Main.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn import preprocessing\n",
    "from sklearn import linear_model\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import model_selection\n",
    "from sklearn import metrics\n",
    "import math\n",
    "import seaborn as sns\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_2019 = pd.read_csv(\"./survey_results_public_2019.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Respondent', 'MainBranch', 'Hobbyist', 'OpenSourcer', 'OpenSource',\n",
       "       'Employment', 'Country', 'Student', 'EdLevel', 'UndergradMajor',\n",
       "       'EduOther', 'OrgSize', 'DevType', 'YearsCode', 'Age1stCode',\n",
       "       'YearsCodePro', 'CareerSat', 'JobSat', 'MgrIdiot', 'MgrMoney',\n",
       "       'MgrWant', 'JobSeek', 'LastHireDate', 'LastInt', 'FizzBuzz',\n",
       "       'JobFactors', 'ResumeUpdate', 'CurrencySymbol', 'CurrencyDesc',\n",
       "       'CompTotal', 'CompFreq', 'ConvertedComp', 'WorkWeekHrs', 'WorkPlan',\n",
       "       'WorkChallenge', 'WorkRemote', 'WorkLoc', 'ImpSyn', 'CodeRev',\n",
       "       'CodeRevHrs', 'UnitTests', 'PurchaseHow', 'PurchaseWhat',\n",
       "       'LanguageWorkedWith', 'LanguageDesireNextYear', 'DatabaseWorkedWith',\n",
       "       'DatabaseDesireNextYear', 'PlatformWorkedWith',\n",
       "       'PlatformDesireNextYear', 'WebFrameWorkedWith',\n",
       "       'WebFrameDesireNextYear', 'MiscTechWorkedWith',\n",
       "       'MiscTechDesireNextYear', 'DevEnviron', 'OpSys', 'Containers',\n",
       "       'BlockchainOrg', 'BlockchainIs', 'BetterLife', 'ITperson', 'OffOn',\n",
       "       'SocialMedia', 'Extraversion', 'ScreenName', 'SOVisit1st',\n",
       "       'SOVisitFreq', 'SOVisitTo', 'SOFindAnswer', 'SOTimeSaved',\n",
       "       'SOHowMuchTime', 'SOAccount', 'SOPartFreq', 'SOJobs', 'EntTeams',\n",
       "       'SOComm', 'WelcomeChange', 'SONewContent', 'Age', 'Gender', 'Trans',\n",
       "       'Sexuality', 'Ethnicity', 'Dependents', 'SurveyLength', 'SurveyEase'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_2019.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                                   NaN\n",
       "1     Developer, desktop or enterprise applications;...\n",
       "2     Designer;Developer, back-end;Developer, front-...\n",
       "3                                 Developer, full-stack\n",
       "4     Academic researcher;Developer, desktop or ente...\n",
       "5     Data or business analyst;Data scientist or mac...\n",
       "6                         Designer;Developer, front-end\n",
       "7        Developer, back-end;Engineer, site reliability\n",
       "8     Database administrator;Developer, back-end;Dev...\n",
       "9     Data or business analyst;Data scientist or mac...\n",
       "10                                                  NaN\n",
       "11    Data or business analyst;Data scientist or mac...\n",
       "12    Data or business analyst;Database administrato...\n",
       "13        Developer, desktop or enterprise applications\n",
       "14                                              Student\n",
       "15                                Developer, full-stack\n",
       "16    Developer, back-end;Developer, front-end;Devel...\n",
       "17                             Data or business analyst\n",
       "18                                Developer, full-stack\n",
       "19    Database administrator;Designer;Developer, bac...\n",
       "Name: DevType, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_2019['DevType'].head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "languages = raw_2019[['Respondent', 'LanguageWorkedWith']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = languages['LanguageWorkedWith'].str.split(';', expand=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = []\n",
    "for i in range(28):\n",
    "    for j in b[i].unique():\n",
    "        l.append(j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_lang = list(dict.fromkeys(l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = raw_2019[['Respondent', 'Employment', 'EdLevel', 'UndergradMajor', 'OrgSize','DevType', 'YearsCode', 'YearsCodePro', 'ConvertedComp', 'Age', 'Gender', 'Country']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Employment</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>DevType</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>YearsCodePro</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Not employed, and not looking for work</td>\n",
       "      <td>Primary/elementary school</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Not employed, but looking for work</td>\n",
       "      <td>Secondary school (e.g. American high school, G...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Developer, desktop or enterprise applications;...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Web development or web design</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>Designer;Developer, back-end;Developer, front-...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8820.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Thailand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>Developer, full-stack</td>\n",
       "      <td>3</td>\n",
       "      <td>Less than 1 year</td>\n",
       "      <td>61000.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>Academic researcher;Developer, desktop or ente...</td>\n",
       "      <td>16</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Ukraine</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Respondent                              Employment  \\\n",
       "0           1  Not employed, and not looking for work   \n",
       "1           2      Not employed, but looking for work   \n",
       "2           3                      Employed full-time   \n",
       "3           4                      Employed full-time   \n",
       "4           5                      Employed full-time   \n",
       "\n",
       "                                             EdLevel  \\\n",
       "0                          Primary/elementary school   \n",
       "1  Secondary school (e.g. American high school, G...   \n",
       "2           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "3           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "4           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "\n",
       "                                      UndergradMajor  \\\n",
       "0                                                NaN   \n",
       "1                                                NaN   \n",
       "2                      Web development or web design   \n",
       "3  Computer science, computer engineering, or sof...   \n",
       "4  Computer science, computer engineering, or sof...   \n",
       "\n",
       "                    OrgSize  \\\n",
       "0                       NaN   \n",
       "1                       NaN   \n",
       "2      100 to 499 employees   \n",
       "3      100 to 499 employees   \n",
       "4  10,000 or more employees   \n",
       "\n",
       "                                             DevType YearsCode  \\\n",
       "0                                                NaN         4   \n",
       "1  Developer, desktop or enterprise applications;...       NaN   \n",
       "2  Designer;Developer, back-end;Developer, front-...         3   \n",
       "3                              Developer, full-stack         3   \n",
       "4  Academic researcher;Developer, desktop or ente...        16   \n",
       "\n",
       "       YearsCodePro  ConvertedComp   Age Gender                 Country  \n",
       "0               NaN            NaN  14.0    Man          United Kingdom  \n",
       "1               NaN            NaN  19.0    Man  Bosnia and Herzegovina  \n",
       "2                 1         8820.0  28.0    Man                Thailand  \n",
       "3  Less than 1 year        61000.0  22.0    Man           United States  \n",
       "4                 9            NaN  30.0    Man                 Ukraine  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(88883, 12)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019[~df_2019['ConvertedComp'].isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_by_country = df_2019.groupby(by=['Country'])['ConvertedComp'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019.merge(avg_by_country, left_on='Country', right_index=True, how='left').rename(columns={'ConvertedComp_x':'ConvertedComp', 'ConvertedComp_y':'CountryAvgComp'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_by_ed_lvl = df_2019.groupby(by=['EdLevel'])['ConvertedComp'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019.merge(avg_by_ed_lvl, left_on='EdLevel', right_index=True, how='left').rename(columns={'ConvertedComp_x':'ConvertedComp', 'ConvertedComp_y':'EducationAvgComp'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_by_major = df_2019.groupby(by=['UndergradMajor'])['ConvertedComp'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019.merge(avg_by_major, left_on='UndergradMajor', right_index=True, how='left').rename(columns={'ConvertedComp_x':'ConvertedComp', 'ConvertedComp_y':'MajorAvgComp'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Employment</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>DevType</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>YearsCodePro</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Country</th>\n",
       "      <th>CountryAvgComp</th>\n",
       "      <th>EducationAvgComp</th>\n",
       "      <th>MajorAvgComp</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gender</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Man</td>\n",
       "      <td>50503</td>\n",
       "      <td>50387</td>\n",
       "      <td>49787</td>\n",
       "      <td>46367</td>\n",
       "      <td>49671</td>\n",
       "      <td>49872</td>\n",
       "      <td>50441</td>\n",
       "      <td>50377</td>\n",
       "      <td>50503</td>\n",
       "      <td>48735</td>\n",
       "      <td>50503</td>\n",
       "      <td>50503</td>\n",
       "      <td>49787</td>\n",
       "      <td>46367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Man;Non-binary, genderqueer, or gender non-conforming</td>\n",
       "      <td>115</td>\n",
       "      <td>115</td>\n",
       "      <td>111</td>\n",
       "      <td>112</td>\n",
       "      <td>113</td>\n",
       "      <td>114</td>\n",
       "      <td>115</td>\n",
       "      <td>115</td>\n",
       "      <td>115</td>\n",
       "      <td>113</td>\n",
       "      <td>115</td>\n",
       "      <td>115</td>\n",
       "      <td>111</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Non-binary, genderqueer, or gender non-conforming</td>\n",
       "      <td>342</td>\n",
       "      <td>341</td>\n",
       "      <td>334</td>\n",
       "      <td>300</td>\n",
       "      <td>333</td>\n",
       "      <td>335</td>\n",
       "      <td>339</td>\n",
       "      <td>338</td>\n",
       "      <td>342</td>\n",
       "      <td>318</td>\n",
       "      <td>342</td>\n",
       "      <td>342</td>\n",
       "      <td>334</td>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Woman</td>\n",
       "      <td>3762</td>\n",
       "      <td>3754</td>\n",
       "      <td>3701</td>\n",
       "      <td>3500</td>\n",
       "      <td>3660</td>\n",
       "      <td>3703</td>\n",
       "      <td>3759</td>\n",
       "      <td>3747</td>\n",
       "      <td>3762</td>\n",
       "      <td>3642</td>\n",
       "      <td>3762</td>\n",
       "      <td>3762</td>\n",
       "      <td>3701</td>\n",
       "      <td>3500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Woman;Man</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>39</td>\n",
       "      <td>35</td>\n",
       "      <td>40</td>\n",
       "      <td>39</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>39</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Woman;Man;Non-binary, genderqueer, or gender non-conforming</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>16</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Woman;Non-binary, genderqueer, or gender non-conforming</td>\n",
       "      <td>106</td>\n",
       "      <td>106</td>\n",
       "      <td>106</td>\n",
       "      <td>88</td>\n",
       "      <td>103</td>\n",
       "      <td>105</td>\n",
       "      <td>104</td>\n",
       "      <td>106</td>\n",
       "      <td>106</td>\n",
       "      <td>105</td>\n",
       "      <td>106</td>\n",
       "      <td>106</td>\n",
       "      <td>106</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Respondent  Employment  \\\n",
       "Gender                                                                       \n",
       "Man                                                      50503       50387   \n",
       "Man;Non-binary, genderqueer, or gender non-conf...         115         115   \n",
       "Non-binary, genderqueer, or gender non-conforming          342         341   \n",
       "Woman                                                     3762        3754   \n",
       "Woman;Man                                                   40          40   \n",
       "Woman;Man;Non-binary, genderqueer, or gender no...          25          24   \n",
       "Woman;Non-binary, genderqueer, or gender non-co...         106         106   \n",
       "\n",
       "                                                    EdLevel  UndergradMajor  \\\n",
       "Gender                                                                        \n",
       "Man                                                   49787           46367   \n",
       "Man;Non-binary, genderqueer, or gender non-conf...      111             112   \n",
       "Non-binary, genderqueer, or gender non-conforming       334             300   \n",
       "Woman                                                  3701            3500   \n",
       "Woman;Man                                                39              35   \n",
       "Woman;Man;Non-binary, genderqueer, or gender no...       22              16   \n",
       "Woman;Non-binary, genderqueer, or gender non-co...      106              88   \n",
       "\n",
       "                                                    OrgSize  DevType  \\\n",
       "Gender                                                                 \n",
       "Man                                                   49671    49872   \n",
       "Man;Non-binary, genderqueer, or gender non-conf...      113      114   \n",
       "Non-binary, genderqueer, or gender non-conforming       333      335   \n",
       "Woman                                                  3660     3703   \n",
       "Woman;Man                                                40       39   \n",
       "Woman;Man;Non-binary, genderqueer, or gender no...       24       24   \n",
       "Woman;Non-binary, genderqueer, or gender non-co...      103      105   \n",
       "\n",
       "                                                    YearsCode  YearsCodePro  \\\n",
       "Gender                                                                        \n",
       "Man                                                     50441         50377   \n",
       "Man;Non-binary, genderqueer, or gender non-conf...        115           115   \n",
       "Non-binary, genderqueer, or gender non-conforming         339           338   \n",
       "Woman                                                    3759          3747   \n",
       "Woman;Man                                                  40            40   \n",
       "Woman;Man;Non-binary, genderqueer, or gender no...         22            22   \n",
       "Woman;Non-binary, genderqueer, or gender non-co...        104           106   \n",
       "\n",
       "                                                    ConvertedComp    Age  \\\n",
       "Gender                                                                     \n",
       "Man                                                         50503  48735   \n",
       "Man;Non-binary, genderqueer, or gender non-conf...            115    113   \n",
       "Non-binary, genderqueer, or gender non-conforming             342    318   \n",
       "Woman                                                        3762   3642   \n",
       "Woman;Man                                                      40     35   \n",
       "Woman;Man;Non-binary, genderqueer, or gender no...             25     22   \n",
       "Woman;Non-binary, genderqueer, or gender non-co...            106    105   \n",
       "\n",
       "                                                    Country  CountryAvgComp  \\\n",
       "Gender                                                                        \n",
       "Man                                                   50503           50503   \n",
       "Man;Non-binary, genderqueer, or gender non-conf...      115             115   \n",
       "Non-binary, genderqueer, or gender non-conforming       342             342   \n",
       "Woman                                                  3762            3762   \n",
       "Woman;Man                                                40              40   \n",
       "Woman;Man;Non-binary, genderqueer, or gender no...       25              25   \n",
       "Woman;Non-binary, genderqueer, or gender non-co...      106             106   \n",
       "\n",
       "                                                    EducationAvgComp  \\\n",
       "Gender                                                                 \n",
       "Man                                                            49787   \n",
       "Man;Non-binary, genderqueer, or gender non-conf...               111   \n",
       "Non-binary, genderqueer, or gender non-conforming                334   \n",
       "Woman                                                           3701   \n",
       "Woman;Man                                                         39   \n",
       "Woman;Man;Non-binary, genderqueer, or gender no...                22   \n",
       "Woman;Non-binary, genderqueer, or gender non-co...               106   \n",
       "\n",
       "                                                    MajorAvgComp  \n",
       "Gender                                                            \n",
       "Man                                                        46367  \n",
       "Man;Non-binary, genderqueer, or gender non-conf...           112  \n",
       "Non-binary, genderqueer, or gender non-conforming            300  \n",
       "Woman                                                       3500  \n",
       "Woman;Man                                                     35  \n",
       "Woman;Man;Non-binary, genderqueer, or gender no...            16  \n",
       "Woman;Non-binary, genderqueer, or gender non-co...            88  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019.groupby(by=['Gender']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019['Gender'] = df_2019['Gender'].fillna('Not Specified')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LabelEncoder()"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "le = preprocessing.LabelEncoder()\n",
    "le.fit(list(df_2019['Gender'].unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019['GenderCode'] = le.transform(df_2019['Gender'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019.loc[df_2019['OrgSize']=='1,000 to 4,999 employees', 'NewOrgSize'] = 3000\n",
    "df_2019.loc[df_2019['OrgSize']=='10 to 19 employees', 'NewOrgSize'] = 15\n",
    "df_2019.loc[df_2019['OrgSize']=='10,000 or more employees', 'NewOrgSize'] = 10000\n",
    "df_2019.loc[df_2019['OrgSize']=='100 to 499 employees', 'NewOrgSize'] = 300\n",
    "df_2019.loc[df_2019['OrgSize']=='2-9 employees', 'NewOrgSize'] = 5\n",
    "df_2019.loc[df_2019['OrgSize']=='20 to 99 employees', 'NewOrgSize'] = 60\n",
    "df_2019.loc[df_2019['OrgSize']=='5,000 to 9,999 employees', 'NewOrgSize'] = 7500\n",
    "df_2019.loc[df_2019['OrgSize']=='500 to 999 employees', 'NewOrgSize'] = 750\n",
    "df_2019.loc[df_2019['OrgSize']=='Just me - I am a freelancer, sole proprietor, etc.', 'NewOrgSize'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "orgSizeMean = df_2019['NewOrgSize'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019['NewOrgSize'] = df_2019['NewOrgSize'].fillna(value=orgSizeMean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "avgComp = df_2019['ConvertedComp'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019['EducationAvgComp'] = df_2019['EducationAvgComp'].fillna(value=avgComp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019['MajorAvgComp'] = df_2019['MajorAvgComp'].fillna(value=avgComp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019.reset_index().drop('index', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp1 = df_2019['DevType'].str.split(';', expand=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "      <th>23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Designer</td>\n",
       "      <td>Developer, back-end</td>\n",
       "      <td>Developer, front-end</td>\n",
       "      <td>Developer, full-stack</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Developer, full-stack</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Data or business analyst</td>\n",
       "      <td>Data scientist or machine learning specialist</td>\n",
       "      <td>Database administrator</td>\n",
       "      <td>Engineer, data</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Database administrator</td>\n",
       "      <td>Developer, back-end</td>\n",
       "      <td>Developer, front-end</td>\n",
       "      <td>Developer, full-stack</td>\n",
       "      <td>Developer, QA or test</td>\n",
       "      <td>DevOps specialist</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Data or business analyst</td>\n",
       "      <td>Data scientist or machine learning specialist</td>\n",
       "      <td>Database administrator</td>\n",
       "      <td>Developer, back-end</td>\n",
       "      <td>Developer, desktop or enterprise applications</td>\n",
       "      <td>Developer, front-end</td>\n",
       "      <td>Developer, full-stack</td>\n",
       "      <td>Developer, game or graphics</td>\n",
       "      <td>Educator</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         0                                              1   \\\n",
       "0                  Designer                            Developer, back-end   \n",
       "1     Developer, full-stack                                           None   \n",
       "2  Data or business analyst  Data scientist or machine learning specialist   \n",
       "3    Database administrator                            Developer, back-end   \n",
       "4  Data or business analyst  Data scientist or machine learning specialist   \n",
       "\n",
       "                       2                      3   \\\n",
       "0    Developer, front-end  Developer, full-stack   \n",
       "1                    None                   None   \n",
       "2  Database administrator         Engineer, data   \n",
       "3    Developer, front-end  Developer, full-stack   \n",
       "4  Database administrator    Developer, back-end   \n",
       "\n",
       "                                              4                     5   \\\n",
       "0                                           None                  None   \n",
       "1                                           None                  None   \n",
       "2                                           None                  None   \n",
       "3                          Developer, QA or test     DevOps specialist   \n",
       "4  Developer, desktop or enterprise applications  Developer, front-end   \n",
       "\n",
       "                      6                            7         8     9   ...  \\\n",
       "0                   None                         None      None  None  ...   \n",
       "1                   None                         None      None  None  ...   \n",
       "2                   None                         None      None  None  ...   \n",
       "3                   None                         None      None  None  ...   \n",
       "4  Developer, full-stack  Developer, game or graphics  Educator  None  ...   \n",
       "\n",
       "     14    15    16    17    18    19    20    21    22    23  \n",
       "0  None  None  None  None  None  None  None  None  None  None  \n",
       "1  None  None  None  None  None  None  None  None  None  None  \n",
       "2  None  None  None  None  None  None  None  None  None  None  \n",
       "3  None  None  None  None  None  None  None  None  None  None  \n",
       "4  None  None  None  None  None  None  None  None  None  None  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(55823, 24)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:3: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "all_positions = []\n",
    "for row in range(temp1.shape[0]):\n",
    "    j = temp1.iloc[row].as_matrix()\n",
    "    for position in j:\n",
    "        if position not in all_positions:\n",
    "            all_positions.append(position)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_positions.remove(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_positions.pop(-2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_positions.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Academic researcher',\n",
       " 'Data or business analyst',\n",
       " 'Data scientist or machine learning specialist',\n",
       " 'Database administrator',\n",
       " 'Designer',\n",
       " 'DevOps specialist',\n",
       " 'Developer, QA or test',\n",
       " 'Developer, back-end',\n",
       " 'Developer, desktop or enterprise applications',\n",
       " 'Developer, embedded applications or devices',\n",
       " 'Developer, front-end',\n",
       " 'Developer, full-stack',\n",
       " 'Developer, game or graphics',\n",
       " 'Developer, mobile',\n",
       " 'Educator',\n",
       " 'Engineer, data',\n",
       " 'Engineer, site reliability',\n",
       " 'Engineering manager',\n",
       " 'Marketing or sales professional',\n",
       " 'Product manager',\n",
       " 'Scientist',\n",
       " 'Senior executive/VP',\n",
       " 'Student',\n",
       " 'System administrator']"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_positions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in all_positions:\n",
    "    df_2019[i] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_positions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "for i in range(temp1.shape[0]):\n",
    "    j = list(temp1.iloc[i].as_matrix())\n",
    "    for item in j:\n",
    "        if type(item)==type('str'):\n",
    "            df_2019.at[i, item] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>Academic researcher</th>\n",
       "      <th>Data or business analyst</th>\n",
       "      <th>Data scientist or machine learning specialist</th>\n",
       "      <th>Database administrator</th>\n",
       "      <th>Designer</th>\n",
       "      <th>DevOps specialist</th>\n",
       "      <th>Developer, QA or test</th>\n",
       "      <th>Developer, back-end</th>\n",
       "      <th>Developer, desktop or enterprise applications</th>\n",
       "      <th>Developer, embedded applications or devices</th>\n",
       "      <th>...</th>\n",
       "      <th>Educator</th>\n",
       "      <th>Engineer, data</th>\n",
       "      <th>Engineer, site reliability</th>\n",
       "      <th>Engineering manager</th>\n",
       "      <th>Marketing or sales professional</th>\n",
       "      <th>Product manager</th>\n",
       "      <th>Scientist</th>\n",
       "      <th>Senior executive/VP</th>\n",
       "      <th>Student</th>\n",
       "      <th>System administrator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Academic researcher  Data or business analyst  \\\n",
       "0                     0                         0   \n",
       "1                     0                         0   \n",
       "2                     0                         1   \n",
       "3                     0                         0   \n",
       "4                     0                         1   \n",
       "5                     0                         1   \n",
       "6                     0                         0   \n",
       "7                     0                         0   \n",
       "8                     0                         0   \n",
       "9                     0                         1   \n",
       "10                    0                         0   \n",
       "11                    0                         0   \n",
       "12                    0                         1   \n",
       "13                    0                         0   \n",
       "14                    0                         0   \n",
       "15                    0                         0   \n",
       "16                    0                         0   \n",
       "17                    0                         0   \n",
       "18                    0                         0   \n",
       "19                    0                         0   \n",
       "\n",
       "    Data scientist or machine learning specialist  Database administrator  \\\n",
       "0                                               0                       0   \n",
       "1                                               0                       0   \n",
       "2                                               1                       1   \n",
       "3                                               0                       1   \n",
       "4                                               1                       1   \n",
       "5                                               0                       1   \n",
       "6                                               0                       0   \n",
       "7                                               0                       0   \n",
       "8                                               0                       0   \n",
       "9                                               0                       0   \n",
       "10                                              0                       0   \n",
       "11                                              0                       1   \n",
       "12                                              0                       0   \n",
       "13                                              0                       0   \n",
       "14                                              0                       0   \n",
       "15                                              0                       0   \n",
       "16                                              0                       0   \n",
       "17                                              0                       0   \n",
       "18                                              0                       0   \n",
       "19                                              0                       0   \n",
       "\n",
       "    Designer  DevOps specialist  Developer, QA or test  Developer, back-end  \\\n",
       "0          1                  0                      0                    1   \n",
       "1          0                  0                      0                    0   \n",
       "2          0                  0                      0                    0   \n",
       "3          0                  1                      1                    1   \n",
       "4          0                  0                      0                    1   \n",
       "5          0                  1                      0                    1   \n",
       "6          0                  0                      0                    0   \n",
       "7          0                  0                      0                    0   \n",
       "8          0                  0                      0                    1   \n",
       "9          0                  0                      0                    0   \n",
       "10         0                  0                      0                    0   \n",
       "11         1                  0                      0                    1   \n",
       "12         1                  1                      0                    1   \n",
       "13         0                  0                      0                    0   \n",
       "14         0                  0                      0                    0   \n",
       "15         1                  0                      0                    1   \n",
       "16         1                  0                      1                    1   \n",
       "17         0                  0                      0                    0   \n",
       "18         0                  1                      0                    0   \n",
       "19         0                  0                      0                    0   \n",
       "\n",
       "    Developer, desktop or enterprise applications  \\\n",
       "0                                               0   \n",
       "1                                               0   \n",
       "2                                               0   \n",
       "3                                               0   \n",
       "4                                               1   \n",
       "5                                               1   \n",
       "6                                               1   \n",
       "7                                               0   \n",
       "8                                               0   \n",
       "9                                               0   \n",
       "10                                              0   \n",
       "11                                              0   \n",
       "12                                              1   \n",
       "13                                              0   \n",
       "14                                              0   \n",
       "15                                              0   \n",
       "16                                              1   \n",
       "17                                              0   \n",
       "18                                              0   \n",
       "19                                              0   \n",
       "\n",
       "    Developer, embedded applications or devices  ...  Educator  \\\n",
       "0                                             0  ...         0   \n",
       "1                                             0  ...         0   \n",
       "2                                             0  ...         0   \n",
       "3                                             0  ...         0   \n",
       "4                                             0  ...         1   \n",
       "5                                             0  ...         0   \n",
       "6                                             0  ...         0   \n",
       "7                                             0  ...         0   \n",
       "8                                             0  ...         0   \n",
       "9                                             0  ...         0   \n",
       "10                                            0  ...         0   \n",
       "11                                            1  ...         0   \n",
       "12                                            0  ...         0   \n",
       "13                                            0  ...         0   \n",
       "14                                            0  ...         0   \n",
       "15                                            0  ...         0   \n",
       "16                                            1  ...         1   \n",
       "17                                            0  ...         1   \n",
       "18                                            0  ...         0   \n",
       "19                                            0  ...         0   \n",
       "\n",
       "    Engineer, data  Engineer, site reliability  Engineering manager  \\\n",
       "0                0                           0                    0   \n",
       "1                0                           0                    0   \n",
       "2                1                           0                    0   \n",
       "3                0                           0                    0   \n",
       "4                0                           0                    0   \n",
       "5                1                           1                    1   \n",
       "6                0                           0                    0   \n",
       "7                0                           0                    0   \n",
       "8                0                           0                    0   \n",
       "9                0                           0                    0   \n",
       "10               0                           0                    0   \n",
       "11               0                           0                    0   \n",
       "12               0                           0                    0   \n",
       "13               0                           0                    0   \n",
       "14               0                           0                    0   \n",
       "15               0                           0                    0   \n",
       "16               0                           0                    1   \n",
       "17               0                           0                    0   \n",
       "18               0                           1                    0   \n",
       "19               0                           0                    0   \n",
       "\n",
       "    Marketing or sales professional  Product manager  Scientist  \\\n",
       "0                                 0                0          0   \n",
       "1                                 0                0          0   \n",
       "2                                 0                0          0   \n",
       "3                                 0                0          0   \n",
       "4                                 0                0          0   \n",
       "5                                 0                0          0   \n",
       "6                                 0                0          0   \n",
       "7                                 0                0          0   \n",
       "8                                 0                0          0   \n",
       "9                                 0                0          0   \n",
       "10                                0                0          0   \n",
       "11                                0                0          0   \n",
       "12                                0                0          0   \n",
       "13                                0                0          0   \n",
       "14                                0                0          0   \n",
       "15                                0                0          0   \n",
       "16                                0                1          0   \n",
       "17                                0                0          0   \n",
       "18                                0                0          0   \n",
       "19                                0                0          0   \n",
       "\n",
       "    Senior executive/VP  Student  System administrator  \n",
       "0                     0        0                     0  \n",
       "1                     0        0                     0  \n",
       "2                     0        0                     0  \n",
       "3                     0        0                     0  \n",
       "4                     0        0                     0  \n",
       "5                     1        0                     1  \n",
       "6                     0        0                     0  \n",
       "7                     0        0                     0  \n",
       "8                     0        1                     0  \n",
       "9                     0        0                     0  \n",
       "10                    0        0                     0  \n",
       "11                    0        0                     1  \n",
       "12                    0        0                     1  \n",
       "13                    0        0                     0  \n",
       "14                    0        0                     0  \n",
       "15                    0        0                     0  \n",
       "16                    0        0                     0  \n",
       "17                    0        0                     0  \n",
       "18                    0        0                     0  \n",
       "19                    0        0                     0  \n",
       "\n",
       "[20 rows x 24 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019[all_positions].head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019.drop(['DevType', 'YearsCodePro'], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Respondent', 'Employment', 'EdLevel', 'UndergradMajor', 'OrgSize',\n",
       "       'YearsCode', 'ConvertedComp', 'Age', 'Gender', 'Country',\n",
       "       'CountryAvgComp', 'EducationAvgComp', 'MajorAvgComp', 'GenderCode',\n",
       "       'NewOrgSize', 'Academic researcher', 'Data or business analyst',\n",
       "       'Data scientist or machine learning specialist',\n",
       "       'Database administrator', 'Designer', 'DevOps specialist',\n",
       "       'Developer, QA or test', 'Developer, back-end',\n",
       "       'Developer, desktop or enterprise applications',\n",
       "       'Developer, embedded applications or devices', 'Developer, front-end',\n",
       "       'Developer, full-stack', 'Developer, game or graphics',\n",
       "       'Developer, mobile', 'Educator', 'Engineer, data',\n",
       "       'Engineer, site reliability', 'Engineering manager',\n",
       "       'Marketing or sales professional', 'Product manager', 'Scientist',\n",
       "       'Senior executive/VP', 'Student', 'System administrator'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Respondent', 'MainBranch', 'Hobbyist', 'OpenSourcer', 'OpenSource',\n",
       "       'Employment', 'Country', 'Student', 'EdLevel', 'UndergradMajor',\n",
       "       'EduOther', 'OrgSize', 'DevType', 'YearsCode', 'Age1stCode',\n",
       "       'YearsCodePro', 'CareerSat', 'JobSat', 'MgrIdiot', 'MgrMoney',\n",
       "       'MgrWant', 'JobSeek', 'LastHireDate', 'LastInt', 'FizzBuzz',\n",
       "       'JobFactors', 'ResumeUpdate', 'CurrencySymbol', 'CurrencyDesc',\n",
       "       'CompTotal', 'CompFreq', 'ConvertedComp', 'WorkWeekHrs', 'WorkPlan',\n",
       "       'WorkChallenge', 'WorkRemote', 'WorkLoc', 'ImpSyn', 'CodeRev',\n",
       "       'CodeRevHrs', 'UnitTests', 'PurchaseHow', 'PurchaseWhat',\n",
       "       'LanguageWorkedWith', 'LanguageDesireNextYear', 'DatabaseWorkedWith',\n",
       "       'DatabaseDesireNextYear', 'PlatformWorkedWith',\n",
       "       'PlatformDesireNextYear', 'WebFrameWorkedWith',\n",
       "       'WebFrameDesireNextYear', 'MiscTechWorkedWith',\n",
       "       'MiscTechDesireNextYear', 'DevEnviron', 'OpSys', 'Containers',\n",
       "       'BlockchainOrg', 'BlockchainIs', 'BetterLife', 'ITperson', 'OffOn',\n",
       "       'SocialMedia', 'Extraversion', 'ScreenName', 'SOVisit1st',\n",
       "       'SOVisitFreq', 'SOVisitTo', 'SOFindAnswer', 'SOTimeSaved',\n",
       "       'SOHowMuchTime', 'SOAccount', 'SOPartFreq', 'SOJobs', 'EntTeams',\n",
       "       'SOComm', 'WelcomeChange', 'SONewContent', 'Age', 'Gender', 'Trans',\n",
       "       'Sexuality', 'Ethnicity', 'Dependents', 'SurveyLength', 'SurveyEase'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_2019.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019.merge(raw_2019[['Respondent', 'LanguageWorkedWith', 'DatabaseWorkedWith', 'PlatformWorkedWith', 'WebFrameWorkedWith']], on='Respondent', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp2 = df_2019['LanguageWorkedWith'].str.split(';', expand=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:3: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "all_languages = []\n",
    "for row in range(temp2.shape[0]):\n",
    "    j = temp2.iloc[row].as_matrix()\n",
    "    for language in j:\n",
    "        if language not in all_languages:\n",
    "            all_languages.append(language)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_languages.remove(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_languages.pop(-10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_languages.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Assembly',\n",
       " 'Bash/Shell/PowerShell',\n",
       " 'C',\n",
       " 'C#',\n",
       " 'C++',\n",
       " 'Clojure',\n",
       " 'Dart',\n",
       " 'Elixir',\n",
       " 'Erlang',\n",
       " 'F#',\n",
       " 'Go',\n",
       " 'HTML/CSS',\n",
       " 'Java',\n",
       " 'JavaScript',\n",
       " 'Kotlin',\n",
       " 'Objective-C',\n",
       " 'Other(s):',\n",
       " 'PHP',\n",
       " 'Python',\n",
       " 'R',\n",
       " 'Ruby',\n",
       " 'Rust',\n",
       " 'SQL',\n",
       " 'Scala',\n",
       " 'Swift',\n",
       " 'TypeScript',\n",
       " 'VBA',\n",
       " 'WebAssembly']"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_languages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in all_languages:\n",
    "    df_2019[i] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "      <th>23</th>\n",
       "      <th>24</th>\n",
       "      <th>25</th>\n",
       "      <th>26</th>\n",
       "      <th>27</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>HTML/CSS</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>C</td>\n",
       "      <td>C++</td>\n",
       "      <td>C#</td>\n",
       "      <td>Python</td>\n",
       "      <td>SQL</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Java</td>\n",
       "      <td>R</td>\n",
       "      <td>SQL</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Bash/Shell/PowerShell</td>\n",
       "      <td>C#</td>\n",
       "      <td>HTML/CSS</td>\n",
       "      <td>JavaScript</td>\n",
       "      <td>Python</td>\n",
       "      <td>Ruby</td>\n",
       "      <td>Rust</td>\n",
       "      <td>SQL</td>\n",
       "      <td>TypeScript</td>\n",
       "      <td>WebAssembly</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>C#</td>\n",
       "      <td>Go</td>\n",
       "      <td>JavaScript</td>\n",
       "      <td>Python</td>\n",
       "      <td>R</td>\n",
       "      <td>SQL</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      0     1           2           3       4     5     6   \\\n",
       "0               HTML/CSS  None        None        None    None  None  None   \n",
       "1                      C   C++          C#      Python     SQL  None  None   \n",
       "2                   Java     R         SQL        None    None  None  None   \n",
       "3  Bash/Shell/PowerShell    C#    HTML/CSS  JavaScript  Python  Ruby  Rust   \n",
       "4                     C#    Go  JavaScript      Python       R   SQL  None   \n",
       "\n",
       "     7           8            9   ...    18    19    20    21    22    23  \\\n",
       "0  None        None         None  ...  None  None  None  None  None  None   \n",
       "1  None        None         None  ...  None  None  None  None  None  None   \n",
       "2  None        None         None  ...  None  None  None  None  None  None   \n",
       "3   SQL  TypeScript  WebAssembly  ...  None  None  None  None  None  None   \n",
       "4  None        None         None  ...  None  None  None  None  None  None   \n",
       "\n",
       "     24    25    26    27  \n",
       "0  None  None  None  None  \n",
       "1  None  None  None  None  \n",
       "2  None  None  None  None  \n",
       "3  None  None  None  None  \n",
       "4  None  None  None  None  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "for i in range(temp2.shape[0]):\n",
    "    j = list(temp2.iloc[i].as_matrix())\n",
    "    for item in j:\n",
    "        if type(item)==type('str'):\n",
    "            df_2019.at[i, item] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": true
   },
   "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>Assembly</th>\n",
       "      <th>Bash/Shell/PowerShell</th>\n",
       "      <th>C</th>\n",
       "      <th>C#</th>\n",
       "      <th>C++</th>\n",
       "      <th>Clojure</th>\n",
       "      <th>Dart</th>\n",
       "      <th>Elixir</th>\n",
       "      <th>Erlang</th>\n",
       "      <th>F#</th>\n",
       "      <th>...</th>\n",
       "      <th>Python</th>\n",
       "      <th>R</th>\n",
       "      <th>Ruby</th>\n",
       "      <th>Rust</th>\n",
       "      <th>SQL</th>\n",
       "      <th>Scala</th>\n",
       "      <th>Swift</th>\n",
       "      <th>TypeScript</th>\n",
       "      <th>VBA</th>\n",
       "      <th>WebAssembly</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55818</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55819</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55820</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55821</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55822</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>55823 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Assembly  Bash/Shell/PowerShell  C  C#  C++  Clojure  Dart  Elixir  \\\n",
       "0             0                      0  0   0    0        0     0       0   \n",
       "1             0                      0  1   1    1        0     0       0   \n",
       "2             0                      0  0   0    0        0     0       0   \n",
       "3             0                      1  0   1    0        0     0       0   \n",
       "4             0                      0  0   1    0        0     0       0   \n",
       "...         ...                    ... ..  ..  ...      ...   ...     ...   \n",
       "55818         0                      0  0   0    0        0     0       0   \n",
       "55819         0                      1  0   0    1        0     0       0   \n",
       "55820         0                      1  0   0    0        0     0       0   \n",
       "55821         0                      0  0   1    0        0     0       0   \n",
       "55822         0                      0  0   0    0        0     0       0   \n",
       "\n",
       "       Erlang  F#  ...  Python  R  Ruby  Rust  SQL  Scala  Swift  TypeScript  \\\n",
       "0           0   0  ...       0  0     0     0    0      0      0           0   \n",
       "1           0   0  ...       1  0     0     0    1      0      0           0   \n",
       "2           0   0  ...       0  1     0     0    1      0      0           0   \n",
       "3           0   0  ...       1  0     1     1    1      0      0           1   \n",
       "4           0   0  ...       1  1     0     0    1      0      0           0   \n",
       "...       ...  ..  ...     ... ..   ...   ...  ...    ...    ...         ...   \n",
       "55818       0   0  ...       0  0     0     0    0      1      0           1   \n",
       "55819       0   0  ...       1  0     0     0    0      0      0           0   \n",
       "55820       0   0  ...       1  0     0     0    0      0      0           0   \n",
       "55821       0   0  ...       1  0     0     0    0      0      0           0   \n",
       "55822       0   0  ...       0  0     0     0    0      0      0           0   \n",
       "\n",
       "       VBA  WebAssembly  \n",
       "0        0            0  \n",
       "1        0            0  \n",
       "2        0            0  \n",
       "3        0            1  \n",
       "4        0            0  \n",
       "...    ...          ...  \n",
       "55818    0            0  \n",
       "55819    0            0  \n",
       "55820    0            0  \n",
       "55821    0            0  \n",
       "55822    0            0  \n",
       "\n",
       "[55823 rows x 28 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019[~df_2019['Python'].isna()][all_languages]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Respondent', 'Employment', 'EdLevel', 'UndergradMajor', 'OrgSize',\n",
       "       'YearsCode', 'ConvertedComp', 'Age', 'Gender', 'Country',\n",
       "       'CountryAvgComp', 'EducationAvgComp', 'MajorAvgComp', 'GenderCode',\n",
       "       'NewOrgSize', 'Academic researcher', 'Data or business analyst',\n",
       "       'Data scientist or machine learning specialist',\n",
       "       'Database administrator', 'Designer', 'DevOps specialist',\n",
       "       'Developer, QA or test', 'Developer, back-end',\n",
       "       'Developer, desktop or enterprise applications',\n",
       "       'Developer, embedded applications or devices', 'Developer, front-end',\n",
       "       'Developer, full-stack', 'Developer, game or graphics',\n",
       "       'Developer, mobile', 'Educator', 'Engineer, data',\n",
       "       'Engineer, site reliability', 'Engineering manager',\n",
       "       'Marketing or sales professional', 'Product manager', 'Scientist',\n",
       "       'Senior executive/VP', 'Student', 'System administrator',\n",
       "       'LanguageWorkedWith', 'DatabaseWorkedWith', 'PlatformWorkedWith',\n",
       "       'WebFrameWorkedWith', 'Assembly', 'Bash/Shell/PowerShell', 'C', 'C#',\n",
       "       'C++', 'Clojure', 'Dart', 'Elixir', 'Erlang', 'F#', 'Go', 'HTML/CSS',\n",
       "       'Java', 'JavaScript', 'Kotlin', 'Objective-C', 'Other(s):', 'PHP',\n",
       "       'Python', 'R', 'Ruby', 'Rust', 'SQL', 'Scala', 'Swift', 'TypeScript',\n",
       "       'VBA', 'WebAssembly'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:5: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \"\"\"\n"
     ]
    }
   ],
   "source": [
    "temp3 = df_2019['DatabaseWorkedWith'].str.split(';', expand=True)\n",
    "\n",
    "all_DBs = []\n",
    "for row in range(temp3.shape[0]):\n",
    "    j = temp3.iloc[row].as_matrix()\n",
    "    for db in j:\n",
    "        if db not in all_DBs:\n",
    "            all_DBs.append(db)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "False\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "False\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "for i in all_DBs:\n",
    "    print(type(i)==type('str'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_DBs.remove(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_DBs.pop(-6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_DBs.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Cassandra',\n",
       " 'Couchbase',\n",
       " 'DynamoDB',\n",
       " 'Elasticsearch',\n",
       " 'Firebase',\n",
       " 'MariaDB',\n",
       " 'Microsoft SQL Server',\n",
       " 'MongoDB',\n",
       " 'MySQL',\n",
       " 'Oracle',\n",
       " 'Other(s):',\n",
       " 'PostgreSQL',\n",
       " 'Redis',\n",
       " 'SQLite']"
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_DBs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in all_DBs:\n",
    "    df_2019[i] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "for i in range(temp3.shape[0]):\n",
    "    j = list(temp3.iloc[i].as_matrix())\n",
    "    for item in j:\n",
    "        if type(item)==type('str'):\n",
    "            df_2019.at[i, item] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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>Employment</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>...</th>\n",
       "      <th>Elasticsearch</th>\n",
       "      <th>Firebase</th>\n",
       "      <th>MariaDB</th>\n",
       "      <th>Microsoft SQL Server</th>\n",
       "      <th>MongoDB</th>\n",
       "      <th>MySQL</th>\n",
       "      <th>Oracle</th>\n",
       "      <th>PostgreSQL</th>\n",
       "      <th>Redis</th>\n",
       "      <th>SQLite</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Web development or web design</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>3</td>\n",
       "      <td>8820.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Mathematics or statistics</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13</td>\n",
       "      <td>366420.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Canada</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Some college/university study without earning ...</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>10 to 19 employees</td>\n",
       "      <td>12</td>\n",
       "      <td>95179.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>17</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>5</td>\n",
       "      <td>65277.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Australia</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>32</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Associate degree</td>\n",
       "      <td>Information systems, information technology, o...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>3</td>\n",
       "      <td>1100000.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55815</td>\n",
       "      <td>88874</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>A social science (ex. anthropology, psychology...</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>7</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55818</td>\n",
       "      <td>88878</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>12</td>\n",
       "      <td>130000.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55820</td>\n",
       "      <td>88881</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>18</td>\n",
       "      <td>68745.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Austria</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55821</td>\n",
       "      <td>88882</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>10</td>\n",
       "      <td>588012.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Man</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55822</td>\n",
       "      <td>88883</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>9</td>\n",
       "      <td>22915.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Greece</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18207 rows × 84 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Respondent          Employment  \\\n",
       "0               3  Employed full-time   \n",
       "2               6  Employed full-time   \n",
       "3               9  Employed full-time   \n",
       "8              17  Employed full-time   \n",
       "19             32  Employed full-time   \n",
       "...           ...                 ...   \n",
       "55815       88874  Employed full-time   \n",
       "55818       88878  Employed full-time   \n",
       "55820       88881  Employed full-time   \n",
       "55821       88882  Employed full-time   \n",
       "55822       88883  Employed full-time   \n",
       "\n",
       "                                                 EdLevel  \\\n",
       "0               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "2               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "3      Some college/university study without earning ...   \n",
       "8               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "19                                      Associate degree   \n",
       "...                                                  ...   \n",
       "55815           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "55818           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "55820        Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "55821        Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "55822           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "\n",
       "                                          UndergradMajor  \\\n",
       "0                          Web development or web design   \n",
       "2                              Mathematics or statistics   \n",
       "3      Computer science, computer engineering, or sof...   \n",
       "8      Computer science, computer engineering, or sof...   \n",
       "19     Information systems, information technology, o...   \n",
       "...                                                  ...   \n",
       "55815  A social science (ex. anthropology, psychology...   \n",
       "55818  Computer science, computer engineering, or sof...   \n",
       "55820  Computer science, computer engineering, or sof...   \n",
       "55821  Computer science, computer engineering, or sof...   \n",
       "55822  Computer science, computer engineering, or sof...   \n",
       "\n",
       "                        OrgSize YearsCode  ConvertedComp   Age Gender  \\\n",
       "0          100 to 499 employees         3         8820.0  28.0    Man   \n",
       "2                           NaN        13       366420.0  28.0    Man   \n",
       "3            10 to 19 employees        12        95179.0  23.0    Man   \n",
       "8            20 to 99 employees         5        65277.0  29.0    Man   \n",
       "19         100 to 499 employees         3      1100000.0  21.0    Man   \n",
       "...                         ...       ...            ...   ...    ...   \n",
       "55815  10,000 or more employees         7      2000000.0  26.0    Man   \n",
       "55818        20 to 99 employees        12       130000.0  26.0    Man   \n",
       "55820      100 to 499 employees        18        68745.0  37.0    Man   \n",
       "55821      100 to 499 employees        10       588012.0   NaN    Man   \n",
       "55822        20 to 99 employees         9        22915.0  33.0    Man   \n",
       "\n",
       "             Country  ...  Elasticsearch  Firebase  MariaDB  \\\n",
       "0           Thailand  ...              0         0        0   \n",
       "2             Canada  ...              0         0        0   \n",
       "3        New Zealand  ...              0         0        0   \n",
       "8          Australia  ...              0         0        0   \n",
       "19     United States  ...              0         0        0   \n",
       "...              ...  ...            ...       ...      ...   \n",
       "55815  United States  ...              1         0        0   \n",
       "55818  United States  ...              0         0        0   \n",
       "55820        Austria  ...              0         0        0   \n",
       "55821    Netherlands  ...              0         0        1   \n",
       "55822         Greece  ...              0         0        1   \n",
       "\n",
       "       Microsoft SQL Server  MongoDB  MySQL  Oracle  PostgreSQL  Redis  SQLite  \n",
       "0                         0        0      0       0           1      0       0  \n",
       "2                         0        1      0       0           1      0       0  \n",
       "3                         0        0      0       0           1      0       1  \n",
       "8                         0        1      0       0           1      0       0  \n",
       "19                        0        1      0       0           1      1       0  \n",
       "...                     ...      ...    ...     ...         ...    ...     ...  \n",
       "55815                     0        0      0       0           1      0       1  \n",
       "55818                     0        0      0       0           1      0       0  \n",
       "55820                     0        0      0       0           1      1       0  \n",
       "55821                     0        0      0       0           1      0       0  \n",
       "55822                     0        0      0       0           1      0       1  \n",
       "\n",
       "[18207 rows x 84 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019[df_2019['PostgreSQL']==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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>Employment</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>...</th>\n",
       "      <th>Elasticsearch</th>\n",
       "      <th>Firebase</th>\n",
       "      <th>MariaDB</th>\n",
       "      <th>Microsoft SQL Server</th>\n",
       "      <th>MongoDB</th>\n",
       "      <th>MySQL</th>\n",
       "      <th>Oracle</th>\n",
       "      <th>PostgreSQL</th>\n",
       "      <th>Redis</th>\n",
       "      <th>SQLite</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Web development or web design</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>3</td>\n",
       "      <td>8820.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>3</td>\n",
       "      <td>61000.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Mathematics or statistics</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13</td>\n",
       "      <td>366420.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Canada</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Some college/university study without earning ...</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>10 to 19 employees</td>\n",
       "      <td>12</td>\n",
       "      <td>95179.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>12</td>\n",
       "      <td>13293.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not Specified</td>\n",
       "      <td>India</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55818</td>\n",
       "      <td>88878</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>12</td>\n",
       "      <td>130000.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55819</td>\n",
       "      <td>88879</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>17</td>\n",
       "      <td>82488.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Finland</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55820</td>\n",
       "      <td>88881</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>18</td>\n",
       "      <td>68745.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Austria</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55821</td>\n",
       "      <td>88882</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>10</td>\n",
       "      <td>588012.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Man</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55822</td>\n",
       "      <td>88883</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>9</td>\n",
       "      <td>22915.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Greece</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>55823 rows × 84 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Respondent          Employment  \\\n",
       "0               3  Employed full-time   \n",
       "1               4  Employed full-time   \n",
       "2               6  Employed full-time   \n",
       "3               9  Employed full-time   \n",
       "4              10  Employed full-time   \n",
       "...           ...                 ...   \n",
       "55818       88878  Employed full-time   \n",
       "55819       88879  Employed full-time   \n",
       "55820       88881  Employed full-time   \n",
       "55821       88882  Employed full-time   \n",
       "55822       88883  Employed full-time   \n",
       "\n",
       "                                                 EdLevel  \\\n",
       "0               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "1               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "2               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "3      Some college/university study without earning ...   \n",
       "4            Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "...                                                  ...   \n",
       "55818           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "55819        Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "55820        Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "55821        Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "55822           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "\n",
       "                                          UndergradMajor  \\\n",
       "0                          Web development or web design   \n",
       "1      Computer science, computer engineering, or sof...   \n",
       "2                              Mathematics or statistics   \n",
       "3      Computer science, computer engineering, or sof...   \n",
       "4                                                    NaN   \n",
       "...                                                  ...   \n",
       "55818  Computer science, computer engineering, or sof...   \n",
       "55819  Computer science, computer engineering, or sof...   \n",
       "55820  Computer science, computer engineering, or sof...   \n",
       "55821  Computer science, computer engineering, or sof...   \n",
       "55822  Computer science, computer engineering, or sof...   \n",
       "\n",
       "                        OrgSize YearsCode  ConvertedComp   Age         Gender  \\\n",
       "0          100 to 499 employees         3         8820.0  28.0            Man   \n",
       "1          100 to 499 employees         3        61000.0  22.0            Man   \n",
       "2                           NaN        13       366420.0  28.0            Man   \n",
       "3            10 to 19 employees        12        95179.0  23.0            Man   \n",
       "4      10,000 or more employees        12        13293.0   NaN  Not Specified   \n",
       "...                         ...       ...            ...   ...            ...   \n",
       "55818        20 to 99 employees        12       130000.0  26.0            Man   \n",
       "55819        20 to 99 employees        17        82488.0  34.0            Man   \n",
       "55820      100 to 499 employees        18        68745.0  37.0            Man   \n",
       "55821      100 to 499 employees        10       588012.0   NaN            Man   \n",
       "55822        20 to 99 employees         9        22915.0  33.0            Man   \n",
       "\n",
       "             Country  ...  Elasticsearch  Firebase  MariaDB  \\\n",
       "0           Thailand  ...              0         0        0   \n",
       "1      United States  ...              0         0        0   \n",
       "2             Canada  ...              0         0        0   \n",
       "3        New Zealand  ...              0         0        0   \n",
       "4              India  ...              1         0        0   \n",
       "...              ...  ...            ...       ...      ...   \n",
       "55818  United States  ...              0         0        0   \n",
       "55819        Finland  ...              0         0        0   \n",
       "55820        Austria  ...              0         0        0   \n",
       "55821    Netherlands  ...              0         0        1   \n",
       "55822         Greece  ...              0         0        1   \n",
       "\n",
       "       Microsoft SQL Server  MongoDB  MySQL  Oracle  PostgreSQL  Redis  SQLite  \n",
       "0                         0        0      0       0           1      0       0  \n",
       "1                         0        0      1       0           0      0       1  \n",
       "2                         0        1      0       0           1      0       0  \n",
       "3                         0        0      0       0           1      0       1  \n",
       "4                         1        1      1       0           0      0       1  \n",
       "...                     ...      ...    ...     ...         ...    ...     ...  \n",
       "55818                     0        0      0       0           1      0       0  \n",
       "55819                     0        0      0       0           0      0       0  \n",
       "55820                     0        0      0       0           1      1       0  \n",
       "55821                     0        0      0       0           1      0       0  \n",
       "55822                     0        0      0       0           1      0       1  \n",
       "\n",
       "[55823 rows x 84 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:5: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \"\"\"\n"
     ]
    }
   ],
   "source": [
    "temp4 = df_2019['PlatformWorkedWith'].str.split(';', expand=True)\n",
    "\n",
    "all_plats = []\n",
    "for row in range(temp4.shape[0]):\n",
    "    j = temp4.iloc[row].as_matrix()\n",
    "    for plat in j:\n",
    "        if plat not in all_plats:\n",
    "            all_plats.append(plat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n",
      "True\n",
      "True\n",
      "False\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "for i in all_plats:\n",
    "    print(type(i)==type('str'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_plats.remove(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_plats.pop(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Linux',\n",
       " 'Windows',\n",
       " 'Android',\n",
       " 'Google Cloud Platform',\n",
       " 'AWS',\n",
       " 'Docker',\n",
       " 'Heroku',\n",
       " 'MacOS',\n",
       " 'Slack',\n",
       " 'IBM Cloud or Watson',\n",
       " 'iOS',\n",
       " 'Microsoft Azure',\n",
       " 'WordPress',\n",
       " 'Arduino',\n",
       " 'Raspberry Pi',\n",
       " 'Kubernetes',\n",
       " 'Other(s):']"
      ]
     },
     "execution_count": 307,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_plats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in all_plats:\n",
    "    df_2019[i] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "for i in range(temp4.shape[0]):\n",
    "    j = list(temp4.iloc[i].as_matrix())\n",
    "    for item in j:\n",
    "        if type(item)==type('str'):\n",
    "            df_2019.at[i, item] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:5: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \"\"\"\n"
     ]
    }
   ],
   "source": [
    "temp5 = df_2019['WebFrameWorkedWith'].str.split(';', expand=True)\n",
    "\n",
    "all_frames = []\n",
    "for row in range(temp5.shape[0]):\n",
    "    j = temp5.iloc[row].as_matrix()\n",
    "    for frame in j:\n",
    "        if frame not in all_frames:\n",
    "            all_frames.append(frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n",
      "True\n",
      "True\n",
      "True\n",
      "False\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "for i in all_frames:\n",
    "    print(type(i)==type('str'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_frames.remove(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_frames.pop(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Express',\n",
       " 'Ruby on Rails',\n",
       " 'Other(s):',\n",
       " 'Angular/Angular.js',\n",
       " 'ASP.NET',\n",
       " 'Django',\n",
       " 'Flask',\n",
       " 'jQuery',\n",
       " 'Vue.js',\n",
       " 'Spring',\n",
       " 'React.js',\n",
       " 'Laravel',\n",
       " 'Drupal']"
      ]
     },
     "execution_count": 308,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_frames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in all_frames:\n",
    "    df_2019[i] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/owenbchiu/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "for i in range(temp5.shape[0]):\n",
    "    j = list(temp5.iloc[i].as_matrix())\n",
    "    for item in j:\n",
    "        if type(item)==type('str'):\n",
    "            df_2019.at[i, item] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "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>Employment</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>...</th>\n",
       "      <th>Angular/Angular.js</th>\n",
       "      <th>ASP.NET</th>\n",
       "      <th>Django</th>\n",
       "      <th>Flask</th>\n",
       "      <th>jQuery</th>\n",
       "      <th>Vue.js</th>\n",
       "      <th>Spring</th>\n",
       "      <th>React.js</th>\n",
       "      <th>Laravel</th>\n",
       "      <th>Drupal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Some college/university study without earning ...</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>14</td>\n",
       "      <td>31140.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>23</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Information systems, information technology, o...</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>3</td>\n",
       "      <td>69000.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>24</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Primary/elementary school</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10 to 19 employees</td>\n",
       "      <td>2</td>\n",
       "      <td>26388.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Israel</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>29</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>4</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>54</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>20</td>\n",
       "      <td>68268.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 112 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Respondent          Employment  \\\n",
       "10          19  Employed full-time   \n",
       "13          23  Employed full-time   \n",
       "14          24  Employed full-time   \n",
       "17          29  Employed full-time   \n",
       "33          54  Employed full-time   \n",
       "\n",
       "                                              EdLevel  \\\n",
       "10  Some college/university study without earning ...   \n",
       "13           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "14                          Primary/elementary school   \n",
       "17           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "33                                                NaN   \n",
       "\n",
       "                                       UndergradMajor  \\\n",
       "10  Computer science, computer engineering, or sof...   \n",
       "13  Information systems, information technology, o...   \n",
       "14                                                NaN   \n",
       "17                                                NaN   \n",
       "33  Computer science, computer engineering, or sof...   \n",
       "\n",
       "                     OrgSize YearsCode  ConvertedComp   Age Gender  \\\n",
       "10      100 to 499 employees        14        31140.0  31.0    Man   \n",
       "13  10,000 or more employees         3        69000.0  22.0    Man   \n",
       "14        10 to 19 employees         2        26388.0  23.0    Man   \n",
       "17  10,000 or more employees         4       100000.0  32.0    Man   \n",
       "33        20 to 99 employees        20        68268.0  37.0    Man   \n",
       "\n",
       "          Country  ...  Angular/Angular.js  ASP.NET  Django  Flask  jQuery  \\\n",
       "10         Brazil  ...                   1        1       0      0       1   \n",
       "13  United States  ...                   0        0       0      0       0   \n",
       "14         Israel  ...                   0        0       0      0       1   \n",
       "17  United States  ...                   0        0       0      0       1   \n",
       "33         Sweden  ...                   0        0       1      0       0   \n",
       "\n",
       "    Vue.js  Spring  React.js  Laravel  Drupal  \n",
       "10       0       0         1        0       0  \n",
       "13       0       0         1        0       0  \n",
       "14       0       0         1        0       0  \n",
       "17       0       0         1        0       0  \n",
       "33       0       0         1        0       0  \n",
       "\n",
       "[5 rows x 112 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019[df_2019['React.js']==1].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Respondent\n",
      "Employment\n",
      "EdLevel\n",
      "UndergradMajor\n",
      "OrgSize\n",
      "YearsCode\n",
      "ConvertedComp\n",
      "Age\n",
      "Gender\n",
      "Country\n",
      "CountryAvgComp\n",
      "EducationAvgComp\n",
      "MajorAvgComp\n",
      "GenderCode\n",
      "NewOrgSize\n",
      "Academic researcher\n",
      "Data or business analyst\n",
      "Data scientist or machine learning specialist\n",
      "Database administrator\n",
      "Designer\n",
      "DevOps specialist\n",
      "Developer, QA or test\n",
      "Developer, back-end\n",
      "Developer, desktop or enterprise applications\n",
      "Developer, embedded applications or devices\n",
      "Developer, front-end\n",
      "Developer, full-stack\n",
      "Developer, game or graphics\n",
      "Developer, mobile\n",
      "Educator\n",
      "Engineer, data\n",
      "Engineer, site reliability\n",
      "Engineering manager\n",
      "Marketing or sales professional\n",
      "Product manager\n",
      "Scientist\n",
      "Senior executive/VP\n",
      "Student\n",
      "System administrator\n",
      "LanguageWorkedWith\n",
      "DatabaseWorkedWith\n",
      "PlatformWorkedWith\n",
      "WebFrameWorkedWith\n",
      "Assembly\n",
      "Bash/Shell/PowerShell\n",
      "C\n",
      "C#\n",
      "C++\n",
      "Clojure\n",
      "Dart\n",
      "Elixir\n",
      "Erlang\n",
      "F#\n",
      "Go\n",
      "HTML/CSS\n",
      "Java\n",
      "JavaScript\n",
      "Kotlin\n",
      "Objective-C\n",
      "Other(s):\n",
      "PHP\n",
      "Python\n",
      "R\n",
      "Ruby\n",
      "Rust\n",
      "SQL\n",
      "Scala\n",
      "Swift\n",
      "TypeScript\n",
      "VBA\n",
      "WebAssembly\n",
      "Cassandra\n",
      "Couchbase\n",
      "DynamoDB\n",
      "Elasticsearch\n",
      "Firebase\n",
      "MariaDB\n",
      "Microsoft SQL Server\n",
      "MongoDB\n",
      "MySQL\n",
      "Oracle\n",
      "PostgreSQL\n",
      "Redis\n",
      "SQLite\n",
      "Linux\n",
      "Windows\n",
      "Android\n",
      "Google Cloud Platform\n",
      "AWS\n",
      "Docker\n",
      "Heroku\n",
      "MacOS\n",
      "Slack\n",
      "IBM Cloud or Watson\n",
      "iOS\n",
      "Microsoft Azure\n",
      "WordPress\n",
      "Arduino\n",
      "Raspberry Pi\n",
      "Kubernetes\n",
      "Express\n",
      "Ruby on Rails\n",
      "Angular/Angular.js\n",
      "ASP.NET\n",
      "Django\n",
      "Flask\n",
      "jQuery\n",
      "Vue.js\n",
      "Spring\n",
      "React.js\n",
      "Laravel\n",
      "Drupal\n"
     ]
    }
   ],
   "source": [
    "for i in df_2019.columns:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019.loc[df_2019['YearsCode']==np.nan, 'YearsCode'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019['YearsCode'] = df_2019['YearsCode'].fillna(value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['3', '13', '12', '17', '10', '5', '14', '8', '35', '2', '4', '6',\n",
       "       '30', '9', '26', '40', '15', '7', '20', '28', '25', '1', '22',\n",
       "       '16', '11', '33', '50', '18', '34', '19', '24', '23', '42', '27',\n",
       "       '21', '36', 'Less than 1 year', '32', '39', '38', 0, '31', '29',\n",
       "       '37', '41', '44', '48', '45', '43', '47', '46', '49',\n",
       "       'More than 50 years'], dtype=object)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019['YearsCode'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019.loc[df_2019['YearsCode']=='Less than 1 year', 'YearsCode'] = 0\n",
    "df_2019.loc[df_2019['YearsCode']=='More than 50 years', 'YearsCode'] = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019['YearsCode'] = df_2019['YearsCode'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019.loc[df_2019['Age']==np.nan, 'Age'] = 0\n",
    "df_2019['Age'] = df_2019['Age'].fillna(value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019['Age'] = df_2019['Age'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31.42608338160821"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019[df_2019['Age']!=0]['Age'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019.loc[df_2019['Age']==0, 'Age'] = 31"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019[df_2019['ConvertedComp']<1000000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2018 = pd.read_csv('2018_formatted_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df_2019[df_2019['Country']!='']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df_2019.drop(['Respondent', 'Employment', 'EdLevel', 'UndergradMajor', 'OrgSize', 'Gender', 'Country', 'ConvertedComp', 'LanguageWorkedWith', 'DatabaseWorkedWith', 'PlatformWorkedWith', 'WebFrameWorkedWith'], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = X.drop(['Age', 'NewOrgSize','GenderCode', 'MajorAvgComp','Marketing or sales professional', 'Drupal', 'IBM Cloud or Watson', 'WebAssembly', 'Couchbase', 'F#', 'Erlang', 'Elixir', 'Dart', 'Clojure'], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = pd.concat([X, df_2018[X.columns]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = pd.concat([df_2019['ConvertedComp'], df_2018['ConvertedComp']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {},
   "outputs": [],
   "source": [
    "lm = linear_model.LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = lm.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = lm.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = abs(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {},
   "outputs": [],
   "source": [
    "MAE = metrics.mean_absolute_error(y_test, y_pred)\n",
    "MSE = metrics.mean_squared_error(y_test, y_pred)\n",
    "R2 = metrics.r2_score(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Abs Error: 119590.11219623643\n",
      "Mean Squared Error: 72707776706.6328\n",
      "R2: 0.1002219359074934\n"
     ]
    }
   ],
   "source": [
    "#Baseline - All Features, no Hyperparameters\n",
    "print(\"Mean Abs Error:\", MAE)\n",
    "print(\"Mean Squared Error:\", MSE)\n",
    "print(\"R2:\", R2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Abs Error: 45773.713510622954\n",
      "Mean Squared Error: 11340788906.778673\n",
      "R2: 0.12592263345589205\n"
     ]
    }
   ],
   "source": [
    "print(\"Mean Abs Error:\", MAE)\n",
    "print(\"Mean Squared Error:\", MSE)\n",
    "print(\"R2:\", R2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "113505.41763002942"
      ]
     },
     "execution_count": 285,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "math.sqrt(MSE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = pd.concat([y_test.reset_index()['ConvertedComp'], pd.Series(y_pred)], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = results.rename(columns={'ConvertedComp': 'Actual', 0:'Predicted'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [],
   "source": [
    "results['Diff'] = abs(results['Actual']-results['Predicted'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = results.sort_values(by=['Predicted'], ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "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>Actual</th>\n",
       "      <th>Predicted</th>\n",
       "      <th>Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>5717</td>\n",
       "      <td>260000.0</td>\n",
       "      <td>230707.118083</td>\n",
       "      <td>29292.881917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11046</td>\n",
       "      <td>275000.0</td>\n",
       "      <td>228345.162907</td>\n",
       "      <td>46654.837093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>907</td>\n",
       "      <td>212500.0</td>\n",
       "      <td>223282.184551</td>\n",
       "      <td>10782.184551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10004</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>222938.490722</td>\n",
       "      <td>22938.490722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16136</td>\n",
       "      <td>225000.0</td>\n",
       "      <td>222565.262269</td>\n",
       "      <td>2434.737731</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Actual      Predicted          Diff\n",
       "5717   260000.0  230707.118083  29292.881917\n",
       "11046  275000.0  228345.162907  46654.837093\n",
       "907    212500.0  223282.184551  10782.184551\n",
       "10004  200000.0  222938.490722  22938.490722\n",
       "16136  225000.0  222565.262269   2434.737731"
      ]
     },
     "execution_count": 296,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([14331.87438231])"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test4 = {\n",
    "  \"YearsCode\": 10,\n",
    "  \"CountryAvgComp\": 28057.664916,\n",
    "  \"EducationAvgComp\": 134966.131508,\n",
    "  \"Academic researcher\": 1,\n",
    "  \"Data or business analyst\": 1,\n",
    "  \"Data scientist or machine learning specialist\": 0,\n",
    "  \"Database administrator\": 0,\n",
    "  \"Designer\": 1,\n",
    "  \"DevOps specialist\": 1,\n",
    "  \"Developer, QA or test\": 1,\n",
    "  \"Developer, back-end\": 1,\n",
    "  \"Developer, desktop or enterprise applications\": 0,\n",
    "  \"Developer, embedded applications or devices\": 1,\n",
    "  \"Developer, front-end\": 0,\n",
    "  \"Developer, full-stack\": 1,\n",
    "  \"Developer, game or graphics\": 0,\n",
    "  \"Developer, mobile\": 0,\n",
    "  \"Educator\": 0,\n",
    "  \"Engineer, data\": 0,\n",
    "  \"Engineer, site reliability\": 0,\n",
    "  \"Engineering manager\": 0,\n",
    "  \"Product manager\": 0,\n",
    "  \"Scientist\": 0,\n",
    "  \"Senior executive/VP\": 0,\n",
    "  \"Student\": 0,\n",
    "  \"System administrator\": 0,\n",
    "  \"Assembly\": 1,\n",
    "  \"Bash/Shell/PowerShell\": 0,\n",
    "  \"C\": 1,\n",
    "  \"C#\": 0,\n",
    "  \"C++\": 1,\n",
    "  \"Go\": 1,\n",
    "  \"HTML/CSS\": 0,\n",
    "  \"Java\": 0,\n",
    "  \"JavaScript\": 1,\n",
    "  \"Kotlin\": 0,\n",
    "  \"Objective-C\": 0,\n",
    "  \"Other(s):\": 0,\n",
    "  \"PHP\": 1,\n",
    "  \"Python\": 1,\n",
    "  \"R\": 1,\n",
    "  \"Ruby\": 0,\n",
    "  \"Rust\": 0,\n",
    "  \"SQL\": 0,\n",
    "  \"Scala\": 0,\n",
    "  \"Swift\": 1,\n",
    "  \"TypeScript\": 1,\n",
    "  \"VBA\": 0,\n",
    "  \"Cassandra\": 0,\n",
    "  \"DynamoDB\": 0,\n",
    "  \"Elasticsearch\": 0,\n",
    "  \"Firebase\": 1,\n",
    "  \"MariaDB\": 1,\n",
    "  \"Microsoft SQL Server\": 0,\n",
    "  \"MongoDB\": 1,\n",
    "  \"MySQL\": 1,\n",
    "  \"Oracle\": 1,\n",
    "  \"PostgreSQL\": 0,\n",
    "  \"Redis\": 0,\n",
    "  \"SQLite\": 0,\n",
    "  \"Linux\": 1,\n",
    "  \"Windows\": 1,\n",
    "  \"Android\": 1,\n",
    "  \"Google Cloud Platform\": 0,\n",
    "  \"AWS\": 0,\n",
    "  \"Docker\": 0,\n",
    "  \"Heroku\": 0,\n",
    "  \"MacOS\": 0,\n",
    "  \"Slack\": 0,\n",
    "  \"iOS\": 0,\n",
    "  \"Microsoft Azure\": 0,\n",
    "  \"WordPress\": 0,\n",
    "  \"Arduino\": 1,\n",
    "  \"Raspberry Pi\": 1,\n",
    "  \"Kubernetes\": 0,\n",
    "  \"Express\": 0,\n",
    "  \"Ruby on Rails\": 0,\n",
    "  \"Angular/Angular.js\": 0,\n",
    "  \"ASP.NET\": 0,\n",
    "  \"Django\": 0,\n",
    "  \"Flask\": 1,\n",
    "  \"jQuery\": 1,\n",
    "  \"Vue.js\": 1,\n",
    "  \"Spring\": 1,\n",
    "  \"React.js\": 1,\n",
    "  \"Laravel\": 0\n",
    "}\n",
    "test4_df = pd.DataFrame(test4, index=[0])\n",
    "\n",
    "lm.predict(test4_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['YearsCode', 'CountryAvgComp', 'EducationAvgComp',\n",
       "       'Academic researcher', 'Data or business analyst',\n",
       "       'Data scientist or machine learning specialist',\n",
       "       'Database administrator', 'Designer', 'DevOps specialist',\n",
       "       'Developer, QA or test', 'Developer, back-end',\n",
       "       'Developer, desktop or enterprise applications',\n",
       "       'Developer, embedded applications or devices', 'Developer, front-end',\n",
       "       'Developer, full-stack', 'Developer, game or graphics',\n",
       "       'Developer, mobile', 'Educator', 'Engineer, data',\n",
       "       'Engineer, site reliability', 'Engineering manager', 'Product manager',\n",
       "       'Scientist', 'Senior executive/VP', 'Student', 'System administrator',\n",
       "       'Assembly', 'Bash/Shell/PowerShell', 'C', 'C#', 'C++', 'Go', 'HTML/CSS',\n",
       "       'Java', 'JavaScript', 'Kotlin', 'Objective-C', 'Other(s):', 'PHP',\n",
       "       'Python', 'R', 'Ruby', 'Rust', 'SQL', 'Scala', 'Swift', 'TypeScript',\n",
       "       'VBA', 'Cassandra', 'DynamoDB', 'Elasticsearch', 'Firebase', 'MariaDB',\n",
       "       'Microsoft SQL Server', 'MongoDB', 'MySQL', 'Oracle', 'PostgreSQL',\n",
       "       'Redis', 'SQLite', 'Linux', 'Windows', 'Android',\n",
       "       'Google Cloud Platform', 'AWS', 'Docker', 'Heroku', 'MacOS', 'Slack',\n",
       "       'iOS', 'Microsoft Azure', 'WordPress', 'Arduino', 'Raspberry Pi',\n",
       "       'Kubernetes', 'Express', 'Ruby on Rails', 'Angular/Angular.js',\n",
       "       'ASP.NET', 'Django', 'Flask', 'jQuery', 'Vue.js', 'Spring', 'React.js',\n",
       "       'Laravel'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 299,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "test2 = {'YearsCode':20, 'Age':40, 'CountryAvgComp':134018.564909, 'EducationAvgComp':154087.31363636,\n",
    "       'MajorAvgComp':180557.20155902, 'GenderCode':0, 'NewOrgSize':10000, 'Academic researcher':1,\n",
    "       'Data or business analyst':1,\n",
    "       'Data scientist or machine learning specialist':1,\n",
    "       'Database administrator':1, 'Designer':1, 'DevOps specialist':1,\n",
    "       'Developer, QA or test':1, 'Developer, back-end':1,\n",
    "       'Developer, desktop or enterprise applications':1,\n",
    "       'Developer, embedded applications or devices':1, 'Developer, front-end':1,\n",
    "       'Developer, full-stack':1, 'Developer, game or graphics':1,\n",
    "       'Developer, mobile':1, 'Educator':1, 'Engineer, data':1,\n",
    "       'Engineer, site reliability':1, 'Engineering manager':1,\n",
    "       'Marketing or sales professional':1, 'Product manager':1, 'Scientist':1,\n",
    "       'Senior executive/VP':1, 'Student':1, 'System administrator':1, 'Assembly':1,\n",
    "       'Bash/Shell/PowerShell':1, 'C':1, 'C#':1, 'C++':1, 'Clojure':1, 'Dart':1, 'Elixir':1,\n",
    "       'Erlang':1, 'F#':1, 'Go':1, 'HTML/CSS':1, 'Java':1, 'JavaScript':1, 'Kotlin':1,\n",
    "       'Objective-C':1, 'Other(s):':1, 'PHP':1, 'Python':1, 'R':1, 'Ruby':1, 'Rust':1, 'SQL':1,\n",
    "       'Scala':1, 'Swift':1, 'TypeScript':1, 'VBA':1, 'WebAssembly':1, 'Cassandra':1,\n",
    "       'Couchbase':1, 'DynamoDB':1, 'Elasticsearch':1, 'Firebase':1, 'MariaDB':1,\n",
    "       'Microsoft SQL Server':1, 'MongoDB':1, 'MySQL':1, 'Oracle':1, 'PostgreSQL':1,\n",
    "       'Redis':1, 'SQLite':1, 'Linux':1, 'Windows':1, 'Android':1,\n",
    "       'Google Cloud Platform':1, 'AWS':1, 'Docker':1, 'Heroku':1, 'MacOS':1, 'Slack':1,\n",
    "       'IBM Cloud or Watson':1, 'iOS':1, 'Microsoft Azure':1, 'WordPress':1, 'Arduino':1,\n",
    "       'Raspberry Pi':1, 'Kubernetes':1, 'Express':1, 'Ruby on Rails':1,\n",
    "       'Angular/Angular.js':1, 'ASP.NET':1, 'Django':1, 'Flask':1, 'jQuery':1, 'Vue.js':1,\n",
    "       'Spring':1, 'React.js':1, 'Laravel':1, 'Drupal':1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "test3 = pd.DataFrame(test2, index=[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([390970.83524984])"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lm.predict(test3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4        28057.664916\n",
       "30       28057.664916\n",
       "44       28057.664916\n",
       "50       28057.664916\n",
       "53       28057.664916\n",
       "             ...     \n",
       "55713    28057.664916\n",
       "55727    28057.664916\n",
       "55753    28057.664916\n",
       "55774    28057.664916\n",
       "55781    28057.664916\n",
       "Name: CountryAvgComp, Length: 3992, dtype: float64"
      ]
     },
     "execution_count": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019[df_2019['Country']=='India']['CountryAvgComp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_series = pd.Series(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        109000.0\n",
       "1         41688.0\n",
       "2         77400.0\n",
       "3         59652.0\n",
       "4         62000.0\n",
       "           ...   \n",
       "18417     54996.0\n",
       "18418    130847.0\n",
       "18419     24576.0\n",
       "18420    103117.0\n",
       "18421     54956.0\n",
       "Name: ConvertedComp, Length: 18422, dtype: float64"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.reset_index()['ConvertedComp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "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>Actual</th>\n",
       "      <th>Predicted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>109000.0</td>\n",
       "      <td>282996.099051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>41688.0</td>\n",
       "      <td>66016.540709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>77400.0</td>\n",
       "      <td>238533.021570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>59652.0</td>\n",
       "      <td>83078.629025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>62000.0</td>\n",
       "      <td>225278.611587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>10608.0</td>\n",
       "      <td>41212.641112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>6876.0</td>\n",
       "      <td>-2817.714491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>91593.0</td>\n",
       "      <td>179932.179814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>4272.0</td>\n",
       "      <td>-5842.383589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>17200.0</td>\n",
       "      <td>47935.324338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>17256.0</td>\n",
       "      <td>-5033.337664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>182000.0</td>\n",
       "      <td>226216.109916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>293879.080490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>19248.0</td>\n",
       "      <td>31535.017412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>12500.0</td>\n",
       "      <td>248408.296594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>143219.0</td>\n",
       "      <td>175864.054592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>230829.452790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>135198.0</td>\n",
       "      <td>150983.317759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>107000.0</td>\n",
       "      <td>190821.664864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>38383.0</td>\n",
       "      <td>72822.338998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>29789.0</td>\n",
       "      <td>34787.410344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>60256.0</td>\n",
       "      <td>127264.283372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>88000.0</td>\n",
       "      <td>277321.975349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>25680.0</td>\n",
       "      <td>58209.515207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>95000.0</td>\n",
       "      <td>244867.490569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>4198.0</td>\n",
       "      <td>-24688.200092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>46752.0</td>\n",
       "      <td>22122.096904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>1464.0</td>\n",
       "      <td>1923.260086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>86000.0</td>\n",
       "      <td>281411.955475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>52000.0</td>\n",
       "      <td>206857.559836</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Actual      Predicted\n",
       "0    109000.0  282996.099051\n",
       "1     41688.0   66016.540709\n",
       "2     77400.0  238533.021570\n",
       "3     59652.0   83078.629025\n",
       "4     62000.0  225278.611587\n",
       "5     10608.0   41212.641112\n",
       "6      6876.0   -2817.714491\n",
       "7     91593.0  179932.179814\n",
       "8      4272.0   -5842.383589\n",
       "9     17200.0   47935.324338\n",
       "10    17256.0   -5033.337664\n",
       "11   182000.0  226216.109916\n",
       "12  2000000.0  293879.080490\n",
       "13    19248.0   31535.017412\n",
       "14    12500.0  248408.296594\n",
       "15   143219.0  175864.054592\n",
       "16   140000.0  230829.452790\n",
       "17   135198.0  150983.317759\n",
       "18   107000.0  190821.664864\n",
       "19    38383.0   72822.338998\n",
       "20    29789.0   34787.410344\n",
       "21    60256.0  127264.283372\n",
       "22    88000.0  277321.975349\n",
       "23    25680.0   58209.515207\n",
       "24    95000.0  244867.490569\n",
       "25     4198.0  -24688.200092\n",
       "26    46752.0   22122.096904\n",
       "27     1464.0    1923.260086\n",
       "28    86000.0  281411.955475\n",
       "29    52000.0  206857.559836"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['YearsCode', 'Age', 'CountryAvgComp', 'EducationAvgComp',\n",
       "       'MajorAvgComp', 'GenderCode', 'NewOrgSize', 'Academic researcher',\n",
       "       'Data or business analyst',\n",
       "       'Data scientist or machine learning specialist',\n",
       "       'Database administrator', 'Designer', 'DevOps specialist',\n",
       "       'Developer, QA or test', 'Developer, back-end',\n",
       "       'Developer, desktop or enterprise applications',\n",
       "       'Developer, embedded applications or devices', 'Developer, front-end',\n",
       "       'Developer, full-stack', 'Developer, game or graphics',\n",
       "       'Developer, mobile', 'Educator', 'Engineer, data',\n",
       "       'Engineer, site reliability', 'Engineering manager',\n",
       "       'Marketing or sales professional', 'Product manager', 'Scientist',\n",
       "       'Senior executive/VP', 'Student', 'System administrator', 'Assembly',\n",
       "       'Bash/Shell/PowerShell', 'C', 'C#', 'C++', 'Clojure', 'Dart', 'Elixir',\n",
       "       'Erlang', 'F#', 'Go', 'HTML/CSS', 'Java', 'JavaScript', 'Kotlin',\n",
       "       'Objective-C', 'Other(s):', 'PHP', 'Python', 'R', 'Ruby', 'Rust', 'SQL',\n",
       "       'Scala', 'Swift', 'TypeScript', 'VBA', 'WebAssembly', 'Cassandra',\n",
       "       'Couchbase', 'DynamoDB', 'Elasticsearch', 'Firebase', 'MariaDB',\n",
       "       'Microsoft SQL Server', 'MongoDB', 'MySQL', 'Oracle', 'PostgreSQL',\n",
       "       'Redis', 'SQLite', 'Linux', 'Windows', 'Android',\n",
       "       'Google Cloud Platform', 'AWS', 'Docker', 'Heroku', 'MacOS', 'Slack',\n",
       "       'IBM Cloud or Watson', 'iOS', 'Microsoft Azure', 'WordPress', 'Arduino',\n",
       "       'Raspberry Pi', 'Kubernetes', 'Express', 'Ruby on Rails',\n",
       "       'Angular/Angular.js', 'ASP.NET', 'Django', 'Flask', 'jQuery', 'Vue.js',\n",
       "       'Spring', 'React.js', 'Laravel', 'Drupal'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = df_2019[['YearsCode', 'Age', 'CountryAvgComp', 'EducationAvgComp',\n",
    "       'MajorAvgComp', 'GenderCode', 'NewOrgSize', 'ConvertedComp']].corr()\n",
    "ax = sns.heatmap(\n",
    "    corr, \n",
    "    vmin=-1, vmax=1, center=0,\n",
    "    cmap=sns.diverging_palette(20, 220, n=200),\n",
    "    square=True\n",
    ")\n",
    "ax.set_xticklabels(\n",
    "    ax.get_xticklabels(),\n",
    "    rotation=45,\n",
    "    horizontalalignment='right'\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [],
   "source": [
    "totals = df_2019[['Academic researcher',\n",
    "       'Data or business analyst',\n",
    "       'Data scientist or machine learning specialist',\n",
    "       'Database administrator', 'Designer', 'DevOps specialist',\n",
    "       'Developer, QA or test', 'Developer, back-end',\n",
    "       'Developer, desktop or enterprise applications',\n",
    "       'Developer, embedded applications or devices', 'Developer, front-end',\n",
    "       'Developer, full-stack', 'Developer, game or graphics',\n",
    "       'Developer, mobile', 'Educator', 'Engineer, data',\n",
    "       'Engineer, site reliability', 'Engineering manager',\n",
    "       'Marketing or sales professional', 'Product manager', 'Scientist',\n",
    "       'Senior executive/VP', 'Student', 'System administrator', 'Assembly',\n",
    "       'Bash/Shell/PowerShell', 'C', 'C#', 'C++', 'Clojure', 'Dart', 'Elixir',\n",
    "       'Erlang', 'F#', 'Go', 'HTML/CSS', 'Java', 'JavaScript', 'Kotlin',\n",
    "       'Objective-C', 'Other(s):', 'PHP', 'Python', 'R', 'Ruby', 'Rust', 'SQL',\n",
    "       'Scala', 'Swift', 'TypeScript', 'VBA', 'WebAssembly', 'Cassandra',\n",
    "       'Couchbase', 'DynamoDB', 'Elasticsearch', 'Firebase', 'MariaDB',\n",
    "       'Microsoft SQL Server', 'MongoDB', 'MySQL', 'Oracle', 'PostgreSQL',\n",
    "       'Redis', 'SQLite', 'Linux', 'Windows', 'Android',\n",
    "       'Google Cloud Platform', 'AWS', 'Docker', 'Heroku', 'MacOS', 'Slack',\n",
    "       'IBM Cloud or Watson', 'iOS', 'Microsoft Azure', 'WordPress', 'Arduino',\n",
    "       'Raspberry Pi', 'Kubernetes', 'Express', 'Ruby on Rails',\n",
    "       'Angular/Angular.js', 'ASP.NET', 'Django', 'Flask', 'jQuery', 'Vue.js',\n",
    "       'Spring', 'React.js', 'Laravel', 'Drupal']].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Senior executive/VP       1318\n",
       "Student                   3848\n",
       "System administrator      5957\n",
       "Assembly                  2428\n",
       "Bash/Shell/PowerShell    21832\n",
       "C                         8851\n",
       "C#                       18062\n",
       "C++                      10688\n",
       "Clojure                    863\n",
       "Dart                       979\n",
       "Elixir                     898\n",
       "Erlang                     515\n",
       "F#                         648\n",
       "Go                        5079\n",
       "HTML/CSS                 35134\n",
       "Java                     21154\n",
       "JavaScript               39029\n",
       "Kotlin                    3689\n",
       "Objective-C               2838\n",
       "Other(s):                 3764\n",
       "dtype: int64"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "totals[21:41]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "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>Employment</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>CountryAvgComp</th>\n",
       "      <th>...</th>\n",
       "      <th>Angular/Angular.js</th>\n",
       "      <th>ASP.NET</th>\n",
       "      <th>Django</th>\n",
       "      <th>Flask</th>\n",
       "      <th>jQuery</th>\n",
       "      <th>Vue.js</th>\n",
       "      <th>Spring</th>\n",
       "      <th>React.js</th>\n",
       "      <th>Laravel</th>\n",
       "      <th>Drupal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>A business discipline (ex. accounting, finance, marketing)</td>\n",
       "      <td>1154</td>\n",
       "      <td>1151</td>\n",
       "      <td>1143</td>\n",
       "      <td>1142</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>...</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "      <td>1154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>A health science (ex. nursing, pharmacy, radiology)</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>150</td>\n",
       "      <td>152</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>...</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>A humanities discipline (ex. literature, history, philosophy)</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1130</td>\n",
       "      <td>1117</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>...</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "      <td>1138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>A natural science (ex. biology, chemistry, physics)</td>\n",
       "      <td>2303</td>\n",
       "      <td>2299</td>\n",
       "      <td>2279</td>\n",
       "      <td>2260</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>...</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "      <td>2303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>A social science (ex. anthropology, psychology, political science)</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>955</td>\n",
       "      <td>949</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>...</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "      <td>962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Another engineering discipline (ex. civil, electrical, mechanical)</td>\n",
       "      <td>4204</td>\n",
       "      <td>4188</td>\n",
       "      <td>4181</td>\n",
       "      <td>4141</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>...</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "      <td>4204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Computer science, computer engineering, or software engineering</td>\n",
       "      <td>32356</td>\n",
       "      <td>32284</td>\n",
       "      <td>31937</td>\n",
       "      <td>31792</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>...</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "      <td>32356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Fine arts or performing arts (ex. graphic design, music, studio art)</td>\n",
       "      <td>898</td>\n",
       "      <td>896</td>\n",
       "      <td>882</td>\n",
       "      <td>878</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>...</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "      <td>898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>I never declared a major</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>528</td>\n",
       "      <td>563</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>...</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "      <td>575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Information systems, information technology, or system administration</td>\n",
       "      <td>3460</td>\n",
       "      <td>3447</td>\n",
       "      <td>3392</td>\n",
       "      <td>3387</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>...</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "      <td>3460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Mathematics or statistics</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2012</td>\n",
       "      <td>1989</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>...</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Web development or web design</td>\n",
       "      <td>2030</td>\n",
       "      <td>2022</td>\n",
       "      <td>1930</td>\n",
       "      <td>1992</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>...</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "      <td>2030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 111 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Respondent  Employment  \\\n",
       "UndergradMajor                                                               \n",
       "A business discipline (ex. accounting, finance,...        1154        1151   \n",
       "A health science (ex. nursing, pharmacy, radiol...         154         154   \n",
       "A humanities discipline (ex. literature, histor...        1138        1138   \n",
       "A natural science (ex. biology, chemistry, phys...        2303        2299   \n",
       "A social science (ex. anthropology, psychology,...         962         962   \n",
       "Another engineering discipline (ex. civil, elec...        4204        4188   \n",
       "Computer science, computer engineering, or soft...       32356       32284   \n",
       "Fine arts or performing arts (ex. graphic desig...         898         896   \n",
       "I never declared a major                                   575         575   \n",
       "Information systems, information technology, or...        3460        3447   \n",
       "Mathematics or statistics                                 2030        2030   \n",
       "Web development or web design                             2030        2022   \n",
       "\n",
       "                                                    EdLevel  OrgSize  \\\n",
       "UndergradMajor                                                         \n",
       "A business discipline (ex. accounting, finance,...     1143     1142   \n",
       "A health science (ex. nursing, pharmacy, radiol...      150      152   \n",
       "A humanities discipline (ex. literature, histor...     1130     1117   \n",
       "A natural science (ex. biology, chemistry, phys...     2279     2260   \n",
       "A social science (ex. anthropology, psychology,...      955      949   \n",
       "Another engineering discipline (ex. civil, elec...     4181     4141   \n",
       "Computer science, computer engineering, or soft...    31937    31792   \n",
       "Fine arts or performing arts (ex. graphic desig...      882      878   \n",
       "I never declared a major                                528      563   \n",
       "Information systems, information technology, or...     3392     3387   \n",
       "Mathematics or statistics                              2012     1989   \n",
       "Web development or web design                          1930     1992   \n",
       "\n",
       "                                                    YearsCode  ConvertedComp  \\\n",
       "UndergradMajor                                                                 \n",
       "A business discipline (ex. accounting, finance,...       1154           1154   \n",
       "A health science (ex. nursing, pharmacy, radiol...        154            154   \n",
       "A humanities discipline (ex. literature, histor...       1138           1138   \n",
       "A natural science (ex. biology, chemistry, phys...       2303           2303   \n",
       "A social science (ex. anthropology, psychology,...        962            962   \n",
       "Another engineering discipline (ex. civil, elec...       4204           4204   \n",
       "Computer science, computer engineering, or soft...      32356          32356   \n",
       "Fine arts or performing arts (ex. graphic desig...        898            898   \n",
       "I never declared a major                                  575            575   \n",
       "Information systems, information technology, or...       3460           3460   \n",
       "Mathematics or statistics                                2030           2030   \n",
       "Web development or web design                            2030           2030   \n",
       "\n",
       "                                                      Age  Gender  Country  \\\n",
       "UndergradMajor                                                               \n",
       "A business discipline (ex. accounting, finance,...   1154    1154     1154   \n",
       "A health science (ex. nursing, pharmacy, radiol...    154     154      154   \n",
       "A humanities discipline (ex. literature, histor...   1138    1138     1138   \n",
       "A natural science (ex. biology, chemistry, phys...   2303    2303     2303   \n",
       "A social science (ex. anthropology, psychology,...    962     962      962   \n",
       "Another engineering discipline (ex. civil, elec...   4204    4204     4204   \n",
       "Computer science, computer engineering, or soft...  32356   32356    32356   \n",
       "Fine arts or performing arts (ex. graphic desig...    898     898      898   \n",
       "I never declared a major                              575     575      575   \n",
       "Information systems, information technology, or...   3460    3460     3460   \n",
       "Mathematics or statistics                            2030    2030     2030   \n",
       "Web development or web design                        2030    2030     2030   \n",
       "\n",
       "                                                    CountryAvgComp  ...  \\\n",
       "UndergradMajor                                                      ...   \n",
       "A business discipline (ex. accounting, finance,...            1154  ...   \n",
       "A health science (ex. nursing, pharmacy, radiol...             154  ...   \n",
       "A humanities discipline (ex. literature, histor...            1138  ...   \n",
       "A natural science (ex. biology, chemistry, phys...            2303  ...   \n",
       "A social science (ex. anthropology, psychology,...             962  ...   \n",
       "Another engineering discipline (ex. civil, elec...            4204  ...   \n",
       "Computer science, computer engineering, or soft...           32356  ...   \n",
       "Fine arts or performing arts (ex. graphic desig...             898  ...   \n",
       "I never declared a major                                       575  ...   \n",
       "Information systems, information technology, or...            3460  ...   \n",
       "Mathematics or statistics                                     2030  ...   \n",
       "Web development or web design                                 2030  ...   \n",
       "\n",
       "                                                    Angular/Angular.js  \\\n",
       "UndergradMajor                                                           \n",
       "A business discipline (ex. accounting, finance,...                1154   \n",
       "A health science (ex. nursing, pharmacy, radiol...                 154   \n",
       "A humanities discipline (ex. literature, histor...                1138   \n",
       "A natural science (ex. biology, chemistry, phys...                2303   \n",
       "A social science (ex. anthropology, psychology,...                 962   \n",
       "Another engineering discipline (ex. civil, elec...                4204   \n",
       "Computer science, computer engineering, or soft...               32356   \n",
       "Fine arts or performing arts (ex. graphic desig...                 898   \n",
       "I never declared a major                                           575   \n",
       "Information systems, information technology, or...                3460   \n",
       "Mathematics or statistics                                         2030   \n",
       "Web development or web design                                     2030   \n",
       "\n",
       "                                                    ASP.NET  Django  Flask  \\\n",
       "UndergradMajor                                                               \n",
       "A business discipline (ex. accounting, finance,...     1154    1154   1154   \n",
       "A health science (ex. nursing, pharmacy, radiol...      154     154    154   \n",
       "A humanities discipline (ex. literature, histor...     1138    1138   1138   \n",
       "A natural science (ex. biology, chemistry, phys...     2303    2303   2303   \n",
       "A social science (ex. anthropology, psychology,...      962     962    962   \n",
       "Another engineering discipline (ex. civil, elec...     4204    4204   4204   \n",
       "Computer science, computer engineering, or soft...    32356   32356  32356   \n",
       "Fine arts or performing arts (ex. graphic desig...      898     898    898   \n",
       "I never declared a major                                575     575    575   \n",
       "Information systems, information technology, or...     3460    3460   3460   \n",
       "Mathematics or statistics                              2030    2030   2030   \n",
       "Web development or web design                          2030    2030   2030   \n",
       "\n",
       "                                                    jQuery  Vue.js  Spring  \\\n",
       "UndergradMajor                                                               \n",
       "A business discipline (ex. accounting, finance,...    1154    1154    1154   \n",
       "A health science (ex. nursing, pharmacy, radiol...     154     154     154   \n",
       "A humanities discipline (ex. literature, histor...    1138    1138    1138   \n",
       "A natural science (ex. biology, chemistry, phys...    2303    2303    2303   \n",
       "A social science (ex. anthropology, psychology,...     962     962     962   \n",
       "Another engineering discipline (ex. civil, elec...    4204    4204    4204   \n",
       "Computer science, computer engineering, or soft...   32356   32356   32356   \n",
       "Fine arts or performing arts (ex. graphic desig...     898     898     898   \n",
       "I never declared a major                               575     575     575   \n",
       "Information systems, information technology, or...    3460    3460    3460   \n",
       "Mathematics or statistics                             2030    2030    2030   \n",
       "Web development or web design                         2030    2030    2030   \n",
       "\n",
       "                                                    React.js  Laravel  Drupal  \n",
       "UndergradMajor                                                                 \n",
       "A business discipline (ex. accounting, finance,...      1154     1154    1154  \n",
       "A health science (ex. nursing, pharmacy, radiol...       154      154     154  \n",
       "A humanities discipline (ex. literature, histor...      1138     1138    1138  \n",
       "A natural science (ex. biology, chemistry, phys...      2303     2303    2303  \n",
       "A social science (ex. anthropology, psychology,...       962      962     962  \n",
       "Another engineering discipline (ex. civil, elec...      4204     4204    4204  \n",
       "Computer science, computer engineering, or soft...     32356    32356   32356  \n",
       "Fine arts or performing arts (ex. graphic desig...       898      898     898  \n",
       "I never declared a major                                 575      575     575  \n",
       "Information systems, information technology, or...      3460     3460    3460  \n",
       "Mathematics or statistics                               2030     2030    2030  \n",
       "Web development or web design                           2030     2030    2030  \n",
       "\n",
       "[12 rows x 111 columns]"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019.groupby(by=['UndergradMajor']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['YearsCode', 'CountryAvgComp', 'EducationAvgComp',\n",
       "       'Academic researcher', 'Data or business analyst',\n",
       "       'Data scientist or machine learning specialist',\n",
       "       'Database administrator', 'Designer', 'DevOps specialist',\n",
       "       'Developer, QA or test', 'Developer, back-end',\n",
       "       'Developer, desktop or enterprise applications',\n",
       "       'Developer, embedded applications or devices', 'Developer, front-end',\n",
       "       'Developer, full-stack', 'Developer, game or graphics',\n",
       "       'Developer, mobile', 'Educator', 'Engineer, data',\n",
       "       'Engineer, site reliability', 'Engineering manager', 'Product manager',\n",
       "       'Scientist', 'Senior executive/VP', 'Student', 'System administrator',\n",
       "       'Assembly', 'Bash/Shell/PowerShell', 'C', 'C#', 'C++', 'Go', 'HTML/CSS',\n",
       "       'Java', 'JavaScript', 'Kotlin', 'Objective-C', 'Other(s):', 'PHP',\n",
       "       'Python', 'R', 'Ruby', 'Rust', 'SQL', 'Scala', 'Swift', 'TypeScript',\n",
       "       'VBA', 'Cassandra', 'DynamoDB', 'Elasticsearch', 'Firebase', 'MariaDB',\n",
       "       'Microsoft SQL Server', 'MongoDB', 'MySQL', 'Oracle', 'PostgreSQL',\n",
       "       'Redis', 'SQLite', 'Linux', 'Windows', 'Android',\n",
       "       'Google Cloud Platform', 'AWS', 'Docker', 'Heroku', 'MacOS', 'Slack',\n",
       "       'iOS', 'Microsoft Azure', 'WordPress', 'Arduino', 'Raspberry Pi',\n",
       "       'Kubernetes', 'Express', 'Ruby on Rails', 'Angular/Angular.js',\n",
       "       'ASP.NET', 'Django', 'Flask', 'jQuery', 'Vue.js', 'Spring', 'React.js',\n",
       "       'Laravel'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "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>YearsCode</th>\n",
       "      <th>CountryAvgComp</th>\n",
       "      <th>EducationAvgComp</th>\n",
       "      <th>Academic researcher</th>\n",
       "      <th>Data or business analyst</th>\n",
       "      <th>Data scientist or machine learning specialist</th>\n",
       "      <th>Database administrator</th>\n",
       "      <th>Designer</th>\n",
       "      <th>DevOps specialist</th>\n",
       "      <th>Developer, QA or test</th>\n",
       "      <th>...</th>\n",
       "      <th>Ruby on Rails</th>\n",
       "      <th>Angular/Angular.js</th>\n",
       "      <th>ASP.NET</th>\n",
       "      <th>Django</th>\n",
       "      <th>Flask</th>\n",
       "      <th>jQuery</th>\n",
       "      <th>Vue.js</th>\n",
       "      <th>Spring</th>\n",
       "      <th>React.js</th>\n",
       "      <th>Laravel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>48379.436893</td>\n",
       "      <td>134966.131508</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>249546.254589</td>\n",
       "      <td>134966.131508</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>134018.564909</td>\n",
       "      <td>134966.131508</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>151681.803922</td>\n",
       "      <td>117587.731065</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>28057.664916</td>\n",
       "      <td>120712.385650</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 86 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   YearsCode  CountryAvgComp  EducationAvgComp  Academic researcher  \\\n",
       "0          3    48379.436893     134966.131508                    0   \n",
       "1          3   249546.254589     134966.131508                    0   \n",
       "2         13   134018.564909     134966.131508                    0   \n",
       "3         12   151681.803922     117587.731065                    0   \n",
       "4         12    28057.664916     120712.385650                    0   \n",
       "\n",
       "   Data or business analyst  Data scientist or machine learning specialist  \\\n",
       "0                         0                                              0   \n",
       "1                         0                                              0   \n",
       "2                         1                                              1   \n",
       "3                         0                                              0   \n",
       "4                         1                                              1   \n",
       "\n",
       "   Database administrator  Designer  DevOps specialist  Developer, QA or test  \\\n",
       "0                       0         1                  0                      0   \n",
       "1                       0         0                  0                      0   \n",
       "2                       1         0                  0                      0   \n",
       "3                       1         0                  1                      1   \n",
       "4                       1         0                  0                      0   \n",
       "\n",
       "   ...  Ruby on Rails  Angular/Angular.js  ASP.NET  Django  Flask  jQuery  \\\n",
       "0  ...              0                   0        0       0      0       0   \n",
       "1  ...              0                   0        0       0      0       0   \n",
       "2  ...              0                   0        0       0      0       0   \n",
       "3  ...              1                   0        0       0      0       0   \n",
       "4  ...              0                   1        1       1      1       1   \n",
       "\n",
       "   Vue.js  Spring  React.js  Laravel  \n",
       "0       0       0         0        0  \n",
       "1       0       0         0        0  \n",
       "2       0       0         0        0  \n",
       "3       0       0         0        0  \n",
       "4       0       0         0        0  \n",
       "\n",
       "[5 rows x 86 columns]"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{\n",
    "    YearsCode: 0,\n",
    "    CountryAvgComp: \"CA\",\n",
    "    EducationAvgComp: 'Bachelor’s degree (BA, BS, B.Eng., etc.)',\n",
    "    Jobs...,\n",
    "    Skills...\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019['YearsCode'].unique().max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [],
   "source": [
    "country_map = df_2019[['Country', 'CountryAvgComp']].drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [],
   "source": [
    "edu_map = df_2019[['EdLevel', 'EducationAvgComp']].drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {},
   "outputs": [],
   "source": [
    "edu_map.to_csv('edu_map.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {},
   "outputs": [],
   "source": [
    "country_map.to_csv('country_map.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = 'linear_model.sav'\n",
    "pickle.dump(lm, open(filename, 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'YearsCode': [12],\n",
       " 'CountryAvgComp': [81214.77972238987],\n",
       " 'EducationAvgComp': [120712.38565022421],\n",
       " 'Academic researcher': [0],\n",
       " 'Data or business analyst': [0],\n",
       " 'Data scientist or machine learning specialist': [0],\n",
       " 'Database administrator': [0],\n",
       " 'Designer': [0],\n",
       " 'DevOps specialist': [0],\n",
       " 'Developer, QA or test': [0],\n",
       " 'Developer, back-end': [0],\n",
       " 'Developer, desktop or enterprise applications': [0],\n",
       " 'Developer, embedded applications or devices': [1],\n",
       " 'Developer, front-end': [0],\n",
       " 'Developer, full-stack': [0],\n",
       " 'Developer, game or graphics': [0],\n",
       " 'Developer, mobile': [0],\n",
       " 'Educator': [0],\n",
       " 'Engineer, data': [0],\n",
       " 'Engineer, site reliability': [0],\n",
       " 'Engineering manager': [0],\n",
       " 'Product manager': [0],\n",
       " 'Scientist': [0],\n",
       " 'Senior executive/VP': [0],\n",
       " 'Student': [0],\n",
       " 'System administrator': [0],\n",
       " 'Assembly': [1],\n",
       " 'Bash/Shell/PowerShell': [0],\n",
       " 'C': [1],\n",
       " 'C#': [0],\n",
       " 'C++': [1],\n",
       " 'Go': [1],\n",
       " 'HTML/CSS': [0],\n",
       " 'Java': [0],\n",
       " 'JavaScript': [0],\n",
       " 'Kotlin': [0],\n",
       " 'Objective-C': [0],\n",
       " 'Other(s):': [0],\n",
       " 'PHP': [0],\n",
       " 'Python': [0],\n",
       " 'R': [0],\n",
       " 'Ruby': [0],\n",
       " 'Rust': [0],\n",
       " 'SQL': [0],\n",
       " 'Scala': [0],\n",
       " 'Swift': [0],\n",
       " 'TypeScript': [0],\n",
       " 'VBA': [0],\n",
       " 'Cassandra': [0],\n",
       " 'DynamoDB': [0],\n",
       " 'Elasticsearch': [0],\n",
       " 'Firebase': [0],\n",
       " 'MariaDB': [0],\n",
       " 'Microsoft SQL Server': [0],\n",
       " 'MongoDB': [0],\n",
       " 'MySQL': [0],\n",
       " 'Oracle': [0],\n",
       " 'PostgreSQL': [0],\n",
       " 'Redis': [0],\n",
       " 'SQLite': [0],\n",
       " 'Linux': [1],\n",
       " 'Windows': [1],\n",
       " 'Android': [1],\n",
       " 'Google Cloud Platform': [0],\n",
       " 'AWS': [0],\n",
       " 'Docker': [0],\n",
       " 'Heroku': [0],\n",
       " 'MacOS': [0],\n",
       " 'Slack': [0],\n",
       " 'iOS': [0],\n",
       " 'Microsoft Azure': [0],\n",
       " 'WordPress': [0],\n",
       " 'Arduino': [1],\n",
       " 'Raspberry Pi': [1],\n",
       " 'Kubernetes': [0],\n",
       " 'Express': [0],\n",
       " 'Ruby on Rails': [0],\n",
       " 'Angular/Angular.js': [0],\n",
       " 'ASP.NET': [0],\n",
       " 'Django': [0],\n",
       " 'Flask': [0],\n",
       " 'jQuery': [0],\n",
       " 'Vue.js': [0],\n",
       " 'Spring': [0],\n",
       " 'React.js': [0],\n",
       " 'Laravel': [0]}"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.sample(1).to_dict('list')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "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>EdLevel</th>\n",
       "      <th>EducationAvgComp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>134966.131508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Some college/university study without earning ...</td>\n",
       "      <td>117587.731065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>120712.385650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Other doctoral degree (Ph.D, Ed.D., etc.)</td>\n",
       "      <td>171504.379046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>Primary/elementary school</td>\n",
       "      <td>95072.546154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>Associate degree</td>\n",
       "      <td>146191.275269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>Secondary school (e.g. American high school, G...</td>\n",
       "      <td>85330.023734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>127110.738423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>Professional degree (JD, MD, etc.)</td>\n",
       "      <td>86490.193289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>94</td>\n",
       "      <td>I never completed any formal education</td>\n",
       "      <td>154087.313636</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              EdLevel  EducationAvgComp\n",
       "0            Bachelor’s degree (BA, BS, B.Eng., etc.)     134966.131508\n",
       "3   Some college/university study without earning ...     117587.731065\n",
       "4         Master’s degree (MA, MS, M.Eng., MBA, etc.)     120712.385650\n",
       "6           Other doctoral degree (Ph.D, Ed.D., etc.)     171504.379046\n",
       "14                          Primary/elementary school      95072.546154\n",
       "15                                   Associate degree     146191.275269\n",
       "22  Secondary school (e.g. American high school, G...      85330.023734\n",
       "33                                                NaN     127110.738423\n",
       "45                 Professional degree (JD, MD, etc.)      86490.193289\n",
       "94             I never completed any formal education     154087.313636"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edu_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "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>Country</th>\n",
       "      <th>CountryAvgComp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>48379.436893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "      <td>249546.254589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Canada</td>\n",
       "      <td>134018.564909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>151681.803922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>India</td>\n",
       "      <td>28057.664916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43930</td>\n",
       "      <td>Seychelles</td>\n",
       "      <td>61308.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44142</td>\n",
       "      <td>Malawi</td>\n",
       "      <td>11532.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49696</td>\n",
       "      <td>Democratic People's Republic of Korea</td>\n",
       "      <td>32880.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>51153</td>\n",
       "      <td>Chad</td>\n",
       "      <td>6288.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>51750</td>\n",
       "      <td>Mali</td>\n",
       "      <td>10476.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>161 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Country  CountryAvgComp\n",
       "0                                   Thailand    48379.436893\n",
       "1                              United States   249546.254589\n",
       "2                                     Canada   134018.564909\n",
       "3                                New Zealand   151681.803922\n",
       "4                                      India    28057.664916\n",
       "...                                      ...             ...\n",
       "43930                             Seychelles    61308.000000\n",
       "44142                                 Malawi    11532.000000\n",
       "49696  Democratic People's Republic of Korea    32880.000000\n",
       "51153                                   Chad     6288.000000\n",
       "51750                                   Mali    10476.000000\n",
       "\n",
       "[161 rows x 2 columns]"
      ]
     },
     "execution_count": 271,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "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>Employment</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>...</th>\n",
       "      <th>Angular/Angular.js</th>\n",
       "      <th>ASP.NET</th>\n",
       "      <th>Django</th>\n",
       "      <th>Flask</th>\n",
       "      <th>jQuery</th>\n",
       "      <th>Vue.js</th>\n",
       "      <th>Spring</th>\n",
       "      <th>React.js</th>\n",
       "      <th>Laravel</th>\n",
       "      <th>Drupal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>107</td>\n",
       "      <td>155</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>500 to 999 employees</td>\n",
       "      <td>17</td>\n",
       "      <td>962424.0</td>\n",
       "      <td>34</td>\n",
       "      <td>Man</td>\n",
       "      <td>Germany</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>109</td>\n",
       "      <td>157</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>10 to 19 employees</td>\n",
       "      <td>8</td>\n",
       "      <td>960000.0</td>\n",
       "      <td>25</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>166</td>\n",
       "      <td>245</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Some college/university study without earning ...</td>\n",
       "      <td>Another engineering discipline (ex. civil, ele...</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>3</td>\n",
       "      <td>649536.0</td>\n",
       "      <td>35</td>\n",
       "      <td>Man</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>177</td>\n",
       "      <td>262</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>9</td>\n",
       "      <td>864000.0</td>\n",
       "      <td>24</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>193</td>\n",
       "      <td>286</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>8</td>\n",
       "      <td>618708.0</td>\n",
       "      <td>23</td>\n",
       "      <td>Man</td>\n",
       "      <td>Ireland</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55594</td>\n",
       "      <td>88493</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Some college/university study without earning ...</td>\n",
       "      <td>A natural science (ex. biology, chemistry, phy...</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>16</td>\n",
       "      <td>628068.0</td>\n",
       "      <td>32</td>\n",
       "      <td>Man</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55680</td>\n",
       "      <td>88648</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>A business discipline (ex. accounting, finance...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>2</td>\n",
       "      <td>900000.0</td>\n",
       "      <td>38</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55712</td>\n",
       "      <td>88696</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>2</td>\n",
       "      <td>720000.0</td>\n",
       "      <td>22</td>\n",
       "      <td>Man</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55722</td>\n",
       "      <td>88714</td>\n",
       "      <td>Independent contractor, freelancer, or self-em...</td>\n",
       "      <td>Other doctoral degree (Ph.D, Ed.D., etc.)</td>\n",
       "      <td>Mathematics or statistics</td>\n",
       "      <td>2-9 employees</td>\n",
       "      <td>47</td>\n",
       "      <td>732852.0</td>\n",
       "      <td>63</td>\n",
       "      <td>Man</td>\n",
       "      <td>Canada</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55812</td>\n",
       "      <td>88868</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Some college/university study without earning ...</td>\n",
       "      <td>Web development or web design</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>15</td>\n",
       "      <td>797436.0</td>\n",
       "      <td>30</td>\n",
       "      <td>Man</td>\n",
       "      <td>Germany</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1037 rows × 112 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Respondent                                         Employment  \\\n",
       "107           155                                 Employed full-time   \n",
       "109           157                                 Employed full-time   \n",
       "166           245                                 Employed full-time   \n",
       "177           262                                 Employed full-time   \n",
       "193           286                                 Employed full-time   \n",
       "...           ...                                                ...   \n",
       "55594       88493                                 Employed full-time   \n",
       "55680       88648                                 Employed full-time   \n",
       "55712       88696                                 Employed full-time   \n",
       "55722       88714  Independent contractor, freelancer, or self-em...   \n",
       "55812       88868                                 Employed full-time   \n",
       "\n",
       "                                                 EdLevel  \\\n",
       "107          Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "109             Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "166    Some college/university study without earning ...   \n",
       "177             Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "193             Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "...                                                  ...   \n",
       "55594  Some college/university study without earning ...   \n",
       "55680           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "55712           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "55722          Other doctoral degree (Ph.D, Ed.D., etc.)   \n",
       "55812  Some college/university study without earning ...   \n",
       "\n",
       "                                          UndergradMajor  \\\n",
       "107    Computer science, computer engineering, or sof...   \n",
       "109    Computer science, computer engineering, or sof...   \n",
       "166    Another engineering discipline (ex. civil, ele...   \n",
       "177    Computer science, computer engineering, or sof...   \n",
       "193    Computer science, computer engineering, or sof...   \n",
       "...                                                  ...   \n",
       "55594  A natural science (ex. biology, chemistry, phy...   \n",
       "55680  A business discipline (ex. accounting, finance...   \n",
       "55712  Computer science, computer engineering, or sof...   \n",
       "55722                          Mathematics or statistics   \n",
       "55812                      Web development or web design   \n",
       "\n",
       "                        OrgSize  YearsCode  ConvertedComp  Age Gender  \\\n",
       "107        500 to 999 employees         17       962424.0   34    Man   \n",
       "109          10 to 19 employees          8       960000.0   25    Man   \n",
       "166    10,000 or more employees          3       649536.0   35    Man   \n",
       "177    10,000 or more employees          9       864000.0   24    Man   \n",
       "193    10,000 or more employees          8       618708.0   23    Man   \n",
       "...                         ...        ...            ...  ...    ...   \n",
       "55594        20 to 99 employees         16       628068.0   32    Man   \n",
       "55680      100 to 499 employees          2       900000.0   38    Man   \n",
       "55712  10,000 or more employees          2       720000.0   22    Man   \n",
       "55722             2-9 employees         47       732852.0   63    Man   \n",
       "55812      100 to 499 employees         15       797436.0   30    Man   \n",
       "\n",
       "              Country  ...  Angular/Angular.js  ASP.NET  Django  Flask  \\\n",
       "107           Germany  ...                   0        0       0      0   \n",
       "109     United States  ...                   0        1       0      0   \n",
       "166            Sweden  ...                   1        0       0      0   \n",
       "177     United States  ...                   1        1       0      0   \n",
       "193           Ireland  ...                   0        0       0      0   \n",
       "...               ...  ...                 ...      ...     ...    ...   \n",
       "55594  United Kingdom  ...                   0        0       0      0   \n",
       "55680   United States  ...                   0        0       0      0   \n",
       "55712   United States  ...                   0        0       0      0   \n",
       "55722          Canada  ...                   0        0       0      0   \n",
       "55812         Germany  ...                   1        0       0      0   \n",
       "\n",
       "       jQuery  Vue.js  Spring  React.js  Laravel  Drupal  \n",
       "107         0       0       0         1        0       0  \n",
       "109         0       1       0         0        0       0  \n",
       "166         0       0       0         0        0       0  \n",
       "177         0       0       0         1        0       0  \n",
       "193         0       1       0         0        0       0  \n",
       "...       ...     ...     ...       ...      ...     ...  \n",
       "55594       0       0       0         0        0       0  \n",
       "55680       0       0       0         0        0       0  \n",
       "55712       0       0       0         1        0       0  \n",
       "55722       0       0       0         0        0       0  \n",
       "55812       1       0       0         1        0       0  \n",
       "\n",
       "[1037 rows x 112 columns]"
      ]
     },
     "execution_count": 300,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019[df_2019['ConvertedComp']>600000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "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>Employment</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>...</th>\n",
       "      <th>Angular/Angular.js</th>\n",
       "      <th>ASP.NET</th>\n",
       "      <th>Django</th>\n",
       "      <th>Flask</th>\n",
       "      <th>jQuery</th>\n",
       "      <th>Vue.js</th>\n",
       "      <th>Spring</th>\n",
       "      <th>React.js</th>\n",
       "      <th>Laravel</th>\n",
       "      <th>Drupal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 112 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Respondent, Employment, EdLevel, UndergradMajor, OrgSize, YearsCode, ConvertedComp, Age, Gender, Country, CountryAvgComp, EducationAvgComp, MajorAvgComp, GenderCode, NewOrgSize, Academic researcher, Data or business analyst, Data scientist or machine learning specialist, Database administrator, Designer, DevOps specialist, Developer, QA or test, Developer, back-end, Developer, desktop or enterprise applications, Developer, embedded applications or devices, Developer, front-end, Developer, full-stack, Developer, game or graphics, Developer, mobile, Educator, Engineer, data, Engineer, site reliability, Engineering manager, Marketing or sales professional, Product manager, Scientist, Senior executive/VP, Student, System administrator, LanguageWorkedWith, DatabaseWorkedWith, PlatformWorkedWith, WebFrameWorkedWith, Assembly, Bash/Shell/PowerShell, C, C#, C++, Clojure, Dart, Elixir, Erlang, F#, Go, HTML/CSS, Java, JavaScript, Kotlin, Objective-C, Other(s):, PHP, Python, R, Ruby, Rust, SQL, Scala, Swift, TypeScript, VBA, WebAssembly, Cassandra, Couchbase, DynamoDB, Elasticsearch, Firebase, MariaDB, Microsoft SQL Server, MongoDB, MySQL, Oracle, PostgreSQL, Redis, SQLite, Linux, Windows, Android, Google Cloud Platform, AWS, Docker, Heroku, MacOS, Slack, IBM Cloud or Watson, iOS, Microsoft Azure, WordPress, Arduino, Raspberry Pi, Kubernetes, ...]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 112 columns]"
      ]
     },
     "execution_count": 301,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019[df_2019['Country']=='Antarctica']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "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>YearsCode</th>\n",
       "      <th>CountryAvgComp</th>\n",
       "      <th>EducationAvgComp</th>\n",
       "      <th>Academic researcher</th>\n",
       "      <th>Data or business analyst</th>\n",
       "      <th>Data scientist or machine learning specialist</th>\n",
       "      <th>Database administrator</th>\n",
       "      <th>Designer</th>\n",
       "      <th>DevOps specialist</th>\n",
       "      <th>Developer, QA or test</th>\n",
       "      <th>...</th>\n",
       "      <th>Ruby on Rails</th>\n",
       "      <th>Angular/Angular.js</th>\n",
       "      <th>ASP.NET</th>\n",
       "      <th>Django</th>\n",
       "      <th>Flask</th>\n",
       "      <th>jQuery</th>\n",
       "      <th>Vue.js</th>\n",
       "      <th>Spring</th>\n",
       "      <th>React.js</th>\n",
       "      <th>Laravel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 86 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [YearsCode, CountryAvgComp, EducationAvgComp, Academic researcher, Data or business analyst, Data scientist or machine learning specialist, Database administrator, Designer, DevOps specialist, Developer, QA or test, Developer, back-end, Developer, desktop or enterprise applications, Developer, embedded applications or devices, Developer, front-end, Developer, full-stack, Developer, game or graphics, Developer, mobile, Educator, Engineer, data, Engineer, site reliability, Engineering manager, Product manager, Scientist, Senior executive/VP, Student, System administrator, Assembly, Bash/Shell/PowerShell, C, C#, C++, Go, HTML/CSS, Java, JavaScript, Kotlin, Objective-C, Other(s):, PHP, Python, R, Ruby, Rust, SQL, Scala, Swift, TypeScript, VBA, Cassandra, DynamoDB, Elasticsearch, Firebase, MariaDB, Microsoft SQL Server, MongoDB, MySQL, Oracle, PostgreSQL, Redis, SQLite, Linux, Windows, Android, Google Cloud Platform, AWS, Docker, Heroku, MacOS, Slack, iOS, Microsoft Azure, WordPress, Arduino, Raspberry Pi, Kubernetes, Express, Ruby on Rails, Angular/Angular.js, ASP.NET, Django, Flask, jQuery, Vue.js, Spring, React.js, Laravel]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 86 columns]"
      ]
     },
     "execution_count": 303,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X[X['YearsCode']==np.nan]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Academic researcher',\n",
       " 'Data or business analyst',\n",
       " 'Data scientist or machine learning specialist',\n",
       " 'Database administrator',\n",
       " 'Designer',\n",
       " 'DevOps specialist',\n",
       " 'Developer, QA or test',\n",
       " 'Developer, back-end',\n",
       " 'Developer, desktop or enterprise applications',\n",
       " 'Developer, embedded applications or devices',\n",
       " 'Developer, front-end',\n",
       " 'Developer, full-stack',\n",
       " 'Developer, game or graphics',\n",
       " 'Developer, mobile',\n",
       " 'Educator',\n",
       " 'Engineer, data',\n",
       " 'Engineer, site reliability',\n",
       " 'Engineering manager',\n",
       " 'Marketing or sales professional',\n",
       " 'Product manager',\n",
       " 'Scientist',\n",
       " 'Senior executive/VP',\n",
       " 'Student',\n",
       " 'System administrator']"
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_positions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}