\n",
       "               swls                                     swls_str  \n",
       "id_participant                                                    \n",
       "orenth01         22                                Average score  \n",
       "orenth02         26                                   High score  \n",
       "orenth03         20                                Average score  \n",
       "orenth04         18  Slightly below average in life satisfaction  \n",
       "orenth05         24                                Average score  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select relevant columns for Satisfaction with life score\n",
    "columns_swls = [\n",
    "    'In most ways my life is close to my ideal.',\n",
    "    'The conditions of my life are excellent.',\n",
    "    'I am satisfied with my life.',\n",
    "    'So far I have gotten the important things I want in life.',\n",
    "    'If I could live my life over, I would change almost nothing.']\n",
    "df_swls = df[columns_swls]\n",
    "\n",
    "# Convert responses from string scale to integer scale\n",
    "map = {\n",
    "    'Strongly disagree': 1, \n",
    "    'Disagree': 2,\n",
    "    'Somewhat disagree': 3,\n",
    "    'Neither agree nor disagree': 4, \n",
    "    'Somewhat agree': 5, \n",
    "    'Agree': 6, \n",
    "    'Strongly agree': 7\n",
    "    }\n",
    "df_swls= df_swls.replace(map)\n",
    "df_swls.loc[:,columns_swls] = df_swls.loc[:,columns_swls].astype(int)\n",
    "\n",
    "# Compute Satisfaction with life score\n",
    "df_swls['swls'] = df_swls.loc[:,columns_swls].sum(axis=1)\n",
    "df_swls['swls_str'] = df_swls['swls'].apply(lambda x: 'Extremely Dissatisfied' if x <= 9 else \n",
    "                                                      'Dissatisfied' if x <= 14 else \n",
    "                                                      'Slightly below average in life satisfaction' if x <= 19 else\n",
    "                                                      'Average score' if x <= 24 else\n",
    "                                                      'High score' if x <= 29 else\n",
    "                                                      'HIghly satisfied')\n",
    "\n",
    "# Show result\n",
    "df_swls.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Consolidate scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Extraversion</th>\n",
       "      <th>Agreeableness</th>\n",
       "      <th>Conscientiousness</th>\n",
       "      <th>Emotional Stability</th>\n",
       "      <th>Openness to Experience</th>\n",
       "      <th>swls</th>\n",
       "      <th>sensitivity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id_participant</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>orenth01</th>\n",
       "      <td>3.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22</td>\n",
       "      <td>4.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth02</th>\n",
       "      <td>4.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>26</td>\n",
       "      <td>4.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth03</th>\n",
       "      <td>2.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>20</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth04</th>\n",
       "      <td>3.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>18</td>\n",
       "      <td>5.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orenth05</th>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>24</td>\n",
       "      <td>4.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Extraversion  Agreeableness  Conscientiousness  \\\n",
       "id_participant                                                   \n",
       "orenth01                 3.5            6.0                3.0   \n",
       "orenth02                 4.5            3.5                5.0   \n",
       "orenth03                 2.0            5.5                3.0   \n",
       "orenth04                 3.0            5.5                4.0   \n",
       "orenth05                 4.0            4.5                4.0   \n",
       "\n",
       "                Emotional Stability  Openness to Experience swls sensitivity  \n",
       "id_participant                                                                \n",
       "orenth01                        5.5                     3.0   22        4.25  \n",
       "orenth02                        5.5                     4.0   26    4.666667  \n",
       "orenth03                        2.5                     4.5   20         4.5  \n",
       "orenth04                        3.0                     4.5   18        5.25  \n",
       "orenth05                        4.0                     4.5   24    4.333333  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Consolidate all scores\n",
    "df_all = pd.DataFrame(index=df.index)\n",
    "\n",
    "df_all.loc[:, ['Extraversion', 'Agreeableness', 'Conscientiousness', 'Emotional Stability', 'Openness to Experience']] = df_5[['Extraversion', 'Agreeableness', 'Conscientiousness', 'Emotional Stability', 'Openness to Experience']]\n",
    "df_all.loc[:,'swls'] = df_swls['swls']\n",
    "#df_all.loc[:, 'swls_str'] = df_swls['swls_str']\n",
    "df_all.loc[:, 'sensitivity'] = df_s['sensitivity']\n",
    "\n",
    "df_all.to_csv('./3_all_personality_scores.csv')\n",
    "df_all.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merge all scores with weekly survey\n",
    "df_weekly = pd.read_csv(weekly_survey_path)\n",
    "df_weekly['Extraversion'] = df_weekly['id_participant'].map(df_all['Extraversion'])\n",
    "df_weekly['Agreeableness'] = df_weekly['id_participant'].map(df_all['Agreeableness'])\n",
    "df_weekly['Conscientiousness'] = df_weekly['id_participant'].map(df_all['Conscientiousness'])\n",
    "df_weekly['Emotional Stability'] = df_weekly['id_participant'].map(df_all['Emotional Stability'])\n",
    "df_weekly['Openness to Experience'] = df_weekly['id_participant'].map(df_all['Openness to Experience'])\n",
    "df_weekly['swls'] = df_weekly['id_participant'].map(df_all['swls'])\n",
    "df_weekly['sensitivity'] = df_weekly['id_participant'].map(df_all['sensitivity'])\n",
    "df_weekly.head()\n",
    "\n",
    "df_weekly.to_csv('./4_weekly_survey_with_personality.csv', index=False)"
   ]
  }
 ],
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