stackoverflow.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Business understanding\n",
    "\n",
    "Base on the Stackoverflow’s 2017 Annual Developer Survey we are looking for logical and accurate patterns to help us identify some factors that affect the respondents' average salaries and job satisfaction. This dataset has more than 150 variables to study, so we need to choose the most useful ones to help determine such patterns.\n",
    "We will be using the **CRISP-DM** process for a cleaner analysis process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set(rc={'figure.figsize': (20, 10)})\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "schema = pd.read_csv('./data/survey-results-schema.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data understanding\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Column</th>\n",
       "      <th>Question</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Respondent</td>\n",
       "      <td>Respondent ID number</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Professional</td>\n",
       "      <td>Which of the following best describes you?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ProgramHobby</td>\n",
       "      <td>Do you program as a hobby or contribute to open source projects?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Country</td>\n",
       "      <td>In which country do you currently live?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>University</td>\n",
       "      <td>Are you currently enrolled in a formal, degree-granting college or university program?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>EmploymentStatus</td>\n",
       "      <td>Which of the following best describes your current employment status?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>FormalEducation</td>\n",
       "      <td>Which of the following best describes the highest level of formal education that you've completed?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MajorUndergrad</td>\n",
       "      <td>Which of the following best describes your main field of study (aka 'major') in college or university/for your undergraduate studies?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>HomeRemote</td>\n",
       "      <td>How often do you work from home or remotely?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CompanySize</td>\n",
       "      <td>In terms of the number of employees, how large is the company or organization you work for?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>CompanyType</td>\n",
       "      <td>Which of the following best describes the type of company or organization you work for?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>YearsProgram</td>\n",
       "      <td>How long has it been since you first learned how to program?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>YearsCodedJob</td>\n",
       "      <td>For how many years have you coded as part of your job?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>YearsCodedJobPast</td>\n",
       "      <td>For how many years did you code as part of your job?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>DeveloperType</td>\n",
       "      <td>Which of the following best describe you?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>WebDeveloperType</td>\n",
       "      <td>Which of the following best describes you as a Web developer?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>MobileDeveloperType</td>\n",
       "      <td>For which of the following platforms do you develop mobile applications?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NonDeveloperType</td>\n",
       "      <td>Which of the following describe you?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>CareerSatisfaction</td>\n",
       "      <td>Career satisfaction rating</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>JobSatisfaction</td>\n",
       "      <td>Job satisfaction rating</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ExCoderReturn</td>\n",
       "      <td>You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? If money weren't an issue, I would take a c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>ExCoderNotForMe</td>\n",
       "      <td>You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? Working as a developer just wasn't for me</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ExCoderBalance</td>\n",
       "      <td>You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? I have better work-life balance now than I ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>ExCoder10Years</td>\n",
       "      <td>You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? My career is going the way I thought it wou...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ExCoderBelonged</td>\n",
       "      <td>You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? When I was a developer, I didn't feel like ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>ExCoderSkills</td>\n",
       "      <td>You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? I don't think my coding skills are up to date</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>ExCoderWillNotCode</td>\n",
       "      <td>You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? I probably won't code for a living ever again</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ExCoderActive</td>\n",
       "      <td>You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? I'm still active in the developer community</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>PronounceGIF</td>\n",
       "      <td>How do you pronounce \"GIF\"?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>ProblemSolving</td>\n",
       "      <td>I love solving problems</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>BuildingThings</td>\n",
       "      <td>Building things is very rewarding</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>LearningNewTech</td>\n",
       "      <td>Learning new technologies is fun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>BoringDetails</td>\n",
       "      <td>I tend to get bored by implementation details</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>JobSecurity</td>\n",
       "      <td>Job security is important to me</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>DiversityImportant</td>\n",
       "      <td>Diversity in the workplace is important</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>AnnoyingUI</td>\n",
       "      <td>It annoys me when software has a poor UI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>FriendsDevelopers</td>\n",
       "      <td>Most of my friends are developers, engineers, or scientists</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>RightWrongWay</td>\n",
       "      <td>There's a right and a wrong way to do everything</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>UnderstandComputers</td>\n",
       "      <td>Honestly, there's a lot about computers that I just don't understand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>SeriousWork</td>\n",
       "      <td>I take my work very seriously</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>InvestTimeTools</td>\n",
       "      <td>I invest a lot of time into the tools I use</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>WorkPayCare</td>\n",
       "      <td>I don't really care what I work on, so long as I'm paid well</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>KinshipDevelopers</td>\n",
       "      <td>I feel a sense of kinship to other developers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>ChallengeMyself</td>\n",
       "      <td>I like to challenge myself</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>CompetePeers</td>\n",
       "      <td>I think of myself as competing with my peers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>ChangeWorld</td>\n",
       "      <td>I want to change the world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>JobSeekingStatus</td>\n",
       "      <td>Which of the following best describes your current job-seeking status?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>HoursPerWeek</td>\n",
       "      <td>During a typical week, approximately how many hours do you spend on activities related to finding new job opportunities?Please adjust the slider to the appropriate number of hours. The box to...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>LastNewJob</td>\n",
       "      <td>When was the last time that you took a job with a new employer?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>AssessJobIndustry</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The industry that I'd be working in</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>AssessJobRole</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The specific role or job title I'd be applying for</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>AssessJobExp</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The experience level called for in the job description</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>AssessJobDept</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The specific department or team I'd be working on</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>AssessJobTech</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The languages, frameworks, and other technologies I'd be working with</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>AssessJobProjects</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? How projects are managed at the company or organization</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>AssessJobCompensation</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The compensation and benefits offered</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>AssessJobOffice</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The office environment I'd be working in</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>AssessJobCommute</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The amount of time I'd have to spend commuting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>AssessJobRemote</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The opportunity to work from home/remotely</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>AssessJobLeaders</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The reputations of the company's senior leaders</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Column  \\\n",
       "0              Respondent   \n",
       "1            Professional   \n",
       "2            ProgramHobby   \n",
       "3                 Country   \n",
       "4              University   \n",
       "5        EmploymentStatus   \n",
       "6         FormalEducation   \n",
       "7          MajorUndergrad   \n",
       "8              HomeRemote   \n",
       "9             CompanySize   \n",
       "10            CompanyType   \n",
       "11           YearsProgram   \n",
       "12          YearsCodedJob   \n",
       "13      YearsCodedJobPast   \n",
       "14          DeveloperType   \n",
       "15       WebDeveloperType   \n",
       "16    MobileDeveloperType   \n",
       "17       NonDeveloperType   \n",
       "18     CareerSatisfaction   \n",
       "19        JobSatisfaction   \n",
       "20          ExCoderReturn   \n",
       "21        ExCoderNotForMe   \n",
       "22         ExCoderBalance   \n",
       "23         ExCoder10Years   \n",
       "24        ExCoderBelonged   \n",
       "25          ExCoderSkills   \n",
       "26     ExCoderWillNotCode   \n",
       "27          ExCoderActive   \n",
       "28           PronounceGIF   \n",
       "29         ProblemSolving   \n",
       "30         BuildingThings   \n",
       "31        LearningNewTech   \n",
       "32          BoringDetails   \n",
       "33            JobSecurity   \n",
       "34     DiversityImportant   \n",
       "35             AnnoyingUI   \n",
       "36      FriendsDevelopers   \n",
       "37          RightWrongWay   \n",
       "38    UnderstandComputers   \n",
       "39            SeriousWork   \n",
       "40        InvestTimeTools   \n",
       "41            WorkPayCare   \n",
       "42      KinshipDevelopers   \n",
       "43        ChallengeMyself   \n",
       "44           CompetePeers   \n",
       "45            ChangeWorld   \n",
       "46       JobSeekingStatus   \n",
       "47           HoursPerWeek   \n",
       "48             LastNewJob   \n",
       "49      AssessJobIndustry   \n",
       "50          AssessJobRole   \n",
       "51           AssessJobExp   \n",
       "52          AssessJobDept   \n",
       "53          AssessJobTech   \n",
       "54      AssessJobProjects   \n",
       "55  AssessJobCompensation   \n",
       "56        AssessJobOffice   \n",
       "57       AssessJobCommute   \n",
       "58        AssessJobRemote   \n",
       "59       AssessJobLeaders   \n",
       "\n",
       "                                                                                                                                                                                              Question  \n",
       "0                                                                                                                                                                                 Respondent ID number  \n",
       "1                                                                                                                                                           Which of the following best describes you?  \n",
       "2                                                                                                                                     Do you program as a hobby or contribute to open source projects?  \n",
       "3                                                                                                                                                              In which country do you currently live?  \n",
       "4                                                                                                               Are you currently enrolled in a formal, degree-granting college or university program?  \n",
       "5                                                                                                                                Which of the following best describes your current employment status?  \n",
       "6                                                                                                   Which of the following best describes the highest level of formal education that you've completed?  \n",
       "7                                                                Which of the following best describes your main field of study (aka 'major') in college or university/for your undergraduate studies?  \n",
       "8                                                                                                                                                         How often do you work from home or remotely?  \n",
       "9                                                                                                          In terms of the number of employees, how large is the company or organization you work for?  \n",
       "10                                                                                                             Which of the following best describes the type of company or organization you work for?  \n",
       "11                                                                                                                                        How long has it been since you first learned how to program?  \n",
       "12                                                                                                                                              For how many years have you coded as part of your job?  \n",
       "13                                                                                                                                                For how many years did you code as part of your job?  \n",
       "14                                                                                                                                                           Which of the following best describe you?  \n",
       "15                                                                                                                                       Which of the following best describes you as a Web developer?  \n",
       "16                                                                                                                            For which of the following platforms do you develop mobile applications?  \n",
       "17                                                                                                                                                                Which of the following describe you?  \n",
       "18                                                                                                                                                                          Career satisfaction rating  \n",
       "19                                                                                                                                                                             Job satisfaction rating  \n",
       "20  You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? If money weren't an issue, I would take a c...  \n",
       "21       You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? Working as a developer just wasn't for me  \n",
       "22  You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? I have better work-life balance now than I ...  \n",
       "23  You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? My career is going the way I thought it wou...  \n",
       "24  You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? When I was a developer, I didn't feel like ...  \n",
       "25   You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? I don't think my coding skills are up to date  \n",
       "26   You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? I probably won't code for a living ever again  \n",
       "27     You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? I'm still active in the developer community  \n",
       "28                                                                                                                                                                         How do you pronounce \"GIF\"?  \n",
       "29                                                                                                                                                                             I love solving problems  \n",
       "30                                                                                                                                                                   Building things is very rewarding  \n",
       "31                                                                                                                                                                    Learning new technologies is fun  \n",
       "32                                                                                                                                                       I tend to get bored by implementation details  \n",
       "33                                                                                                                                                                     Job security is important to me  \n",
       "34                                                                                                                                                             Diversity in the workplace is important  \n",
       "35                                                                                                                                                            It annoys me when software has a poor UI  \n",
       "36                                                                                                                                         Most of my friends are developers, engineers, or scientists  \n",
       "37                                                                                                                                                    There's a right and a wrong way to do everything  \n",
       "38                                                                                                                                Honestly, there's a lot about computers that I just don't understand  \n",
       "39                                                                                                                                                                       I take my work very seriously  \n",
       "40                                                                                                                                                         I invest a lot of time into the tools I use  \n",
       "41                                                                                                                                        I don't really care what I work on, so long as I'm paid well  \n",
       "42                                                                                                                                                       I feel a sense of kinship to other developers  \n",
       "43                                                                                                                                                                          I like to challenge myself  \n",
       "44                                                                                                                                                        I think of myself as competing with my peers  \n",
       "45                                                                                                                                                                          I want to change the world  \n",
       "46                                                                                                                              Which of the following best describes your current job-seeking status?  \n",
       "47  During a typical week, approximately how many hours do you spend on activities related to finding new job opportunities?Please adjust the slider to the appropriate number of hours. The box to...  \n",
       "48                                                                                                                                     When was the last time that you took a job with a new employer?  \n",
       "49                                                               When you're assessing potential jobs to apply to, how important are each of the following to you? The industry that I'd be working in  \n",
       "50                                                When you're assessing potential jobs to apply to, how important are each of the following to you? The specific role or job title I'd be applying for  \n",
       "51                                            When you're assessing potential jobs to apply to, how important are each of the following to you? The experience level called for in the job description  \n",
       "52                                                 When you're assessing potential jobs to apply to, how important are each of the following to you? The specific department or team I'd be working on  \n",
       "53                             When you're assessing potential jobs to apply to, how important are each of the following to you? The languages, frameworks, and other technologies I'd be working with  \n",
       "54                                           When you're assessing potential jobs to apply to, how important are each of the following to you? How projects are managed at the company or organization  \n",
       "55                                                             When you're assessing potential jobs to apply to, how important are each of the following to you? The compensation and benefits offered  \n",
       "56                                                          When you're assessing potential jobs to apply to, how important are each of the following to you? The office environment I'd be working in  \n",
       "57                                                    When you're assessing potential jobs to apply to, how important are each of the following to you? The amount of time I'd have to spend commuting  \n",
       "58                                                        When you're assessing potential jobs to apply to, how important are each of the following to you? The opportunity to work from home/remotely  \n",
       "59                                                   When you're assessing potential jobs to apply to, how important are each of the following to you? The reputations of the company's senior leaders  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "schema[:60]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
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     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Column</th>\n",
       "      <th>Question</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>AssessJobProfDevel</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? Opportunities for professional development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>AssessJobDiversity</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The diversity of the company or organization</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>AssessJobProduct</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? How widely used or impactful the product or service I'd be working on is</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>AssessJobFinances</td>\n",
       "      <td>When you're assessing potential jobs to apply to, how important are each of the following to you? The financial performance or funding status of the company or organization</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>ImportantBenefits</td>\n",
       "      <td>When it comes to compensation and benefits, other than base salary, which of the following are most important to you?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>ClickyKeys</td>\n",
       "      <td>If two developers are sharing an office, is it OK for one of them to get a mechanical keyboard with loud \"clicky\" keys?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>JobProfile</td>\n",
       "      <td>On which of the following sites do you maintain a profile, CV, or resumé?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>ResumePrompted</td>\n",
       "      <td>Think back to the last time you updated your resumé, CV, or an online profile on a job site. What prompted you to do so?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>LearnedHiring</td>\n",
       "      <td>Think back to when you first applied to work for your current employer. Which of the following best describes how you learned that they were hiring for that particular job?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>ImportantHiringAlgorithms</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>ImportantHiringTechExp</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>ImportantHiringCommunication</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>ImportantHiringOpenSource</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>ImportantHiringPMExp</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>ImportantHiringCompanies</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>ImportantHiringTitles</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>ImportantHiringEducation</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>ImportantHiringRep</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>ImportantHiringGettingThingsDone</td>\n",
       "      <td>Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>Currency</td>\n",
       "      <td>Which currency do you use day-to-day? If you're a globe-trotting digital nomad and the answer is “it's complicated,” please pick the one you're most comfortable estimating in.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Overpaid</td>\n",
       "      <td>Compared to your estimate of your own market value, do you think you are…?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>TabsSpaces</td>\n",
       "      <td>Tabs or spaces?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>EducationImportant</td>\n",
       "      <td>Overall, how important has your formal schooling and education been to your career success?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>EducationTypes</td>\n",
       "      <td>Outside of your formal schooling and education, which of the following have you done?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>SelfTaughtTypes</td>\n",
       "      <td>You indicated that you had taught yourself a programming technology without taking a course. What resources did you use to do that? If you've done it more than once, please think about the mo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>TimeAfterBootcamp</td>\n",
       "      <td>You indicated previously that you went through a developer “bootcamp.” How long did it take you to get a full-time job as a developer after graduating?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>CousinEducation</td>\n",
       "      <td>Let's pretend you have a distant cousin. They are 24 years old, have a college degree in a field not related to computer programming, and have been working a non-coding job for the last two y...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>WorkStart</td>\n",
       "      <td>Suppose you could choose your own working hours for an 8-hour day. What time would you start work for the day? Please adjust the slider to the hour nearest your ideal start time. The box next...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>HaveWorkedLanguage</td>\n",
       "      <td>Which of the following languages have you done extensive development work in over the past year, and which do you want to work in over the next year?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>WantWorkLanguage</td>\n",
       "      <td>Which of the following languages have you done extensive development work in over the past year, and which do you want to work in over the next year?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>HaveWorkedFramework</td>\n",
       "      <td>Which of the following libraries, frameworks, and tools have you done extensive development work in over the past year, and which do you want to work in over the next year?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>WantWorkFramework</td>\n",
       "      <td>Which of the following libraries, frameworks, and tools have you done extensive development work in over the past year, and which do you want to work in over the next year?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>HaveWorkedDatabase</td>\n",
       "      <td>Which of the following database technologies have you done extensive development work in over the past year, and which do you want to work in over the next year?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>WantWorkDatabase</td>\n",
       "      <td>Which of the following database technologies have you done extensive development work in over the past year, and which do you want to work in over the next year?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>HaveWorkedPlatform</td>\n",
       "      <td>Which of the following platforms have you done extensive development work for over the past year, and which do you want to work on over the next year?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>WantWorkPlatform</td>\n",
       "      <td>Which of the following platforms have you done extensive development work for over the past year, and which do you want to work on over the next year?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>IDE</td>\n",
       "      <td>Which development environment(s) do you use regularly?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>AuditoryEnvironment</td>\n",
       "      <td>Suppose you're about to start a few hours of coding and have complete control over your auditory environment (music, background noise, etc.). What would you do?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Methodology</td>\n",
       "      <td>Which of the following methodologies do you have experience working in?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>VersionControl</td>\n",
       "      <td>What version control system do you use? If you use several, please choose the one you use most often.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>CheckInCode</td>\n",
       "      <td>Over the last year, how often have you checked-in or committed code?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>ShipIt</td>\n",
       "      <td>It's better to ship now and optimize later</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>OtherPeoplesCode</td>\n",
       "      <td>Maintaining other people's code is a form of torture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>ProjectManagement</td>\n",
       "      <td>Most project management techniques are useless</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>EnjoyDebugging</td>\n",
       "      <td>I enjoy debugging code</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>InTheZone</td>\n",
       "      <td>I often get “into the zone” when I'm coding</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>DifficultCommunication</td>\n",
       "      <td>I have difficulty communicating my ideas to my peers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>CollaborateRemote</td>\n",
       "      <td>It's harder to collaborate with remote peers than those on site</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>MetricAssess</td>\n",
       "      <td>Congratulations! The bosses at your new employer, E Corp, are allowing you to choose which metrics will be used to assess your individual performance in your role as a senior developer. Which...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>EquipmentSatisfiedMonitors</td>\n",
       "      <td>Thinking about your main coding workstation, how satisfied are you with each of the following? Monitors/screens (number of, size, resolution)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>EquipmentSatisfiedCPU</td>\n",
       "      <td>Thinking about your main coding workstation, how satisfied are you with each of the following? Processing power (CPU and/or GPU)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>EquipmentSatisfiedRAM</td>\n",
       "      <td>Thinking about your main coding workstation, how satisfied are you with each of the following? Amount of RAM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>EquipmentSatisfiedStorage</td>\n",
       "      <td>Thinking about your main coding workstation, how satisfied are you with each of the following? Storage capacity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>EquipmentSatisfiedRW</td>\n",
       "      <td>Thinking about your main coding workstation, how satisfied are you with each of the following? Storage read/write speed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>InfluenceInternet</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Internet bandwidth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>InfluenceWorkstation</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Your personal workstation hardware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>InfluenceHardware</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Personal workstation hardware for others in the company</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>InfluenceServers</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Servers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>InfluenceTechStack</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Main technical stack of the company</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>InfluenceDeptTech</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Technical stack used in your department</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Column  \\\n",
       "60                 AssessJobProfDevel   \n",
       "61                 AssessJobDiversity   \n",
       "62                   AssessJobProduct   \n",
       "63                  AssessJobFinances   \n",
       "64                  ImportantBenefits   \n",
       "65                         ClickyKeys   \n",
       "66                         JobProfile   \n",
       "67                     ResumePrompted   \n",
       "68                      LearnedHiring   \n",
       "69          ImportantHiringAlgorithms   \n",
       "70             ImportantHiringTechExp   \n",
       "71       ImportantHiringCommunication   \n",
       "72          ImportantHiringOpenSource   \n",
       "73               ImportantHiringPMExp   \n",
       "74           ImportantHiringCompanies   \n",
       "75              ImportantHiringTitles   \n",
       "76           ImportantHiringEducation   \n",
       "77                 ImportantHiringRep   \n",
       "78   ImportantHiringGettingThingsDone   \n",
       "79                           Currency   \n",
       "80                           Overpaid   \n",
       "81                         TabsSpaces   \n",
       "82                 EducationImportant   \n",
       "83                     EducationTypes   \n",
       "84                    SelfTaughtTypes   \n",
       "85                  TimeAfterBootcamp   \n",
       "86                    CousinEducation   \n",
       "87                          WorkStart   \n",
       "88                 HaveWorkedLanguage   \n",
       "89                   WantWorkLanguage   \n",
       "90                HaveWorkedFramework   \n",
       "91                  WantWorkFramework   \n",
       "92                 HaveWorkedDatabase   \n",
       "93                   WantWorkDatabase   \n",
       "94                 HaveWorkedPlatform   \n",
       "95                   WantWorkPlatform   \n",
       "96                                IDE   \n",
       "97                AuditoryEnvironment   \n",
       "98                        Methodology   \n",
       "99                     VersionControl   \n",
       "100                       CheckInCode   \n",
       "101                            ShipIt   \n",
       "102                  OtherPeoplesCode   \n",
       "103                 ProjectManagement   \n",
       "104                    EnjoyDebugging   \n",
       "105                         InTheZone   \n",
       "106            DifficultCommunication   \n",
       "107                 CollaborateRemote   \n",
       "108                      MetricAssess   \n",
       "109        EquipmentSatisfiedMonitors   \n",
       "110             EquipmentSatisfiedCPU   \n",
       "111             EquipmentSatisfiedRAM   \n",
       "112         EquipmentSatisfiedStorage   \n",
       "113              EquipmentSatisfiedRW   \n",
       "114                 InfluenceInternet   \n",
       "115              InfluenceWorkstation   \n",
       "116                 InfluenceHardware   \n",
       "117                  InfluenceServers   \n",
       "118                InfluenceTechStack   \n",
       "119                 InfluenceDeptTech   \n",
       "\n",
       "                                                                                                                                                                                               Question  \n",
       "60                                                         When you're assessing potential jobs to apply to, how important are each of the following to you? Opportunities for professional development  \n",
       "61                                                       When you're assessing potential jobs to apply to, how important are each of the following to you? The diversity of the company or organization  \n",
       "62                           When you're assessing potential jobs to apply to, how important are each of the following to you? How widely used or impactful the product or service I'd be working on is  \n",
       "63                         When you're assessing potential jobs to apply to, how important are each of the following to you? The financial performance or funding status of the company or organization  \n",
       "64                                                                                When it comes to compensation and benefits, other than base salary, which of the following are most important to you?  \n",
       "65                                                                              If two developers are sharing an office, is it OK for one of them to get a mechanical keyboard with loud \"clicky\" keys?  \n",
       "66                                                                                                                            On which of the following sites do you maintain a profile, CV, or resumé?  \n",
       "67                                                                             Think back to the last time you updated your resumé, CV, or an online profile on a job site. What prompted you to do so?  \n",
       "68                         Think back to when you first applied to work for your current employer. Which of the following best describes how you learned that they were hiring for that particular job?  \n",
       "69   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "70   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "71   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "72   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "73   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "74   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "75   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "76   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "77   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "78   Congratulations! You've just been put in charge of technical recruiting at Globex, a multinational high- tech firm. This job comes with a corner office, and you have an experienced staff of r...  \n",
       "79                      Which currency do you use day-to-day? If you're a globe-trotting digital nomad and the answer is “it's complicated,” please pick the one you're most comfortable estimating in.  \n",
       "80                                                                                                                           Compared to your estimate of your own market value, do you think you are…?  \n",
       "81                                                                                                                                                                                      Tabs or spaces?  \n",
       "82                                                                                                          Overall, how important has your formal schooling and education been to your career success?  \n",
       "83                                                                                                                Outside of your formal schooling and education, which of the following have you done?  \n",
       "84   You indicated that you had taught yourself a programming technology without taking a course. What resources did you use to do that? If you've done it more than once, please think about the mo...  \n",
       "85                                              You indicated previously that you went through a developer “bootcamp.” How long did it take you to get a full-time job as a developer after graduating?  \n",
       "86   Let's pretend you have a distant cousin. They are 24 years old, have a college degree in a field not related to computer programming, and have been working a non-coding job for the last two y...  \n",
       "87   Suppose you could choose your own working hours for an 8-hour day. What time would you start work for the day? Please adjust the slider to the hour nearest your ideal start time. The box next...  \n",
       "88                                                Which of the following languages have you done extensive development work in over the past year, and which do you want to work in over the next year?  \n",
       "89                                                Which of the following languages have you done extensive development work in over the past year, and which do you want to work in over the next year?  \n",
       "90                         Which of the following libraries, frameworks, and tools have you done extensive development work in over the past year, and which do you want to work in over the next year?  \n",
       "91                         Which of the following libraries, frameworks, and tools have you done extensive development work in over the past year, and which do you want to work in over the next year?  \n",
       "92                                    Which of the following database technologies have you done extensive development work in over the past year, and which do you want to work in over the next year?  \n",
       "93                                    Which of the following database technologies have you done extensive development work in over the past year, and which do you want to work in over the next year?  \n",
       "94                                               Which of the following platforms have you done extensive development work for over the past year, and which do you want to work on over the next year?  \n",
       "95                                               Which of the following platforms have you done extensive development work for over the past year, and which do you want to work on over the next year?  \n",
       "96                                                                                                                                               Which development environment(s) do you use regularly?  \n",
       "97                                     Suppose you're about to start a few hours of coding and have complete control over your auditory environment (music, background noise, etc.). What would you do?  \n",
       "98                                                                                                                              Which of the following methodologies do you have experience working in?  \n",
       "99                                                                                                What version control system do you use? If you use several, please choose the one you use most often.  \n",
       "100                                                                                                                                Over the last year, how often have you checked-in or committed code?  \n",
       "101                                                                                                                                                          It's better to ship now and optimize later  \n",
       "102                                                                                                                                                Maintaining other people's code is a form of torture  \n",
       "103                                                                                                                                                      Most project management techniques are useless  \n",
       "104                                                                                                                                                                              I enjoy debugging code  \n",
       "105                                                                                                                                                         I often get “into the zone” when I'm coding  \n",
       "106                                                                                                                                                I have difficulty communicating my ideas to my peers  \n",
       "107                                                                                                                                     It's harder to collaborate with remote peers than those on site  \n",
       "108  Congratulations! The bosses at your new employer, E Corp, are allowing you to choose which metrics will be used to assess your individual performance in your role as a senior developer. Which...  \n",
       "109                                                       Thinking about your main coding workstation, how satisfied are you with each of the following? Monitors/screens (number of, size, resolution)  \n",
       "110                                                                    Thinking about your main coding workstation, how satisfied are you with each of the following? Processing power (CPU and/or GPU)  \n",
       "111                                                                                        Thinking about your main coding workstation, how satisfied are you with each of the following? Amount of RAM  \n",
       "112                                                                                     Thinking about your main coding workstation, how satisfied are you with each of the following? Storage capacity  \n",
       "113                                                                             Thinking about your main coding workstation, how satisfied are you with each of the following? Storage read/write speed  \n",
       "114                                                                       How much influence do you have on purchasing decisions within your organization for each of the following? Internet bandwidth  \n",
       "115                                                       How much influence do you have on purchasing decisions within your organization for each of the following? Your personal workstation hardware  \n",
       "116                                  How much influence do you have on purchasing decisions within your organization for each of the following? Personal workstation hardware for others in the company  \n",
       "117                                                                                  How much influence do you have on purchasing decisions within your organization for each of the following? Servers  \n",
       "118                                                      How much influence do you have on purchasing decisions within your organization for each of the following? Main technical stack of the company  \n",
       "119                                                  How much influence do you have on purchasing decisions within your organization for each of the following? Technical stack used in your department  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
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    }
   ],
   "source": [
    "schema[60:120]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
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     "data": {
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       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Column</th>\n",
       "      <th>Question</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>InfluenceVizTools</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Data analysis and visualization tools (e.g. Tableau, Looker)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>InfluenceDatabase</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Database systems or solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>InfluenceCloud</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Cloud or serverless back-end solutions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>InfluenceConsultants</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Consultants</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>InfluenceRecruitment</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Recruitment tools &amp; platforms</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>InfluenceCommunication</td>\n",
       "      <td>How much influence do you have on purchasing decisions within your organization for each of the following? Communication &amp; collaboration tools</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>StackOverflowDescribes</td>\n",
       "      <td>Which of the following best describes you?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>StackOverflowSatisfaction</td>\n",
       "      <td>Stack Overflow satisfaction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>StackOverflowDevices</td>\n",
       "      <td>Which of the following devices have you used to connect to Stack Overflow over the last three months?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>StackOverflowFoundAnswer</td>\n",
       "      <td>Over the last three months, approximately how often have you done each of the following on Stack Overflow? Found an answer that solved my coding problem</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>StackOverflowCopiedCode</td>\n",
       "      <td>Over the last three months, approximately how often have you done each of the following on Stack Overflow? Copied a code example and pasted it into my codebase</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>StackOverflowJobListing</td>\n",
       "      <td>Over the last three months, approximately how often have you done each of the following on Stack Overflow? Seen a job listing I was interested in</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>StackOverflowCompanyPage</td>\n",
       "      <td>Over the last three months, approximately how often have you done each of the following on Stack Overflow? Researched a potential employer by visiting its company page</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>StackOverflowJobSearch</td>\n",
       "      <td>Over the last three months, approximately how often have you done each of the following on Stack Overflow? Searched for jobs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>StackOverflowNewQuestion</td>\n",
       "      <td>Over the last three months, approximately how often have you done each of the following on Stack Overflow? Asked a new question</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>StackOverflowAnswer</td>\n",
       "      <td>Over the last three months, approximately how often have you done each of the following on Stack Overflow? Written a new answer to someone else's question</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>StackOverflowMetaChat</td>\n",
       "      <td>Over the last three months, approximately how often have you done each of the following on Stack Overflow? Participated in community discussions on meta or in chat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>StackOverflowAdsRelevant</td>\n",
       "      <td>The ads on Stack Overflow are relevant to me</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>StackOverflowAdsDistracting</td>\n",
       "      <td>The ads on Stack Overflow are distracting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>StackOverflowModeration</td>\n",
       "      <td>The moderation on Stack Overflow is unfair</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>StackOverflowCommunity</td>\n",
       "      <td>I feel like a member of the Stack Overflow community</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>StackOverflowHelpful</td>\n",
       "      <td>The answers and code examples I get on Stack Overflow are helpful</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>StackOverflowBetter</td>\n",
       "      <td>Stack Overflow makes the Internet a better place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>StackOverflowWhatDo</td>\n",
       "      <td>I don't know what I'd do without Stack Overflow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>StackOverflowMakeMoney</td>\n",
       "      <td>The people who run Stack Overflow are just in it for the money</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Gender</td>\n",
       "      <td>Which of the following do you currently identify as?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>HighestEducationParents</td>\n",
       "      <td>What is the highest level of education received by either of your parents?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Race</td>\n",
       "      <td>Which of the following do you identify as?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>SurveyLong</td>\n",
       "      <td>This survey was too long</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>QuestionsInteresting</td>\n",
       "      <td>The questions were interesting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>QuestionsConfusing</td>\n",
       "      <td>The questions were confusing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>InterestedAnswers</td>\n",
       "      <td>I'm interested in learning how other developers answered</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Salary</td>\n",
       "      <td>What is your current annual base salary, before taxes, and excluding bonuses, grants, or other compensation?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>ExpectedSalary</td>\n",
       "      <td>You said before that you are currently learning how to program. When you have completed your studies, what annual salary do you expect to earn in your first job after graduation?</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Column  \\\n",
       "120            InfluenceVizTools   \n",
       "121            InfluenceDatabase   \n",
       "122               InfluenceCloud   \n",
       "123         InfluenceConsultants   \n",
       "124         InfluenceRecruitment   \n",
       "125       InfluenceCommunication   \n",
       "126       StackOverflowDescribes   \n",
       "127    StackOverflowSatisfaction   \n",
       "128         StackOverflowDevices   \n",
       "129     StackOverflowFoundAnswer   \n",
       "130      StackOverflowCopiedCode   \n",
       "131      StackOverflowJobListing   \n",
       "132     StackOverflowCompanyPage   \n",
       "133       StackOverflowJobSearch   \n",
       "134     StackOverflowNewQuestion   \n",
       "135          StackOverflowAnswer   \n",
       "136        StackOverflowMetaChat   \n",
       "137     StackOverflowAdsRelevant   \n",
       "138  StackOverflowAdsDistracting   \n",
       "139      StackOverflowModeration   \n",
       "140       StackOverflowCommunity   \n",
       "141         StackOverflowHelpful   \n",
       "142          StackOverflowBetter   \n",
       "143          StackOverflowWhatDo   \n",
       "144       StackOverflowMakeMoney   \n",
       "145                       Gender   \n",
       "146      HighestEducationParents   \n",
       "147                         Race   \n",
       "148                   SurveyLong   \n",
       "149         QuestionsInteresting   \n",
       "150           QuestionsConfusing   \n",
       "151            InterestedAnswers   \n",
       "152                       Salary   \n",
       "153               ExpectedSalary   \n",
       "\n",
       "                                                                                                                                                                               Question  \n",
       "120             How much influence do you have on purchasing decisions within your organization for each of the following? Data analysis and visualization tools (e.g. Tableau, Looker)  \n",
       "121                                            How much influence do you have on purchasing decisions within your organization for each of the following? Database systems or solutions  \n",
       "122                                   How much influence do you have on purchasing decisions within your organization for each of the following? Cloud or serverless back-end solutions  \n",
       "123                                                              How much influence do you have on purchasing decisions within your organization for each of the following? Consultants  \n",
       "124                                            How much influence do you have on purchasing decisions within your organization for each of the following? Recruitment tools & platforms  \n",
       "125                                      How much influence do you have on purchasing decisions within your organization for each of the following? Communication & collaboration tools  \n",
       "126                                                                                                                                          Which of the following best describes you?  \n",
       "127                                                                                                                                                         Stack Overflow satisfaction  \n",
       "128                                                                               Which of the following devices have you used to connect to Stack Overflow over the last three months?  \n",
       "129                            Over the last three months, approximately how often have you done each of the following on Stack Overflow? Found an answer that solved my coding problem  \n",
       "130                     Over the last three months, approximately how often have you done each of the following on Stack Overflow? Copied a code example and pasted it into my codebase  \n",
       "131                                   Over the last three months, approximately how often have you done each of the following on Stack Overflow? Seen a job listing I was interested in  \n",
       "132             Over the last three months, approximately how often have you done each of the following on Stack Overflow? Researched a potential employer by visiting its company page  \n",
       "133                                                        Over the last three months, approximately how often have you done each of the following on Stack Overflow? Searched for jobs  \n",
       "134                                                     Over the last three months, approximately how often have you done each of the following on Stack Overflow? Asked a new question  \n",
       "135                          Over the last three months, approximately how often have you done each of the following on Stack Overflow? Written a new answer to someone else's question  \n",
       "136                 Over the last three months, approximately how often have you done each of the following on Stack Overflow? Participated in community discussions on meta or in chat  \n",
       "137                                                                                                                                        The ads on Stack Overflow are relevant to me  \n",
       "138                                                                                                                                           The ads on Stack Overflow are distracting  \n",
       "139                                                                                                                                          The moderation on Stack Overflow is unfair  \n",
       "140                                                                                                                                I feel like a member of the Stack Overflow community  \n",
       "141                                                                                                                   The answers and code examples I get on Stack Overflow are helpful  \n",
       "142                                                                                                                                    Stack Overflow makes the Internet a better place  \n",
       "143                                                                                                                                     I don't know what I'd do without Stack Overflow  \n",
       "144                                                                                                                      The people who run Stack Overflow are just in it for the money  \n",
       "145                                                                                                                                Which of the following do you currently identify as?  \n",
       "146                                                                                                          What is the highest level of education received by either of your parents?  \n",
       "147                                                                                                                                          Which of the following do you identify as?  \n",
       "148                                                                                                                                                            This survey was too long  \n",
       "149                                                                                                                                                      The questions were interesting  \n",
       "150                                                                                                                                                        The questions were confusing  \n",
       "151                                                                                                                            I'm interested in learning how other developers answered  \n",
       "152                                                                        What is your current annual base salary, before taxes, and excluding bonuses, grants, or other compensation?  \n",
       "153  You said before that you are currently learning how to program. When you have completed your studies, what annual salary do you expect to earn in your first job after graduation?  "
      ]
     },
     "execution_count": 60,
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   ],
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    "schema[120:]"
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  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "topics = '''Professional\n",
    "DifficultCommunication\n",
    "ProgramHobby\n",
    "EmploymentStatus\n",
    "CompanyType\n",
    "DeveloperType\n",
    "CareerSatisfaction\n",
    "JobSatisfaction\n",
    "ExCoderNotForMe\n",
    "ProblemSolving\n",
    "BuildingThings\n",
    "LearningNewTech\n",
    "BoringDetails\n",
    "DiversityImportant\n",
    "FriendsDevelopers\n",
    "SeriousWork\n",
    "WorkPayCare\n",
    "ChallengeMyself\n",
    "CompetePeers\n",
    "ChangeWorld\n",
    "JobSeekingStatus\n",
    "HoursPerWeek\n",
    "Overpaid\n",
    "EducationImportant\n",
    "SelfTaughtTypes\n",
    "TimeAfterBootcamp\n",
    "Methodology\n",
    "CheckInCode\n",
    "ProjectManagement\n",
    "StackOverflowSatisfaction\n",
    "Gender\n",
    "HighestEducationParents\n",
    "Race\n",
    "SurveyLong\n",
    "Salary\n",
    "ExpectedSalary\n",
    "InvestTimeTools\n",
    "Professional'''\n",
    "topics_list = topics.split('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data['DeveloperType'].value_counts().index.str.split(';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1                                                                                                                                                              Which of the following best describes you?\n",
       "2                                                                                                                                        Do you program as a hobby or contribute to open source projects?\n",
       "5                                                                                                                                   Which of the following best describes your current employment status?\n",
       "10                                                                                                                Which of the following best describes the type of company or organization you work for?\n",
       "14                                                                                                                                                              Which of the following best describe you?\n",
       "18                                                                                                                                                                             Career satisfaction rating\n",
       "19                                                                                                                                                                                Job satisfaction rating\n",
       "21          You said before that you used to code as part of your job, but no longer do. To what extent do you agree or disagree with the following statements? Working as a developer just wasn't for me\n",
       "29                                                                                                                                                                                I love solving problems\n",
       "30                                                                                                                                                                      Building things is very rewarding\n",
       "31                                                                                                                                                                       Learning new technologies is fun\n",
       "32                                                                                                                                                          I tend to get bored by implementation details\n",
       "34                                                                                                                                                                Diversity in the workplace is important\n",
       "36                                                                                                                                            Most of my friends are developers, engineers, or scientists\n",
       "39                                                                                                                                                                          I take my work very seriously\n",
       "40                                                                                                                                                            I invest a lot of time into the tools I use\n",
       "41                                                                                                                                           I don't really care what I work on, so long as I'm paid well\n",
       "43                                                                                                                                                                             I like to challenge myself\n",
       "44                                                                                                                                                           I think of myself as competing with my peers\n",
       "45                                                                                                                                                                             I want to change the world\n",
       "46                                                                                                                                 Which of the following best describes your current job-seeking status?\n",
       "47     During a typical week, approximately how many hours do you spend on activities related to finding new job opportunities?Please adjust the slider to the appropriate number of hours. The box to...\n",
       "80                                                                                                                             Compared to your estimate of your own market value, do you think you are…?\n",
       "82                                                                                                            Overall, how important has your formal schooling and education been to your career success?\n",
       "84     You indicated that you had taught yourself a programming technology without taking a course. What resources did you use to do that? If you've done it more than once, please think about the mo...\n",
       "85                                                You indicated previously that you went through a developer “bootcamp.” How long did it take you to get a full-time job as a developer after graduating?\n",
       "98                                                                                                                                Which of the following methodologies do you have experience working in?\n",
       "100                                                                                                                                  Over the last year, how often have you checked-in or committed code?\n",
       "103                                                                                                                                                        Most project management techniques are useless\n",
       "106                                                                                                                                                  I have difficulty communicating my ideas to my peers\n",
       "127                                                                                                                                                                           Stack Overflow satisfaction\n",
       "145                                                                                                                                                  Which of the following do you currently identify as?\n",
       "146                                                                                                                            What is the highest level of education received by either of your parents?\n",
       "147                                                                                                                                                            Which of the following do you identify as?\n",
       "148                                                                                                                                                                              This survey was too long\n",
       "152                                                                                          What is your current annual base salary, before taxes, and excluding bonuses, grants, or other compensation?\n",
       "153                    You said before that you are currently learning how to program. When you have completed your studies, what annual salary do you expect to earn in your first job after graduation?\n",
       "Name: Question, dtype: object"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "pd.options.display.max_colwidth = 195\n",
    "schema[schema['Column'].isin(topics_list)]['Question']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Problem questions\n",
    "\n",
    "1. What is the relation that has the parents' education on the education and salary of the respondents? \n",
    "2. Is the people that is overpaid satisfied with their job?\n",
    "3. What are the common characteristics of the people that is currently employed but is seeking for a new job?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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>Respondent</th>\n",
       "      <th>Professional</th>\n",
       "      <th>ProgramHobby</th>\n",
       "      <th>Country</th>\n",
       "      <th>University</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>FormalEducation</th>\n",
       "      <th>MajorUndergrad</th>\n",
       "      <th>HomeRemote</th>\n",
       "      <th>CompanySize</th>\n",
       "      <th>...</th>\n",
       "      <th>StackOverflowMakeMoney</th>\n",
       "      <th>Gender</th>\n",
       "      <th>HighestEducationParents</th>\n",
       "      <th>Race</th>\n",
       "      <th>SurveyLong</th>\n",
       "      <th>QuestionsInteresting</th>\n",
       "      <th>QuestionsConfusing</th>\n",
       "      <th>InterestedAnswers</th>\n",
       "      <th>Salary</th>\n",
       "      <th>ExpectedSalary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Student</td>\n",
       "      <td>Yes, both</td>\n",
       "      <td>United States</td>\n",
       "      <td>No</td>\n",
       "      <td>Not employed, and not looking for work</td>\n",
       "      <td>Secondary school</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Strongly disagree</td>\n",
       "      <td>Male</td>\n",
       "      <td>High school</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>Strongly disagree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>Disagree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Student</td>\n",
       "      <td>Yes, both</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Yes, full-time</td>\n",
       "      <td>Employed part-time</td>\n",
       "      <td>Some college/university study without earning a bachelor's degree</td>\n",
       "      <td>Computer science or software engineering</td>\n",
       "      <td>More than half, but not all, the time</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>...</td>\n",
       "      <td>Strongly disagree</td>\n",
       "      <td>Male</td>\n",
       "      <td>A master's degree</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>Somewhat agree</td>\n",
       "      <td>Somewhat agree</td>\n",
       "      <td>Disagree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Professional developer</td>\n",
       "      <td>Yes, both</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>No</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor's degree</td>\n",
       "      <td>Computer science or software engineering</td>\n",
       "      <td>Less than half the time, but at least one day each week</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>...</td>\n",
       "      <td>Disagree</td>\n",
       "      <td>Male</td>\n",
       "      <td>A professional degree</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>Somewhat agree</td>\n",
       "      <td>Agree</td>\n",
       "      <td>Disagree</td>\n",
       "      <td>Agree</td>\n",
       "      <td>113750.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Professional non-developer who sometimes writes code</td>\n",
       "      <td>Yes, both</td>\n",
       "      <td>United States</td>\n",
       "      <td>No</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Doctoral degree</td>\n",
       "      <td>A non-computer-focused engineering discipline</td>\n",
       "      <td>Less than half the time, but at least one day each week</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>...</td>\n",
       "      <td>Disagree</td>\n",
       "      <td>Male</td>\n",
       "      <td>A doctoral degree</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>Agree</td>\n",
       "      <td>Agree</td>\n",
       "      <td>Somewhat agree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Professional developer</td>\n",
       "      <td>Yes, I program as a hobby</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>No</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>Computer science or software engineering</td>\n",
       "      <td>Never</td>\n",
       "      <td>10 to 19 employees</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 154 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Respondent                                          Professional  \\\n",
       "0           1                                               Student   \n",
       "1           2                                               Student   \n",
       "2           3                                Professional developer   \n",
       "3           4  Professional non-developer who sometimes writes code   \n",
       "4           5                                Professional developer   \n",
       "\n",
       "                ProgramHobby         Country      University  \\\n",
       "0                  Yes, both   United States              No   \n",
       "1                  Yes, both  United Kingdom  Yes, full-time   \n",
       "2                  Yes, both  United Kingdom              No   \n",
       "3                  Yes, both   United States              No   \n",
       "4  Yes, I program as a hobby     Switzerland              No   \n",
       "\n",
       "                         EmploymentStatus  \\\n",
       "0  Not employed, and not looking for work   \n",
       "1                      Employed part-time   \n",
       "2                      Employed full-time   \n",
       "3                      Employed full-time   \n",
       "4                      Employed full-time   \n",
       "\n",
       "                                                     FormalEducation  \\\n",
       "0                                                   Secondary school   \n",
       "1  Some college/university study without earning a bachelor's degree   \n",
       "2                                                  Bachelor's degree   \n",
       "3                                                    Doctoral degree   \n",
       "4                                                    Master's degree   \n",
       "\n",
       "                                  MajorUndergrad  \\\n",
       "0                                            NaN   \n",
       "1       Computer science or software engineering   \n",
       "2       Computer science or software engineering   \n",
       "3  A non-computer-focused engineering discipline   \n",
       "4       Computer science or software engineering   \n",
       "\n",
       "                                                HomeRemote  \\\n",
       "0                                                      NaN   \n",
       "1                    More than half, but not all, the time   \n",
       "2  Less than half the time, but at least one day each week   \n",
       "3  Less than half the time, but at least one day each week   \n",
       "4                                                    Never   \n",
       "\n",
       "                CompanySize  ... StackOverflowMakeMoney Gender  \\\n",
       "0                       NaN  ...      Strongly disagree   Male   \n",
       "1        20 to 99 employees  ...      Strongly disagree   Male   \n",
       "2  10,000 or more employees  ...               Disagree   Male   \n",
       "3  10,000 or more employees  ...               Disagree   Male   \n",
       "4        10 to 19 employees  ...                    NaN    NaN   \n",
       "\n",
       "  HighestEducationParents                          Race         SurveyLong  \\\n",
       "0             High school  White or of European descent  Strongly disagree   \n",
       "1       A master's degree  White or of European descent     Somewhat agree   \n",
       "2   A professional degree  White or of European descent     Somewhat agree   \n",
       "3       A doctoral degree  White or of European descent              Agree   \n",
       "4                     NaN                           NaN                NaN   \n",
       "\n",
       "  QuestionsInteresting QuestionsConfusing InterestedAnswers    Salary  \\\n",
       "0       Strongly agree           Disagree    Strongly agree       NaN   \n",
       "1       Somewhat agree           Disagree    Strongly agree       NaN   \n",
       "2                Agree           Disagree             Agree  113750.0   \n",
       "3                Agree     Somewhat agree    Strongly agree       NaN   \n",
       "4                  NaN                NaN               NaN       NaN   \n",
       "\n",
       "   ExpectedSalary  \n",
       "0             NaN  \n",
       "1         37500.0  \n",
       "2             NaN  \n",
       "3             NaN  \n",
       "4             NaN  \n",
       "\n",
       "[5 rows x 154 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('./data/survey_results_public.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. What is the relation that has the parents' education on the education and salary of the respondents? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# getting the variables that will be usefull to answer the question\n",
    "variables = ['HighestEducationParents', 'Salary', 'EmploymentStatus', \n",
    "'CareerSatisfaction', 'JobSatisfaction', 'DiversityImportant', 'FormalEducation']\n",
    "df = data[variables] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 51392 entries, 0 to 51391\n",
      "Data columns (total 7 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   HighestEducationParents  34938 non-null  object \n",
      " 1   Salary                   12891 non-null  float64\n",
      " 2   EmploymentStatus         51392 non-null  object \n",
      " 3   CareerSatisfaction       42695 non-null  float64\n",
      " 4   JobSatisfaction          40376 non-null  float64\n",
      " 5   DiversityImportant       30903 non-null  object \n",
      " 6   FormalEducation          51392 non-null  object \n",
      "dtypes: float64(3), object(4)\n",
      "memory usage: 2.7+ MB\n"
     ]
    }
   ],
   "source": [
    "# checking for na values and the data types\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 12891 entries, 2 to 51390\n",
      "Data columns (total 7 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   HighestEducationParents  11703 non-null  object \n",
      " 1   Salary                   12891 non-null  float64\n",
      " 2   EmploymentStatus         12891 non-null  object \n",
      " 3   CareerSatisfaction       12861 non-null  float64\n",
      " 4   JobSatisfaction          12852 non-null  float64\n",
      " 5   DiversityImportant       8863 non-null   object \n",
      " 6   FormalEducation          12891 non-null  object \n",
      "dtypes: float64(3), object(4)\n",
      "memory usage: 805.7+ KB\n"
     ]
    }
   ],
   "source": [
    "# to do an unbiased analysis, all the variable will be removed based on the salary\n",
    "df = df.dropna(subset=['Salary'])\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "HighestEducationParents     9.215732\n",
       "Salary                      0.000000\n",
       "EmploymentStatus            0.000000\n",
       "CareerSatisfaction          0.232721\n",
       "JobSatisfaction             0.302537\n",
       "DiversityImportant         31.246606\n",
       "FormalEducation             0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().mean() * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see some of the categorical variables have missing values. As the missing percentages are relatively small, we'll fill it with the **mode** statistic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 12891 entries, 2 to 51390\n",
      "Data columns (total 4 columns):\n",
      " #   Column                   Non-Null Count  Dtype \n",
      "---  ------                   --------------  ----- \n",
      " 0   HighestEducationParents  12891 non-null  object\n",
      " 1   EmploymentStatus         12891 non-null  object\n",
      " 2   DiversityImportant       12891 non-null  object\n",
      " 3   FormalEducation          12891 non-null  object\n",
      "dtypes: object(4)\n",
      "memory usage: 503.6+ KB\n"
     ]
    }
   ],
   "source": [
    "# filling the categorical variables\n",
    "objects = df.select_dtypes('object')\n",
    "objects = objects.fillna(objects.mode().squeeze())\n",
    "objects.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The numerical variables JobSatisfaction and DiversityImportant have missing values. The missing percentage is insignificant,hence, a **mean** imputation would work very well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 12891 entries, 2 to 51390\n",
      "Data columns (total 3 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   Salary              12891 non-null  float64\n",
      " 1   CareerSatisfaction  12891 non-null  float64\n",
      " 2   JobSatisfaction     12891 non-null  float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 402.8 KB\n"
     ]
    }
   ],
   "source": [
    "# filling the numerical variables\n",
    "float_data = df.select_dtypes('float')\n",
    "float_data = float_data.fillna(float_data.mean())\n",
    "float_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 12891 entries, 2 to 51390\n",
      "Data columns (total 7 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   HighestEducationParents  12891 non-null  object \n",
      " 1   EmploymentStatus         12891 non-null  object \n",
      " 2   DiversityImportant       12891 non-null  object \n",
      " 3   FormalEducation          12891 non-null  object \n",
      " 4   Salary                   12891 non-null  float64\n",
      " 5   CareerSatisfaction       12891 non-null  float64\n",
      " 6   JobSatisfaction          12891 non-null  float64\n",
      "dtypes: float64(3), object(4)\n",
      "memory usage: 805.7+ KB\n"
     ]
    }
   ],
   "source": [
    "# joining both the numerical and categorical data \n",
    "df_ = pd.concat([objects, float_data], axis=1)\n",
    "df_.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A bachelor's degree                                    0.367543\n",
       "A master's degree                                      0.201924\n",
       "High school                                            0.159103\n",
       "Some college/university study, no bachelor's degree    0.125591\n",
       "A doctoral degree                                      0.048483\n",
       "A professional degree                                  0.042743\n",
       "Primary/elementary school                              0.032115\n",
       "I don't know/not sure                                  0.012955\n",
       "I prefer not to answer                                 0.005042\n",
       "No education                                           0.004499\n",
       "Name: HighestEducationParents, dtype: float64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parents = (df_['HighestEducationParents'].value_counts() / df_['HighestEducationParents'].count()).sort_values(ascending=False)\n",
    "parents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PLOT-1\n",
    "\n",
    "# measure with percentages the parents' education \n",
    "(df_['HighestEducationParents'].value_counts() / df_['HighestEducationParents'].count()).sort_values().plot.barh(title=\"Parents' education\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Salaries based on the parents' education"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PLOT-2\n",
    "\n",
    "# Respondents' average salaries based on their parents' education \n",
    "df_.groupby('HighestEducationParents')['Salary'].mean().sort_values().plot.barh(title=\"Respondents' average salaries based on their parents' education\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Salaries based on the repondents' education"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PLOT-3\n",
    "\n",
    "# Respondents' average salaries based on their education\n",
    "df_.groupby('FormalEducation')['Salary'].mean().sort_values().plot.barh(title=\"Respondents' average salaries based on their education\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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>FormalEducation</th>\n",
       "      <th>HighestEducationParents</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A bachelor's degree</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4738.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A doctoral degree</th>\n",
       "      <td>NaN</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A master's degree</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2603.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A professional degree</th>\n",
       "      <td>NaN</td>\n",
       "      <td>551.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bachelor's degree</th>\n",
       "      <td>6407.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Doctoral degree</th>\n",
       "      <td>293.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>High school</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2051.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I don't know/not sure</th>\n",
       "      <td>NaN</td>\n",
       "      <td>167.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I never completed any formal education</th>\n",
       "      <td>60.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I prefer not to answer</th>\n",
       "      <td>45.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Master's degree</th>\n",
       "      <td>3077.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No education</th>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Primary/elementary school</th>\n",
       "      <td>55.0</td>\n",
       "      <td>414.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Professional degree</th>\n",
       "      <td>143.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Secondary school</th>\n",
       "      <td>761.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Some college/university study without earning a bachelor's degree</th>\n",
       "      <td>2050.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Some college/university study, no bachelor's degree</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1619.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                   FormalEducation  \\\n",
       "A bachelor's degree                                                            NaN   \n",
       "A doctoral degree                                                              NaN   \n",
       "A master's degree                                                              NaN   \n",
       "A professional degree                                                          NaN   \n",
       "Bachelor's degree                                                           6407.0   \n",
       "Doctoral degree                                                              293.0   \n",
       "High school                                                                    NaN   \n",
       "I don't know/not sure                                                          NaN   \n",
       "I never completed any formal education                                        60.0   \n",
       "I prefer not to answer                                                        45.0   \n",
       "Master's degree                                                             3077.0   \n",
       "No education                                                                   NaN   \n",
       "Primary/elementary school                                                     55.0   \n",
       "Professional degree                                                          143.0   \n",
       "Secondary school                                                             761.0   \n",
       "Some college/university study without earning a bachelor's degree           2050.0   \n",
       "Some college/university study, no bachelor's degree                            NaN   \n",
       "\n",
       "                                                                   HighestEducationParents  \n",
       "A bachelor's degree                                                                 4738.0  \n",
       "A doctoral degree                                                                    625.0  \n",
       "A master's degree                                                                   2603.0  \n",
       "A professional degree                                                                551.0  \n",
       "Bachelor's degree                                                                      NaN  \n",
       "Doctoral degree                                                                        NaN  \n",
       "High school                                                                         2051.0  \n",
       "I don't know/not sure                                                                167.0  \n",
       "I never completed any formal education                                                 NaN  \n",
       "I prefer not to answer                                                                65.0  \n",
       "Master's degree                                                                        NaN  \n",
       "No education                                                                          58.0  \n",
       "Primary/elementary school                                                            414.0  \n",
       "Professional degree                                                                    NaN  \n",
       "Secondary school                                                                       NaN  \n",
       "Some college/university study without earning a bachelor's degree                      NaN  \n",
       "Some college/university study, no bachelor's degree                                 1619.0  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Relation between parents' and respondents' education\n",
    "df_[['FormalEducation', 'HighestEducationParents']].apply(pd.Series.value_counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see there are some mismatches in the responses, let's fix it to properly plot it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "# updating values so it match between the values of HighestEducationParents and FormalEducation\n",
    "df_['HighestEducationParents'] = df_['HighestEducationParents'].replace('A doctoral degree', 'Doctoral degree')\\\n",
    "    .replace(\"A bachelor's degree\", \"Bachelor's degree\")\\\n",
    "    .replace(\"A master's degree\", \"Master's degree\")\\\n",
    "    .replace(\"A professional degree\", \"Professional degree\")\\\n",
    "    .replace(\"High school\", \"Secondary school\")\\\n",
    "    .replace(\"Some college/university study, no bachelor's degree\", \"Some college/university study without earning a bachelor's degree\")\\\n",
    "    .replace(\"No education\", \"I never completed any formal education\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PLOT-4\n",
    "\n",
    "# Comparison between respondents' and their parents' education\n",
    "df_[['FormalEducation', 'HighestEducationParents']].apply(pd.Series.value_counts).sort_values('HighestEducationParents').plot.barh(title=\"Comparison between respondents' and their parents' education\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Result evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the parents' education has a clear relation in the respondents' salaries. The respondents present a higher salary when their parents have higher education. However, this means nothing about the respondents' salaries based on their education. Take a look at the second element in **PLOT-3**, they have no professional degree, just elementary school studies. So interesting!!!\n",
    "\n",
    "When we are talking about the highest salaries that a developer could seek, **a professional degree is often not necessary**.\n",
    "\n",
    "Furthermore, we can conclude that the parents' education has an impact on the respondents' education. You can take a look at **PLOT-4** to make sure of it. As you can see, the number of respondents with higher degrees(except for the Doctoral degree) is bigger than the corresponding number of their parents."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Does overpayment increase the job satisfaction?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "# variables that will be used to answer the current question\n",
    "variables = ['Overpaid', 'JobSatisfaction', 'WorkPayCare', 'ProblemSolving', 'CompanyType', 'ProgramHobby']\n",
    "df = data[variables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 51392 entries, 0 to 51391\n",
      "Data columns (total 6 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   Overpaid         13387 non-null  object \n",
      " 1   JobSatisfaction  40376 non-null  float64\n",
      " 2   WorkPayCare      30965 non-null  object \n",
      " 3   ProblemSolving   31293 non-null  object \n",
      " 4   CompanyType      38823 non-null  object \n",
      " 5   ProgramHobby     51392 non-null  object \n",
      "dtypes: float64(1), object(5)\n",
      "memory usage: 2.4+ MB\n"
     ]
    }
   ],
   "source": [
    "# understanding data types\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Overpaid           73.951199\n",
       "JobSatisfaction    21.435243\n",
       "WorkPayCare        39.747432\n",
       "ProblemSolving     39.109200\n",
       "CompanyType        24.457114\n",
       "ProgramHobby        0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looking for null data\n",
    "df.isna().mean() * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "# removing null values based on Overpaid column because it has too much null values(73%)\n",
    "df.dropna(subset=['Overpaid'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Overpaid            0.000000\n",
       "JobSatisfaction     0.276388\n",
       "WorkPayCare        31.074923\n",
       "ProblemSolving     31.030104\n",
       "CompanyType         0.171808\n",
       "ProgramHobby        0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looking for null data\n",
    "df.isna().mean() * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see the above categorical variables have almost **32%** of missing data. It is still acceptable, so we'll fill it with the **mode**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "def filler(x: pd.Series) -> str:\n",
    "    \"\"\"Fills the missing data of categorical variables\n",
    "\n",
    "    Args:\n",
    "        x: pandas Series data structure with elements of type <object> \n",
    "    Returns:\n",
    "        The mode statistic of x\n",
    "    \"\"\"\n",
    "    return x.fillna(x.mode()[0])\n",
    "objects = ['WorkPayCare', 'ProblemSolving', 'CompanyType']\n",
    "# fill categorical data with the mode\n",
    "df[objects] = df[objects].apply(filler)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just **2.7%** of the answers are null for job satisfaction variable. We'll fill those null answers with the **mean** of the existent ones.\n",
    "This variable is numeric, the mean works well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fill numerical data with the mean \n",
    "df['JobSatisfaction'] = df['JobSatisfaction'].fillna(df['JobSatisfaction'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Overpaid           0.0\n",
       "JobSatisfaction    0.0\n",
       "WorkPayCare        0.0\n",
       "ProblemSolving     0.0\n",
       "CompanyType        0.0\n",
       "ProgramHobby       0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looking for null values after removing and filling\n",
    "df.isna().mean() * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "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>Overpaid</th>\n",
       "      <th>JobSatisfaction</th>\n",
       "      <th>WorkPayCare</th>\n",
       "      <th>ProblemSolving</th>\n",
       "      <th>CompanyType</th>\n",
       "      <th>ProgramHobby</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Neither underpaid nor overpaid</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Disagree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>Publicly-traded corporation</td>\n",
       "      <td>Yes, both</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Neither underpaid nor overpaid</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Strongly disagree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>Privately-held limited company, not in startup mode</td>\n",
       "      <td>Yes, I program as a hobby</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Somewhat underpaid</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Disagree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>Publicly-traded corporation</td>\n",
       "      <td>Yes, I program as a hobby</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Neither underpaid nor overpaid</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Strongly disagree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>Publicly-traded corporation</td>\n",
       "      <td>Yes, both</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Somewhat overpaid</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Somewhat agree</td>\n",
       "      <td>Strongly agree</td>\n",
       "      <td>Publicly-traded corporation</td>\n",
       "      <td>Yes, I program as a hobby</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Overpaid  JobSatisfaction        WorkPayCare  \\\n",
       "2   Neither underpaid nor overpaid              9.0           Disagree   \n",
       "8   Neither underpaid nor overpaid              6.0  Strongly disagree   \n",
       "14              Somewhat underpaid              8.0           Disagree   \n",
       "17  Neither underpaid nor overpaid              8.0  Strongly disagree   \n",
       "18               Somewhat overpaid              3.0     Somewhat agree   \n",
       "\n",
       "    ProblemSolving                                          CompanyType  \\\n",
       "2   Strongly agree                          Publicly-traded corporation   \n",
       "8   Strongly agree  Privately-held limited company, not in startup mode   \n",
       "14  Strongly agree                          Publicly-traded corporation   \n",
       "17  Strongly agree                          Publicly-traded corporation   \n",
       "18  Strongly agree                          Publicly-traded corporation   \n",
       "\n",
       "                 ProgramHobby  \n",
       "2                   Yes, both  \n",
       "8   Yes, I program as a hobby  \n",
       "14  Yes, I program as a hobby  \n",
       "17                  Yes, both  \n",
       "18  Yes, I program as a hobby  "
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 13387 entries, 2 to 51390\n",
      "Data columns (total 6 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   Overpaid         13387 non-null  object \n",
      " 1   JobSatisfaction  13387 non-null  float64\n",
      " 2   WorkPayCare      13387 non-null  object \n",
      " 3   ProblemSolving   13387 non-null  object \n",
      " 4   CompanyType      13387 non-null  object \n",
      " 5   ProgramHobby     13387 non-null  object \n",
      "dtypes: float64(1), object(5)\n",
      "memory usage: 732.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Overpaid\n",
       "Neither underpaid nor overpaid    7.513156\n",
       "Somewhat overpaid                 7.317700\n",
       "Greatly overpaid                  6.949961\n",
       "Somewhat underpaid                6.777208\n",
       "Greatly underpaid                 5.625619\n",
       "Name: JobSatisfaction, dtype: float64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Job satisfaction per Overpaid category\n",
    "overpaid_df = df.groupby('Overpaid')['JobSatisfaction'].mean().sort_values(ascending=False)\n",
    "overpaid_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Definitely, the people that are overpaid have higher job satisfaction. However, the people that is somewhat underpaid doesn't seem unsatisfied with their job. Furthermore, is interesting to note that the people which is greatly overpaid have a job satisfaction less than the one of the people who are neither underpaid nor overpaid. Could the type of company or the interest in what they work on influence on their job satisfaction?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "# filtering by the category with interesting result\n",
    "target = df.query(\"Overpaid == 'Greatly overpaid'\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CompanyType\n",
       "I don't know                                                             7.625000\n",
       "Privately-held limited company, not in startup mode                      7.552632\n",
       "Pre-series A startup                                                     7.000000\n",
       "Sole proprietorship or partnership, not in startup mode                  7.000000\n",
       "Venture-funded startup                                                   6.794607\n",
       "Non-profit/non-governmental organization or private school/university    6.666667\n",
       "State-owned company                                                      6.666667\n",
       "I prefer not to answer                                                   6.200000\n",
       "Publicly-traded corporation                                              6.150000\n",
       "Government agency or public school/university                            6.142857\n",
       "Name: JobSatisfaction, dtype: float64"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Job satisfaction per type of company\n",
    "companies_types = target.groupby('CompanyType')['JobSatisfaction'].mean().sort_values(ascending=False)\n",
    "companies_types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Privately-held limited company, not in startup mode                      38\n",
       "Publicly-traded corporation                                              20\n",
       "Venture-funded startup                                                   10\n",
       "I don't know                                                              8\n",
       "Government agency or public school/university                             7\n",
       "Sole proprietorship or partnership, not in startup mode                   5\n",
       "I prefer not to answer                                                    5\n",
       "State-owned company                                                       3\n",
       "Non-profit/non-governmental organization or private school/university     3\n",
       "Pre-series A startup                                                      2\n",
       "Name: CompanyType, dtype: int64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of respondents with a certain type of company\n",
    "target['CompanyType'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WorkPayCare\n",
       "Strongly agree       8.000000\n",
       "Disagree             7.228043\n",
       "Somewhat agree       6.700000\n",
       "Agree                6.666667\n",
       "Strongly disagree    6.368421\n",
       "Name: JobSatisfaction, dtype: float64"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Job satisfaction per the interest in what they do and the salary \n",
    "workcare = target.groupby('WorkPayCare')['JobSatisfaction'].mean().sort_values(ascending=False)\n",
    "workcare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 1)\n",
    "plt.subplots_adjust(hspace=0.5)\n",
    "ax[0].set_xlabel('Job satisfaction', fontsize=15)\n",
    "ax[0].set_title('Job Satisfaction based on company type', fontsize=15)\n",
    "ax[1].set_xlabel('Job satisfaction', fontsize=15)\n",
    "ax[1].set_title('Job Satisfaction based on the interest on what the respondents work on', fontsize=15)\n",
    "\n",
    "companies_types.plot.barh(ax=ax[0], fontsize=15)\n",
    "workcare.plot.barh(ax=ax[1], fontsize=15);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Result evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First of all, remember the above aggregates are based only on the data of the respondents who are greatly overpaid.\n",
    "\n",
    "There's and interest pattern. The companies that have job satisfaction between 6.1 and 6.7 are NGOs or government companies. However we cannot conclude nothing from it, there's no clear evidence and the number of company types is **skewed**. On the other side you can take a look at the answers related with the workPayCare. The people who answered **Strongly disagree** have a job satisfaction of 6.36, the lowest! This means that there's a proportion of respondents within this subset that are not entirely satisfied with their functions within their companies, no matter if they are overpaid.\n",
    "\n",
    "So, the job satisfaction level of the people who are greatly overpaid **may be** influenced by the work environment. Moreover, the repondents' functions within their companies may have another factor of influence."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. What is the percentage of people who are currently employed but looking for a new job? Is this people underpaid or their job satisfaction is low?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "# using only the interesting variables\n",
    "variables = ['EmploymentStatus', 'JobSeekingStatus', 'CompanyType', 'JobSatisfaction', 'Overpaid', 'HoursPerWeek']\n",
    "df = data[variables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 51392 entries, 0 to 51391\n",
      "Data columns (total 6 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   EmploymentStatus  51392 non-null  object \n",
      " 1   JobSeekingStatus  33380 non-null  object \n",
      " 2   CompanyType       38823 non-null  object \n",
      " 3   JobSatisfaction   40376 non-null  float64\n",
      " 4   Overpaid          13387 non-null  object \n",
      " 5   HoursPerWeek      20600 non-null  float64\n",
      "dtypes: float64(2), object(4)\n",
      "memory usage: 2.4+ MB\n"
     ]
    }
   ],
   "source": [
    "# checking dtypes\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Employed full-time                                      36148\n",
       "Independent contractor, freelancer, or self-employed     5233\n",
       "Employed part-time                                       3180\n",
       "Not employed, and not looking for work                   2791\n",
       "Not employed, but looking for work                       2786\n",
       "I prefer not to say                                      1086\n",
       "Retired                                                   168\n",
       "Name: EmploymentStatus, dtype: int64"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unique options and frequency of EmploymentStatus variable\n",
    "df.EmploymentStatus.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "I'm not actively looking, but I am open to new opportunities    20729\n",
       "I am not interested in new job opportunities                     8280\n",
       "I am actively looking for a job                                  4371\n",
       "Name: JobSeekingStatus, dtype: int64"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# # Unique options and frequency of JobSeekingStatus variable\n",
    "df.JobSeekingStatus.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "# statuses of people who are employed in some way\n",
    "employment_statuses = ['Employed full-time', 'Independent contractor, freelancer, or self-employed', 'Employed part-time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# filtering by the above statuses and people who are looking for a job\n",
    "df_filtered = df[(df['EmploymentStatus'].isin(employment_statuses)) & (df['JobSeekingStatus'] == 'I am actively looking for a job')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'6.46%'"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# percentage of people who are employed and looking for a job\n",
    "f'{(len(df_filtered) / len(df)) * 100:.2f}%'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the entire dataset **6.46%** of respondents are employed but looking for a job. Let's check if these people are underpaid and how is their job satisfaction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Somewhat underpaid                47.755102\n",
       "Greatly underpaid                 25.306122\n",
       "Neither underpaid nor overpaid    20.204082\n",
       "Somewhat overpaid                  5.306122\n",
       "Greatly overpaid                   1.428571\n",
       "Name: Overpaid, dtype: float64"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Percentages of people who are either underpaid or overpaid\n",
    "overpayment = (df_filtered['Overpaid'].value_counts() / df_filtered['Overpaid'].count()) * 100\n",
    "overpayment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PLOT-1\n",
    "\n",
    "ax= overpayment.plot.barh()\n",
    "ax.set_xlabel('Count', fontsize=15)\n",
    "ax.set_ylabel('Overpayment answers', fontsize=15)\n",
    "ax.set_title('Overpayment proportion of people who are employed but looking for a job', fontsize=15);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "70.4908160192713"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking the proportion of null values\n",
    "df_filtered.Overpaid.isna().mean() * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0     161\n",
       "1.0     111\n",
       "2.0     230\n",
       "3.0     355\n",
       "4.0     318\n",
       "5.0     506\n",
       "6.0     431\n",
       "7.0     354\n",
       "8.0     222\n",
       "9.0     102\n",
       "10.0     95\n",
       "Name: JobSatisfaction, dtype: int64"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "satisfaction = df_filtered['JobSatisfaction'].value_counts().sort_index()\n",
    "satisfaction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PLOT-2\n",
    "\n",
    "ax = satisfaction.plot.bar(alpha=0.7, legend=True)\n",
    "plt.axvline(df_filtered['JobSatisfaction'].mean(), color='r', label='Average satisfaction')\n",
    "plt.legend(fontsize=15)\n",
    "ax.set_xlabel('Job satisfaction', fontsize=15)\n",
    "ax.set_ylabel('N. of people', fontsize=15)\n",
    "ax.set_title('Job satisfaction rates', fontsize=15);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Result evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is clear that most people in this subset are **underpaid**, **73%** aproximately(take a look at **PLOT-1**). Though this would be a good metric to conclude about the reasons, there is a lot of uncertainty because the variable \"Overpaid\" has **70%** of null values.  \n",
    "\n",
    "As you can see in **PLOT-2**, the job satisfaction fractions are greater in the left side from the Average. This tell us that people within this subset often have lower job satisfaction than the average: **4.9**. "
   ]
  }
 ],
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