pandas_transform_google_form_data2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# read and transform Google Form data (checkboxes, multiple choice grid items)\n",
    "* Google Form: https://forms.gle/7a35kfYmzyJJb5GD9\n",
    "* Google Sheets: https://docs.google.com/spreadsheets/d/1W0EaP8WGWaOK8XYDQA3Z4HIZaOQXXYj6U6kzqMuVrUI/edit#gid=1695829581"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "* author:  [Prasert Kanawattanachai](prasert.k@chula.ac.th)\n",
    "* YouTube: https://www.youtube.com/prasertcbs\n",
    "* github: https://github.com/prasertcbs/\n",
    "* [Chulalongkorn Business School](https://www.cbs.chula.ac.th/en/)\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pandas version: 1.2.1\n",
      "numpy  version: 1.19.2\n",
      "2021-02-20 09:20:15.132975\n"
     ]
    }
   ],
   "source": [
    "print(f'pandas version: {pd.__version__}')\n",
    "print(f'numpy  version: {np.__version__}')\n",
    "print(pd.Timestamp.now())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        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>Timestamp</th>\n",
       "      <th>gender</th>\n",
       "      <th>age (years)</th>\n",
       "      <th>skills</th>\n",
       "      <th>satisfaction [product]</th>\n",
       "      <th>satisfaction [price]</th>\n",
       "      <th>satisfaction [service]</th>\n",
       "      <th>satisfaction [overall]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-02-19 22:36:35.982</td>\n",
       "      <td>Male</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Word, Excel, PowerPoint, Access</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-02-19 22:38:17.913</td>\n",
       "      <td>Male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Excel, SQL</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-02-19 22:49:14.802</td>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Word, Excel, PowerPoint, SPSS</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-02-19 23:01:24.057</td>\n",
       "      <td>Female</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Word, Excel, PowerPoint, SQL, Python, R, JavaS...</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-02-20 08:27:19.584</td>\n",
       "      <td>Female</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Word, Excel, PowerPoint</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-02-20 08:27:36.059</td>\n",
       "      <td>Female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Excel, Python, R</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-02-20 08:28:19.725</td>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SQL, R, SPSS, SAS</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-02-20 09:16:02.448</td>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>24.0</td>\n",
       "      <td>PowerPoint</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-02-20 09:22:23.851</td>\n",
       "      <td>Male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Word</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-02-20 09:23:22.259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Excel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Timestamp             gender  age (years)  \\\n",
       "0 2021-02-19 22:36:35.982               Male         24.0   \n",
       "1 2021-02-19 22:38:17.913               Male         22.0   \n",
       "2 2021-02-19 22:49:14.802  Prefer not to say         35.0   \n",
       "3 2021-02-19 23:01:24.057             Female         23.0   \n",
       "4 2021-02-20 08:27:19.584             Female         27.0   \n",
       "5 2021-02-20 08:27:36.059             Female         19.0   \n",
       "6 2021-02-20 08:28:19.725  Prefer not to say         30.0   \n",
       "7 2021-02-20 09:16:02.448  Prefer not to say         24.0   \n",
       "8 2021-02-20 09:22:23.851               Male          NaN   \n",
       "9 2021-02-20 09:23:22.259                NaN          NaN   \n",
       "\n",
       "                                              skills satisfaction [product]  \\\n",
       "0                    Word, Excel, PowerPoint, Access      very dissatisfied   \n",
       "1                                         Excel, SQL         very satisfied   \n",
       "2                      Word, Excel, PowerPoint, SPSS      very dissatisfied   \n",
       "3  Word, Excel, PowerPoint, SQL, Python, R, JavaS...         very satisfied   \n",
       "4                            Word, Excel, PowerPoint                neutral   \n",
       "5                                   Excel, Python, R              satisfied   \n",
       "6                                  SQL, R, SPSS, SAS           dissatisfied   \n",
       "7                                         PowerPoint              satisfied   \n",
       "8                                               Word      very dissatisfied   \n",
       "9                                              Excel                    NaN   \n",
       "\n",
       "  satisfaction [price] satisfaction [service] satisfaction [overall]  \n",
       "0         dissatisfied                neutral              satisfied  \n",
       "1            satisfied                neutral           dissatisfied  \n",
       "2         dissatisfied                neutral           dissatisfied  \n",
       "3            satisfied                neutral           dissatisfied  \n",
       "4            satisfied         very satisfied         very satisfied  \n",
       "5            satisfied              satisfied              satisfied  \n",
       "6            satisfied                neutral         very satisfied  \n",
       "7       very satisfied              satisfied         very satisfied  \n",
       "8         dissatisfied                neutral                   None  \n",
       "9                  NaN                    NaN              satisfied  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# google sheets generated by google form\n",
    "# https://docs.google.com/spreadsheets/d/1W0EaP8WGWaOK8XYDQA3Z4HIZaOQXXYj6U6kzqMuVrUI/edit#gid=1695829581\n",
    "# note: replace 'edit#' with 'export?format=xlsx&'\n",
    "gs_url='https://docs.google.com/spreadsheets/d/1W0EaP8WGWaOK8XYDQA3Z4HIZaOQXXYj6U6kzqMuVrUI/edit#gid=1695829581'\n",
    "url=re.sub('edit#', 'export?format=xlsx&', gs_url)\n",
    "# url='https://docs.google.com/spreadsheets/d/1W0EaP8WGWaOK8XYDQA3Z4HIZaOQXXYj6U6kzqMuVrUI/export?format=xlsx&gid=1695829581'\n",
    "df = pd.read_excel(url)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Timestamp', 'gender', 'age (years)', 'skills',\n",
       "       'satisfaction [product]', 'satisfaction [price]',\n",
       "       'satisfaction [service]', 'satisfaction [overall]'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Timestamp', 'gender', 'age (years)', 'skills', 'product', 'price',\n",
       "       'service', 'overall'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns.str.replace(r'(satisfaction|\\[|\\])', '', regex=True).str.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>skills</th>\n",
       "      <th>product</th>\n",
       "      <th>price</th>\n",
       "      <th>service</th>\n",
       "      <th>overall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-02-19 22:36:35.982</td>\n",
       "      <td>Male</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Word, Excel, PowerPoint, Access</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-02-19 22:38:17.913</td>\n",
       "      <td>Male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Excel, SQL</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-02-19 22:49:14.802</td>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Word, Excel, PowerPoint, SPSS</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-02-19 23:01:24.057</td>\n",
       "      <td>Female</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Word, Excel, PowerPoint, SQL, Python, R, JavaS...</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-02-20 08:27:19.584</td>\n",
       "      <td>Female</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Word, Excel, PowerPoint</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-02-20 08:27:36.059</td>\n",
       "      <td>Female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Excel, Python, R</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-02-20 08:28:19.725</td>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SQL, R, SPSS, SAS</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-02-20 09:16:02.448</td>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>24.0</td>\n",
       "      <td>PowerPoint</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-02-20 09:22:23.851</td>\n",
       "      <td>Male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Word</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-02-20 09:23:22.259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Excel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                timestamp             gender   age  \\\n",
       "0 2021-02-19 22:36:35.982               Male  24.0   \n",
       "1 2021-02-19 22:38:17.913               Male  22.0   \n",
       "2 2021-02-19 22:49:14.802  Prefer not to say  35.0   \n",
       "3 2021-02-19 23:01:24.057             Female  23.0   \n",
       "4 2021-02-20 08:27:19.584             Female  27.0   \n",
       "5 2021-02-20 08:27:36.059             Female  19.0   \n",
       "6 2021-02-20 08:28:19.725  Prefer not to say  30.0   \n",
       "7 2021-02-20 09:16:02.448  Prefer not to say  24.0   \n",
       "8 2021-02-20 09:22:23.851               Male   NaN   \n",
       "9 2021-02-20 09:23:22.259                NaN   NaN   \n",
       "\n",
       "                                              skills            product  \\\n",
       "0                    Word, Excel, PowerPoint, Access  very dissatisfied   \n",
       "1                                         Excel, SQL     very satisfied   \n",
       "2                      Word, Excel, PowerPoint, SPSS  very dissatisfied   \n",
       "3  Word, Excel, PowerPoint, SQL, Python, R, JavaS...     very satisfied   \n",
       "4                            Word, Excel, PowerPoint            neutral   \n",
       "5                                   Excel, Python, R          satisfied   \n",
       "6                                  SQL, R, SPSS, SAS       dissatisfied   \n",
       "7                                         PowerPoint          satisfied   \n",
       "8                                               Word  very dissatisfied   \n",
       "9                                              Excel                NaN   \n",
       "\n",
       "            price         service         overall  \n",
       "0    dissatisfied         neutral       satisfied  \n",
       "1       satisfied         neutral    dissatisfied  \n",
       "2    dissatisfied         neutral    dissatisfied  \n",
       "3       satisfied         neutral    dissatisfied  \n",
       "4       satisfied  very satisfied  very satisfied  \n",
       "5       satisfied       satisfied       satisfied  \n",
       "6       satisfied         neutral  very satisfied  \n",
       "7  very satisfied       satisfied  very satisfied  \n",
       "8    dissatisfied         neutral            None  \n",
       "9             NaN             NaN       satisfied  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = ['timestamp', 'gender', 'age', 'skills', 'product', 'price', 'service', 'overall']\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## recode gender "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      M\n",
       "1      M\n",
       "2      X\n",
       "3      F\n",
       "4      F\n",
       "5      F\n",
       "6      X\n",
       "7      X\n",
       "8      M\n",
       "9    NaN\n",
       "Name: gender, dtype: object"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = {'Female': 'F',\n",
    "     'Male': 'M',\n",
    "     'Prefer not to say': 'X'}\n",
    "\n",
    "df.gender.map(d, na_action='ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.gender=df.gender.map(d, na_action='ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>skills</th>\n",
       "      <th>product</th>\n",
       "      <th>price</th>\n",
       "      <th>service</th>\n",
       "      <th>overall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-02-19 22:36:35.982</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Word, Excel, PowerPoint, Access</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-02-19 22:38:17.913</td>\n",
       "      <td>M</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Excel, SQL</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-02-19 22:49:14.802</td>\n",
       "      <td>X</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Word, Excel, PowerPoint, SPSS</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-02-19 23:01:24.057</td>\n",
       "      <td>F</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Word, Excel, PowerPoint, SQL, Python, R, JavaS...</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-02-20 08:27:19.584</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Word, Excel, PowerPoint</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-02-20 08:27:36.059</td>\n",
       "      <td>F</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Excel, Python, R</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-02-20 08:28:19.725</td>\n",
       "      <td>X</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SQL, R, SPSS, SAS</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-02-20 09:16:02.448</td>\n",
       "      <td>X</td>\n",
       "      <td>24.0</td>\n",
       "      <td>PowerPoint</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-02-20 09:22:23.851</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Word</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-02-20 09:23:22.259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Excel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                timestamp gender   age  \\\n",
       "0 2021-02-19 22:36:35.982      M  24.0   \n",
       "1 2021-02-19 22:38:17.913      M  22.0   \n",
       "2 2021-02-19 22:49:14.802      X  35.0   \n",
       "3 2021-02-19 23:01:24.057      F  23.0   \n",
       "4 2021-02-20 08:27:19.584      F  27.0   \n",
       "5 2021-02-20 08:27:36.059      F  19.0   \n",
       "6 2021-02-20 08:28:19.725      X  30.0   \n",
       "7 2021-02-20 09:16:02.448      X  24.0   \n",
       "8 2021-02-20 09:22:23.851      M   NaN   \n",
       "9 2021-02-20 09:23:22.259    NaN   NaN   \n",
       "\n",
       "                                              skills            product  \\\n",
       "0                    Word, Excel, PowerPoint, Access  very dissatisfied   \n",
       "1                                         Excel, SQL     very satisfied   \n",
       "2                      Word, Excel, PowerPoint, SPSS  very dissatisfied   \n",
       "3  Word, Excel, PowerPoint, SQL, Python, R, JavaS...     very satisfied   \n",
       "4                            Word, Excel, PowerPoint            neutral   \n",
       "5                                   Excel, Python, R          satisfied   \n",
       "6                                  SQL, R, SPSS, SAS       dissatisfied   \n",
       "7                                         PowerPoint          satisfied   \n",
       "8                                               Word  very dissatisfied   \n",
       "9                                              Excel                NaN   \n",
       "\n",
       "            price         service         overall  \n",
       "0    dissatisfied         neutral       satisfied  \n",
       "1       satisfied         neutral    dissatisfied  \n",
       "2    dissatisfied         neutral    dissatisfied  \n",
       "3       satisfied         neutral    dissatisfied  \n",
       "4       satisfied  very satisfied  very satisfied  \n",
       "5       satisfied       satisfied       satisfied  \n",
       "6       satisfied         neutral  very satisfied  \n",
       "7  very satisfied       satisfied  very satisfied  \n",
       "8    dissatisfied         neutral            None  \n",
       "9             NaN             NaN       satisfied  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1.0\n",
       "1    5.0\n",
       "2    1.0\n",
       "3    5.0\n",
       "4    3.0\n",
       "5    4.0\n",
       "6    2.0\n",
       "7    4.0\n",
       "8    1.0\n",
       "9    NaN\n",
       "Name: product, dtype: float64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['product'].map({'very dissatisfied':1, 'dissatisfied':2, 'neutral':3, 'satisfied':4, 'very satisfied':5}, na_action='ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['very dissatisfied', 'very satisfied', 'very dissatisfied', 'very satisfied', 'neutral', 'satisfied', 'dissatisfied', 'satisfied', 'very dissatisfied', NaN]\n",
       "Categories (5, object): ['very dissatisfied' < 'dissatisfied' < 'neutral' < 'satisfied' < 'very satisfied']"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Categorical(df['product'], \n",
    "               categories=['very dissatisfied', 'dissatisfied', 'neutral', 'satisfied', 'very satisfied'], ordered=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    very dissatisfied\n",
       "1       very satisfied\n",
       "2    very dissatisfied\n",
       "3       very satisfied\n",
       "4              neutral\n",
       "5            satisfied\n",
       "6         dissatisfied\n",
       "7            satisfied\n",
       "8    very dissatisfied\n",
       "9                  NaN\n",
       "Name: product, dtype: object"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['product']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "for c in ['product', 'price', 'service', 'overall']:\n",
    "    df[f'{c}_n']=df[c].map({'very dissatisfied':1, 'dissatisfied':2, 'neutral':3, 'satisfied':4, 'very satisfied':5})    \n",
    "    df[c]=pd.Categorical(df[c], \n",
    "               categories=['very dissatisfied', 'dissatisfied', 'neutral', 'satisfied', 'very satisfied'], ordered=True)  \n",
    "    df[f'{c}_cat']=df[c].cat.codes + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10 entries, 0 to 9\n",
      "Data columns (total 16 columns):\n",
      " #   Column       Non-Null Count  Dtype         \n",
      "---  ------       --------------  -----         \n",
      " 0   timestamp    10 non-null     datetime64[ns]\n",
      " 1   gender       9 non-null      object        \n",
      " 2   age          8 non-null      float64       \n",
      " 3   skills       10 non-null     object        \n",
      " 4   product      9 non-null      category      \n",
      " 5   price        9 non-null      category      \n",
      " 6   service      9 non-null      category      \n",
      " 7   overall      9 non-null      category      \n",
      " 8   product_n    9 non-null      float64       \n",
      " 9   product_cat  10 non-null     int8          \n",
      " 10  price_n      9 non-null      float64       \n",
      " 11  price_cat    10 non-null     int8          \n",
      " 12  service_n    9 non-null      float64       \n",
      " 13  service_cat  10 non-null     int8          \n",
      " 14  overall_n    9 non-null      float64       \n",
      " 15  overall_cat  10 non-null     int8          \n",
      "dtypes: category(4), datetime64[ns](1), float64(5), int8(4), object(2)\n",
      "memory usage: 1.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    5\n",
       "2    1\n",
       "3    5\n",
       "4    3\n",
       "5    4\n",
       "6    2\n",
       "7    4\n",
       "8    1\n",
       "9    0\n",
       "dtype: int8"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['product'].cat.codes + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    3\n",
       "1    1\n",
       "2    1\n",
       "3    1\n",
       "4    4\n",
       "5    3\n",
       "6    4\n",
       "7    4\n",
       "8   -1\n",
       "9    3\n",
       "dtype: int8"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['overall'].cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.6666666666666665"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['overall_n'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.3"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df['overall'].cat.codes + 1).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "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>timestamp</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>skills</th>\n",
       "      <th>product</th>\n",
       "      <th>price</th>\n",
       "      <th>service</th>\n",
       "      <th>overall</th>\n",
       "      <th>product_n</th>\n",
       "      <th>product_cat</th>\n",
       "      <th>price_n</th>\n",
       "      <th>price_cat</th>\n",
       "      <th>service_n</th>\n",
       "      <th>service_cat</th>\n",
       "      <th>overall_n</th>\n",
       "      <th>overall_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-02-19 22:36:35.982</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Word, Excel, PowerPoint, Access</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-02-20 08:27:19.584</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Word, Excel, PowerPoint</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-02-20 08:27:36.059</td>\n",
       "      <td>F</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Excel, Python, R</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-02-20 08:28:19.725</td>\n",
       "      <td>X</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SQL, R, SPSS, SAS</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-02-20 09:16:02.448</td>\n",
       "      <td>X</td>\n",
       "      <td>24.0</td>\n",
       "      <td>PowerPoint</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-02-20 09:23:22.259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Excel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                timestamp gender   age                           skills  \\\n",
       "0 2021-02-19 22:36:35.982      M  24.0  Word, Excel, PowerPoint, Access   \n",
       "4 2021-02-20 08:27:19.584      F  27.0          Word, Excel, PowerPoint   \n",
       "5 2021-02-20 08:27:36.059      F  19.0                 Excel, Python, R   \n",
       "6 2021-02-20 08:28:19.725      X  30.0                SQL, R, SPSS, SAS   \n",
       "7 2021-02-20 09:16:02.448      X  24.0                       PowerPoint   \n",
       "9 2021-02-20 09:23:22.259    NaN   NaN                            Excel   \n",
       "\n",
       "             product           price         service         overall  \\\n",
       "0  very dissatisfied    dissatisfied         neutral       satisfied   \n",
       "4            neutral       satisfied  very satisfied  very satisfied   \n",
       "5          satisfied       satisfied       satisfied       satisfied   \n",
       "6       dissatisfied       satisfied         neutral  very satisfied   \n",
       "7          satisfied  very satisfied       satisfied  very satisfied   \n",
       "9                NaN             NaN             NaN       satisfied   \n",
       "\n",
       "   product_n  product_cat  price_n  price_cat  service_n  service_cat  \\\n",
       "0        1.0            1      2.0          2        3.0            3   \n",
       "4        3.0            3      4.0          4        5.0            5   \n",
       "5        4.0            4      4.0          4        4.0            4   \n",
       "6        2.0            2      4.0          4        3.0            3   \n",
       "7        4.0            4      5.0          5        4.0            4   \n",
       "9        NaN            0      NaN          0        NaN            0   \n",
       "\n",
       "   overall_n  overall_cat  \n",
       "0        4.0            4  \n",
       "4        5.0            5  \n",
       "5        4.0            4  \n",
       "6        5.0            5  \n",
       "7        5.0            5  \n",
       "9        4.0            4  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['overall'] > 'neutral']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>price</th>\n",
       "      <th>service</th>\n",
       "      <th>overall</th>\n",
       "      <th>product_n</th>\n",
       "      <th>product_cat</th>\n",
       "      <th>price_n</th>\n",
       "      <th>price_cat</th>\n",
       "      <th>service_n</th>\n",
       "      <th>service_cat</th>\n",
       "      <th>overall_n</th>\n",
       "      <th>overall_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-02-19 22:36:35.982</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Word, Excel, PowerPoint, Access</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-02-20 08:27:19.584</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Word, Excel, PowerPoint</td>\n",
       "      <td>neutral</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-02-20 08:27:36.059</td>\n",
       "      <td>F</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Excel, Python, R</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-02-20 08:28:19.725</td>\n",
       "      <td>X</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SQL, R, SPSS, SAS</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
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       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-02-20 09:16:02.448</td>\n",
       "      <td>X</td>\n",
       "      <td>24.0</td>\n",
       "      <td>PowerPoint</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-02-20 09:23:22.259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Excel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                timestamp gender   age                           skills  \\\n",
       "0 2021-02-19 22:36:35.982      M  24.0  Word, Excel, PowerPoint, Access   \n",
       "4 2021-02-20 08:27:19.584      F  27.0          Word, Excel, PowerPoint   \n",
       "5 2021-02-20 08:27:36.059      F  19.0                 Excel, Python, R   \n",
       "6 2021-02-20 08:28:19.725      X  30.0                SQL, R, SPSS, SAS   \n",
       "7 2021-02-20 09:16:02.448      X  24.0                       PowerPoint   \n",
       "9 2021-02-20 09:23:22.259    NaN   NaN                            Excel   \n",
       "\n",
       "             product           price         service         overall  \\\n",
       "0  very dissatisfied    dissatisfied         neutral       satisfied   \n",
       "4            neutral       satisfied  very satisfied  very satisfied   \n",
       "5          satisfied       satisfied       satisfied       satisfied   \n",
       "6       dissatisfied       satisfied         neutral  very satisfied   \n",
       "7          satisfied  very satisfied       satisfied  very satisfied   \n",
       "9                NaN             NaN             NaN       satisfied   \n",
       "\n",
       "   product_n  product_cat  price_n  price_cat  service_n  service_cat  \\\n",
       "0        1.0            1      2.0          2        3.0            3   \n",
       "4        3.0            3      4.0          4        5.0            5   \n",
       "5        4.0            4      4.0          4        4.0            4   \n",
       "6        2.0            2      4.0          4        3.0            3   \n",
       "7        4.0            4      5.0          5        4.0            4   \n",
       "9        NaN            0      NaN          0        NaN            0   \n",
       "\n",
       "   overall_n  overall_cat  \n",
       "0        4.0            4  \n",
       "4        5.0            5  \n",
       "5        4.0            4  \n",
       "6        5.0            5  \n",
       "7        5.0            5  \n",
       "9        4.0            4  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['overall_n'] > 3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    5\n",
       "2    1\n",
       "3    5\n",
       "4    3\n",
       "5    4\n",
       "6    2\n",
       "7    4\n",
       "8    1\n",
       "9    0\n",
       "Name: product_cat, dtype: int8"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['product_cat']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0\n",
       "1    4\n",
       "2    0\n",
       "3    4\n",
       "4    2\n",
       "5    3\n",
       "6    1\n",
       "7    3\n",
       "8    0\n",
       "9   -1\n",
       "dtype: int8"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['product'].cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'very dissatisfied'"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['product'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
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       "   Access  Excel  JavaScript  PowerPoint  Python  R  SAS  SPSS  SQL  Word\n",
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    "ds=df.skills.str.get_dummies(', ')\n",
    "ds"
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  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
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       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-02-20 08:27:36.059</td>\n",
       "      <td>F</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Excel, Python, R</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-02-20 08:28:19.725</td>\n",
       "      <td>X</td>\n",
       "      <td>30.0</td>\n",
       "      <td>SQL, R, SPSS, SAS</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-02-20 09:16:02.448</td>\n",
       "      <td>X</td>\n",
       "      <td>24.0</td>\n",
       "      <td>PowerPoint</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>very satisfied</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-02-20 09:22:23.851</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Word</td>\n",
       "      <td>very dissatisfied</td>\n",
       "      <td>dissatisfied</td>\n",
       "      <td>neutral</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-02-20 09:23:22.259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Excel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>satisfied</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                timestamp gender   age  \\\n",
       "0 2021-02-19 22:36:35.982      M  24.0   \n",
       "1 2021-02-19 22:38:17.913      M  22.0   \n",
       "2 2021-02-19 22:49:14.802      X  35.0   \n",
       "3 2021-02-19 23:01:24.057      F  23.0   \n",
       "4 2021-02-20 08:27:19.584      F  27.0   \n",
       "5 2021-02-20 08:27:36.059      F  19.0   \n",
       "6 2021-02-20 08:28:19.725      X  30.0   \n",
       "7 2021-02-20 09:16:02.448      X  24.0   \n",
       "8 2021-02-20 09:22:23.851      M   NaN   \n",
       "9 2021-02-20 09:23:22.259    NaN   NaN   \n",
       "\n",
       "                                              skills            product  \\\n",
       "0                    Word, Excel, PowerPoint, Access  very dissatisfied   \n",
       "1                                         Excel, SQL     very satisfied   \n",
       "2                      Word, Excel, PowerPoint, SPSS  very dissatisfied   \n",
       "3  Word, Excel, PowerPoint, SQL, Python, R, JavaS...     very satisfied   \n",
       "4                            Word, Excel, PowerPoint            neutral   \n",
       "5                                   Excel, Python, R          satisfied   \n",
       "6                                  SQL, R, SPSS, SAS       dissatisfied   \n",
       "7                                         PowerPoint          satisfied   \n",
       "8                                               Word  very dissatisfied   \n",
       "9                                              Excel                NaN   \n",
       "\n",
       "            price         service         overall  product_n  product_cat  \\\n",
       "0    dissatisfied         neutral       satisfied        1.0            1   \n",
       "1       satisfied         neutral    dissatisfied        5.0            5   \n",
       "2    dissatisfied         neutral    dissatisfied        1.0            1   \n",
       "3       satisfied         neutral    dissatisfied        5.0            5   \n",
       "4       satisfied  very satisfied  very satisfied        3.0            3   \n",
       "5       satisfied       satisfied       satisfied        4.0            4   \n",
       "6       satisfied         neutral  very satisfied        2.0            2   \n",
       "7  very satisfied       satisfied  very satisfied        4.0            4   \n",
       "8    dissatisfied         neutral             NaN        1.0            1   \n",
       "9             NaN             NaN       satisfied        NaN            0   \n",
       "\n",
       "   ...  Access  Excel  JavaScript  PowerPoint  Python  R  SAS  SPSS  SQL  Word  \n",
       "0  ...       1      1           0           1       0  0    0     0    0     1  \n",
       "1  ...       0      1           0           0       0  0    0     0    1     0  \n",
       "2  ...       0      1           0           1       0  0    0     1    0     1  \n",
       "3  ...       0      1           1           1       1  1    0     0    1     1  \n",
       "4  ...       0      1           0           1       0  0    0     0    0     1  \n",
       "5  ...       0      1           0           0       1  1    0     0    0     0  \n",
       "6  ...       0      0           0           0       0  1    1     1    1     0  \n",
       "7  ...       0      0           0           1       0  0    0     0    0     0  \n",
       "8  ...       0      0           0           0       0  0    0     0    0     1  \n",
       "9  ...       0      1           0           0       0  0    0     0    0     0  \n",
       "\n",
       "[10 rows x 26 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt=pd.concat([df, ds], axis=1).copy()\n",
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['timestamp', 'gender', 'age', 'skills', 'product', 'price', 'service',\n",
       "       'overall', 'product_n', 'product_cat', 'price_n', 'price_cat',\n",
       "       'service_n', 'service_cat', 'overall_n', 'overall_cat', 'Access',\n",
       "       'Excel', 'JavaScript', 'PowerPoint', 'Python', 'R', 'SAS', 'SPSS',\n",
       "       'SQL', 'Word'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>8.0</td>\n",
       "      <td>25.500000</td>\n",
       "      <td>5.042675</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.75</td>\n",
       "      <td>24.0</td>\n",
       "      <td>27.75</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product_n</th>\n",
       "      <td>9.0</td>\n",
       "      <td>2.888889</td>\n",
       "      <td>1.691482</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product_cat</th>\n",
       "      <td>10.0</td>\n",
       "      <td>2.600000</td>\n",
       "      <td>1.837873</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price_n</th>\n",
       "      <td>9.0</td>\n",
       "      <td>3.444444</td>\n",
       "      <td>1.130388</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price_cat</th>\n",
       "      <td>10.0</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>1.523884</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>service_n</th>\n",
       "      <td>9.0</td>\n",
       "      <td>3.444444</td>\n",
       "      <td>0.726483</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>service_cat</th>\n",
       "      <td>10.0</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>1.286684</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.75</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>overall_n</th>\n",
       "      <td>9.0</td>\n",
       "      <td>3.666667</td>\n",
       "      <td>1.322876</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>overall_cat</th>\n",
       "      <td>10.0</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>1.702939</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.75</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Access</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.316228</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Excel</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.483046</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.316228</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PowerPoint</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.527046</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Python</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.421637</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.483046</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAS</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.316228</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPSS</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.421637</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SQL</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.483046</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Word</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.527046</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             count       mean       std   min    25%   50%    75%   max\n",
       "age            8.0  25.500000  5.042675  19.0  22.75  24.0  27.75  35.0\n",
       "product_n      9.0   2.888889  1.691482   1.0   1.00   3.0   4.00   5.0\n",
       "product_cat   10.0   2.600000  1.837873   0.0   1.00   2.5   4.00   5.0\n",
       "price_n        9.0   3.444444  1.130388   2.0   2.00   4.0   4.00   5.0\n",
       "price_cat     10.0   3.100000  1.523884   0.0   2.00   4.0   4.00   5.0\n",
       "service_n      9.0   3.444444  0.726483   3.0   3.00   3.0   4.00   5.0\n",
       "service_cat   10.0   3.100000  1.286684   0.0   3.00   3.0   3.75   5.0\n",
       "overall_n      9.0   3.666667  1.322876   2.0   2.00   4.0   5.00   5.0\n",
       "overall_cat   10.0   3.300000  1.702939   0.0   2.00   4.0   4.75   5.0\n",
       "Access        10.0   0.100000  0.316228   0.0   0.00   0.0   0.00   1.0\n",
       "Excel         10.0   0.700000  0.483046   0.0   0.25   1.0   1.00   1.0\n",
       "JavaScript    10.0   0.100000  0.316228   0.0   0.00   0.0   0.00   1.0\n",
       "PowerPoint    10.0   0.500000  0.527046   0.0   0.00   0.5   1.00   1.0\n",
       "Python        10.0   0.200000  0.421637   0.0   0.00   0.0   0.00   1.0\n",
       "R             10.0   0.300000  0.483046   0.0   0.00   0.0   0.75   1.0\n",
       "SAS           10.0   0.100000  0.316228   0.0   0.00   0.0   0.00   1.0\n",
       "SPSS          10.0   0.200000  0.421637   0.0   0.00   0.0   0.00   1.0\n",
       "SQL           10.0   0.300000  0.483046   0.0   0.00   0.0   0.75   1.0\n",
       "Word          10.0   0.500000  0.527046   0.0   0.00   0.5   1.00   1.0"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Access        1\n",
       "Excel         7\n",
       "JavaScript    1\n",
       "PowerPoint    5\n",
       "Python        2\n",
       "R             3\n",
       "SAS           1\n",
       "SPSS          2\n",
       "SQL           3\n",
       "Word          5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.loc[:, 'Access':'Word'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    4\n",
       "1    2\n",
       "2    4\n",
       "3    7\n",
       "4    3\n",
       "5    3\n",
       "6    4\n",
       "7    1\n",
       "8    1\n",
       "9    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.loc[:, 'Access':'Word'].sum(axis=1)"
   ]
  }
 ],
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